Main.Schedule History

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Lecture: Review of dynamic programming

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Lecture: Review of dynamic programming

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Week 16:

Monday, 12/3
Lecture: Go over the NP-completeness assignment and solved a few additional problems

Wednesday, 12/5
Lecture: Review of dynamic programming
Friday, 12/7
Lecture: Go over the local search assignment, and do a general review for the exam''

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Friday, 11/30
Lecture: Local search, continued.
Reading: Chapter 12 in Kleinberg and Tardos.
Written homework #8 is available.

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Wednesday, 11/28
Lecture: Local search, continued.
Reading: Chapter 12 in Kleinberg and Tardos.

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Week 15:

Monday, 11/26
Lecture: Coping with NP-completeness: local search [ slides ].
Reading: Chapter 12 in Kleinberg and Tardos.

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Week 14:

Thanksgiving. Have a good break!

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Wednesday, 11/13
Lecture: More NP-complete problems [ slides ].
Reading: Chapter 8.5 in Kleinberg and Tardos.

Friday, 11/15
Lecture: quiz and review of NP and NP-completeness

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Week 13:

Monday, 11/12
Lecture: P, NP, and NP-completeness - continued.
Reading: Chapter 8.3,8.4 in Kleinberg and Tardos.

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Friday, 11/8
Lecture: P, NP, and NP-completeness [ slides ].
Reading: Chapter 8.3,8.4 in Kleinberg and Tardos.

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Lecture: Reductions as a tool for showing problem hardness [ slides ].

to:

Lecture: Reductions as a tool for showing problem hardness [ slides ].

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Week 12:

Monday, 11/4
Lecture: Continue the applications of maximum network flow.
Reading: Chapter 7.5,7.7 in Kleinberg and Tardos.

Wednesday, 11/6
Lecture: Reductions as a tool for showing problem hardness [ slides ].
Reading: Chapter 8.1,8.2 in Kleinberg and Tardos.

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Reading: Chapter 7.5-7.7 in Kleinberg and Tardos.

to:

Reading: Chapter 7.5-7.7 in Kleinberg and Tardos.

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Assignments: The next written assignment is [[Path:../../pdfs/hw6.pdf| available].

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Assignments: The next written assignment is available.

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to:

Assignments: The next written assignment is [[Path:../../pdfs/hw6.pdf| available].

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Friday, 11/2
Lecture: Applications of maximum network flow [ slides ].
Reading: Chapter 7.5-7.7 in Kleinberg and Tardos.

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Reading: Chapter 7.1,7.2 in Kleinberg and Tardos.

Wednesday, 10/31
Lecture: Maximum network flow - continued.

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Week 11:

Monday, 10/29
Lecture: Maximum network flow [ slides ].
Reading: Chapter 7.1,7.2 in Kleinberg and Tardos.

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Friday, 10/26
Lecture: Dynamic programming - the Bellman-Ford algorithm for shortest paths [ slides ].
Reading: Chapter 6.8 in Kleinberg and Tardos.

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Reading: Chapter 6.6 in Kleinberg and Tardos.

Wednesday, 10/24
Lecture: Dynamic programming - linear-space sequence alignment using a hybrid dynamic programming/divide and conquer approach .

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Week 10:

Monday, 10/22
Lecture: Dynamic programming - we'll continue the discussion of sequence alignment.
Reading: Chapter 6.7 in Kleinberg and Tardos.

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Friday, 10/19
Lecture: Dynamic programming - sequence alignment [ slides ].
Reading: Chapter 6.6 in Kleinberg and Tardos.

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Wednesday, 10/17
Lecture: Dynamic programming - the knapsack problem (monday slides continued).
Reading: Chapter 6.4 in Kleinberg and Tardos.

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Lecture: Dynamic programming - weighted interval scheduling [ slides ].

to:

Lecture: Dynamic programming - weighted interval scheduling [ slides ].

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Week 8:

to:

Week 9:

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Monday, 10/15
Lecture: Dynamic programming - weighted interval scheduling [ slides ].
Reading: Chapter 6.1 in Kleinberg and Tardos.

Week 8:

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Friday, 10/12
Lecture: Divide and conquer algorithms - integer multiplication [ slides ].
Reading: Chapter 5.5 in Kleinberg and Tardos.

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Reading: Chapter 5.4 in Kleinberg and Tardos.

to:

Reading: Chapter 5.4 in Kleinberg and Tardos.

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Assignments: Written assignment #4 has been posted.

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Wednesday, 10/10
Lecture: Divide and conquer algorithms - closest pair problem [ slides ].
Reading: Chapter 5.4 in Kleinberg and Tardos.

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Week 8:

Monday, 10/8
Lecture: Divide and conquer algorithms [ slides ].
Reading: Chapter 5.1,5.2 in Kleinberg and Tardos.

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Lecture: Greedy algorithms - continue minimum spanning trees and Huffman encoding [ slides ].
Reading: Chapter 4.7,4.8 in Kleinberg and Tardos.

to:

Lecture: Greedy algorithms - continue minimum spanning trees.
Reading: Chapter 4.5 - 4.7 in Kleinberg and Tardos.

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Lecture: Huffman encoding - cont.

to:

Lecture: Greedy algorithms - Huffman encoding [ slides ].

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Week 7:

Monday, 10/1
Lecture: Greedy algorithms - continue minimum spanning trees and Huffman encoding [ slides ].
Reading: Chapter 4.7,4.8 in Kleinberg and Tardos.

Wednesday, 10/3
Lecture: Huffman encoding - cont.
Reading: Chapter 4.8 in Kleinberg and Tardos.

Friday, 10/5
Lecture: midterm.

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Lecture: Greedy algorithms - minimum spanning trees [ slides ].
Here's the [ demo ] of Dijkstra's algorithm.

to:

Lecture: Greedy algorithms - minimum spanning trees [ slides ].
Here's the demo of Dijkstra's algorithm.

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Lecture: Greedy algorithms - minimum spanning trees [ slides ]. Here's the [ demo ] of Dijkstra's algorithm.

to:

Lecture: Greedy algorithms - minimum spanning trees [ slides ].
Here's the [ demo ] of Dijkstra's algorithm.

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Friday, 9/28
Lecture: Greedy algorithms - minimum spanning trees [ slides ]. Here's the [ demo ] of Dijkstra's algorithm.
Reading: Chapter 4.5, 4.7 in Kleinberg and Tardos.

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Lecture: Greedy algorithms [ slides ].

to:

Lecture: Greedy algorithms - interval scheduling [ slides ].

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Lecture: Greedy algorithms [ slides ].

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Lecture: Greedy algorithms - Dijkstra's algorithm [ slides ].

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Reading: Chapter 3 in Kleinberg and Tardos.

to:

Reading: Chapter 4.1 in Kleinberg and Tardos.

Wednesday, 9/26
Lecture: Greedy algorithms [ slides ].
Reading: Chapter 4.4 in Kleinberg and Tardos.

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Lecture: Greedy algorithms [ Path:../../pdfs/04_greedy.pdf ].

to:

Lecture: Greedy algorithms [ slides ].

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Week 6:

Monday, 9/24
Lecture: Greedy algorithms [ Path:../../pdfs/04_greedy.pdf ].
Reading: Chapter 3 in Kleinberg and Tardos.

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Lecture: Graphs - bipartite graphs, strongly connected components
.

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Lecture: Graphs - bipartite graphs, strongly connected components.

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Friday, 9/21
Lecture: Graphs - DAGs.
Reading: Chapter 3 in Kleinberg and Tardos.

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Lecture: Graphs - DFS, bipartite graphs.

to:

Lecture: Graphs - DFS.

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Wednesday, 9/19
Lecture: Graphs - bipartite graphs, strongly connected components
. Reading: Chapter 3 in Kleinberg and Tardos.

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Friday, 9/31

to:

Friday, 8/31

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Assignments: written assignment 3 is posted.

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Week 5:

Monday, 9/17
Lecture: Graphs - DFS, bipartite graphs.
Reading: Chapter 3 in Kleinberg and Tardos.

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Lecture: Graphs and graph traversal [ slides ].

to:

Lecture: Graphs [ slides ].

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Lecture: Graphs - traversal and bipartite graphs (continuing graph slide set).

to:

Lecture: Graphs - graph traversal using BFS (continuing graph slide set).

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Wednesday, 9/12
Lecture: Graphs and graph traversal [ slides ].
Reading: Chapter 3 in Kleinberg and Tardos.

Friday, 9/14
Lecture: Graphs - traversal and bipartite graphs (continuing graph slide set).
Reading: Chapter 3 in Kleinberg and Tardos.

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Reading: Chapter 2 in Kleinberg and Tardos.

to:

Reading: Chapter 2 in Kleinberg and Tardos.
Assignments: written assignment 2 is posted.

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Assignments: Written assignment 1 is available.

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Assignments: Written assignment 1 is available.

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Week 2:

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Week 4:

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Lecture: Finish Big-O analysis.

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Lecture: Finish Big-O analysis.

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Week 2:

Monday, 9/10
Lecture: Finish Big-O analysis. Reading: Chapter 2 in Kleinberg and Tardos.

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Friday, 9/7
Lecture: More Big-O. Reading: Chapter 2 in Kleinberg and Tardos.

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Reading: Chapter 2 in Kleinberg and Tardos.

to:

Reading: Chapter 2 in Kleinberg and Tardos.

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Week 3:

Wednesday, 9/5
Lecture: On friday we just started on Big O analysis. We will continue this topic. Reading: Chapter 2 in Kleinberg and Tardos. Assignments: written assignment 1 is due in class on Wednesday, and programming assignment 1 is due thursday at 5pm.

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Lecture: Big O analysis slides ]. quiz on big O.

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Lecture: Big O analysis [ slides ]. quiz on big O.

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Lecture: Big O analysis. There will be a quiz.

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Lecture: Big O analysis slides ]. quiz on big O.

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Lecture: Crash course in Python. Here's the set code I showed.

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Lecture: Crash course in Python. Here's the set code I showed.

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Python intro sessions: The material covered in this week's intro sessions is here.

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Lecture: We will be in a labs (215 and 225) to help you with your assignments.

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Lecture: We will be in a labs (215 and 225) to help you with your assignments.

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Lecture: Big-O analysis. Reading: Chapter 2 in Kleinberg and Tardos.

to:

Lecture: We will be in a labs (215 and 225) to help you with your assignments.
Friday, 9/31
Lecture: Big O analysis. There will be a quiz.
Reading: Chapter 2 in Kleinberg and Tardos.

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Wednesday, 8/29'

to:

Wednesday, 8/29

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Week 2:

Monday, 8/27
Lecture: Finish discussion of the stable matching problem. Representative problems. Reading: Chapter 1 in Kleinberg and Tardos.

Wednesday, 8/29'
Lecture: Big-O analysis. Reading: Chapter 2 in Kleinberg and Tardos.

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Assignments: Written assignment 1 is available.

to:

Assignments: Written assignment 1 is available.

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Assignments: Written assignment 1 is available.

to:

Assignments: Written assignment 1 is available.

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Reading: Chapter 1 in Kleinberg and Tardos.

to:

Reading: Chapter 1 in Kleinberg and Tardos.
Assignments: Written assignment 1 is available.

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Python intro sessions: The material covered in this week's intro sessions is here.

to:

Python intro sessions: The material covered in this week's intro sessions is here.

Friday, 8/24
Lecture: The Gale Shapely algorithm for the stable matching problem (continuing monday's slide set).
Reading: Chapter 1 in Kleinberg and Tardos.

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Lecture: Crash course in Python, and continuation of the stable matching slide set.
Reading: Chapter 1 in Kleinberg and Tardos.

to:

Lecture: Crash course in Python. Here's the set code I showed.

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Python intro sessions: The material covered in this week's intro sessions is here.

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Links:: Here's a nice demo and explanation of the stable matching problem. The NRMP explains their matching algorithm, which is a variant of the Gale Shapley algorithm.

to:

Links: Here's a nice demo and explanation of the stable matching problem. The NRMP explains their matching algorithm, which is a variant of the Gale Shapley algorithm.

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Links:: Here's a nice demo and explanation of the stable matching problem. The NRMP explains their matching algorithm, which is a variant of the Gale Shapley algorithm.

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Wed, 8/22
Lecture: Crash course in Python, and continuation of the stable matching slide set.
Reading: Chapter 1 in Kleinberg and Tardos.

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Lecture: Course introduction and the stable matching problem [ slides ].

to:

Lecture: Course introduction and the stable matching problem [ slides ].

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Lecture: Course introduction
The stable matching problem.

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Lecture: Course introduction and the stable matching problem [ slides ].

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Tuesday, 1/17

to:

Monday, 8/20

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A crash course in Python. Here's an example Python class: set.

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Week 16:

Tuesday, 5/1
Lecture: Coping with NP-completeness [ slides ].
Reading: Chapters 10-13 in Kleinberg and Tardos

Thursday, 5/3
Lecture: Review for final - please prepare questions!

Week 15:

Tuesday, 4/24
Lecture: NP-completeness [ slides ].
Reading: Chapter 8.3,8.4 in Kleinberg and Tardos

Thursday, 4/26
Lecture: More NP-complete problems [ slides ].
Reading: Chapter 8.5 in Kleinberg and Tardos

Week 14:

Tuesday, 4/17
Lecture: Applications of the Maxflow problem (continue with Thursday's slide set)
Reading: Chapter 7.6,7.7,7.10 in Kleinberg and Tardos

Thursday, 4/19
Lecture: Reductions as a tool for showing problem hardness [ slides ].
Reading: Chapter 8.1,8.2 in Kleinberg and Tardos

Week 13:

Tuesday, 4/10
Lecture: The Maxflow problem and the Ford-Fulckerson algorithm (slides continued from Thursday).
Reading: Chapter 7.1,7.2 in Kleinberg and Tardos

Thursday, 4/12
Lecture: Applications of the Maxflow problem [ slides ]. And here's the maxflow demo I showed.
Reading: Chapter 7.5 in Kleinberg and Tardos

Week 12:

Tuesday, 4/3
Lecture: Shortest paths using dynamic programming - [ slides ].
Reading: Chapter 6.8 in Kleinberg and Tardos

Thursday, 4/5
Lecture: We'll continue the Bellman-Ford algorithm and start on the Maxflow problem [ slides ].
Reading: Chapter 7.1,7.2 in Kleinberg and Tardos

Week 11:

Tuesday, 3/27
Lecture: Dynamic programming - subset sums and knapsack problems [ slides ].
Reading: Chapter 6.4 in Kleinberg and Tardos

Thursday, 3/29
Lecture: Dynamic programming - sequence alignment [ slides ].
Reading: Chapter 6.6, 6.7 in Kleinberg and Tardos

Week 10:

Tuesday, 3/20
Lecture: Divide and conquer - finding closest pair of points [ slides ], integer multiplication [ slides ].
Reading: Chapter 5.4,5.5 in Kleinberg and Tardos.
Thursday, 3/22
Lecture: Dynamic programming - weighted interval scheduling [ slides ].
Reading: Chapter 6.1,6.2 in Kleinberg and Tardos

Week 9:

Spring break

Week 8:

Tuesday, 3/6
Lecture: Divide and conquer and preparation for midterm.
Thursday, 3/8
Midterm.

Week 7:

Tuesday, 2/28
Lecture: Huffman encoding [ slides ].
Reading: Chapter 4.8 in Kleinberg and Tardos.
Thursday, 3/1
Lecture: Divide and conquer [ slides ].
Reading: Chapter 5.1,5.2 in Kleinberg and Tardos.
Here's a cute youtube video on divide and conquer.

Week 6:

Tuesday, 2/21
Lecture: More MST algorithms (cont).
Reading: Chapter 4.5 in Kleinberg and Tardos.
Thursday, 2/23
Lecture: Data clustering, Dijkstra's algorithm [ slides ].
Reading: Chapter 4.4, 4.7 in Kleinberg and Tardos.

Week 5:

Tuesday, 2/14
Lecture: Introduction to greedy algorithms [ slides ].
Reading: Chapter 4.1 in Kleinberg and Tardos.
Thursday, 2/16
Lecture: Greedy algorithms for the minimum spanning tree problem [ slides ].
Reading: Chapter 4.5, 4.7 in Kleinberg and Tardos.

Week 4:

Tuesday, 2/7
Lecture: Graphs - Analysis of BFS, connected components, bipartite graphs.
Reading: Chapter 3.2-3.4 in Kleinberg and Tardos.
Programming assignment #2 is available.

Thursday, 2/9
Lecture: Graphs - Analysis of BFS, connected components, bipartite graphs.
Reading: Chapter 3.5-3.6 in Kleinberg and Tardos.
Written assignment #3 is due.

Week 3:

Tuesday, 1/31
Lecture: Finish the discussion of big O.
Thursday, 2/2
Lecture: Graphs (representations of graphs and BFS) [ slides ]. Written homework 2 is due.
Reading: Chapter 3 in Kleinberg and Tardos.

Week 2:

Tuesday, 1/24
Lecture: Big O [ slides ].
Reading: Chapter 2 in Kleinberg and Tardos.
Thursday, 1/26
Lecture: Big O continued. There will be quiz on big O. Written homework is due.
Reading: Chapter 2 in Kleinberg and Tardos.

to:
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A crash course in Python. Here's the set Python class I showed.
The stable matching problem [ slides ] (slides updated on 1/19 to include the example shown in class)

to:

A crash course in Python. Here's an example Python class: set.
The stable matching problem.

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Thursday, 1/19
Lecture: We continued with the stable matching problem, and talked about representative problems that will be discussed in the course (almost finished the slides I posted on Tuesday).

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Week 16:

Tuesday, 5/1
Lecture: Coping with NP-completeness [ slides ].
Reading: Chapters 10-13 in Kleinberg and Tardos

Thursday, 5/3
Lecture: Review for final - please prepare questions!

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Thursday, 4/26
Lecture: More NP-complete problems [ slides ].
Reading: Chapter 8.5 in Kleinberg and Tardos

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Week 15:

Tuesday, 4/24
Lecture: NP-completeness [ slides ].
Reading: Chapter 8.3,8.4 in Kleinberg and Tardos

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Lecture: Reductions as a tool for showing problem hardness [ slides ].

to:

Lecture: Reductions as a tool for showing problem hardness [ slides ].

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Thursday, 4/19
Lecture: Reductions as a tool for showing problem hardness [ slides ].
Reading: Chapter 8.1,8.2 in Kleinberg and Tardos

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Week 13:

to:

Week 14:

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Week 13:

Tuesday, 4/17
Lecture: Applications of the Maxflow problem (continue with Thursday's slide set)
Reading: Chapter 7.6,7.7,7.10 in Kleinberg and Tardos

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Lecture: Applications of the Maxflow problem [ slides ].
Reading: Chapter 7.5,7.6 in Kleinberg and Tardos

to:

Lecture: Applications of the Maxflow problem [ slides ]. And here's the maxflow demo I showed.
Reading: Chapter 7.5 in Kleinberg and Tardos

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Lecture: We continued with the stable matching problem, and talked about representative problems that will be discussed in the course (almost finished the slides I posted on Tuesday).

to:

Lecture: We continued with the stable matching problem, and talked about representative problems that will be discussed in the course (almost finished the slides I posted on Tuesday).

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Week 12:

to:

Week 13:

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Week 12:

Tuesday, 4/10
Lecture: The Maxflow problem and the Ford-Fulckerson algorithm (slides continued from Thursday).
Reading: Chapter 7.1,7.2 in Kleinberg and Tardos

Thursday, 4/12
Lecture: Applications of the Maxflow problem [ slides ].
Reading: Chapter 7.5,7.6 in Kleinberg and Tardos

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Tuesday, 3/27

to:

Tuesday, 4/3

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Thursday, 4/5
Lecture: We'll continue the Bellman-Ford algorithm and start on the Maxflow problem [ slides ].
Reading: Chapter 7.1,7.2 in Kleinberg and Tardos

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Week 12:

Tuesday, 3/27
Lecture: Shortest paths using dynamic programming - [ slides ].
Reading: Chapter 6.8 in Kleinberg and Tardos

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Lecture: Dynamic programming - subset sums and knapsack problems.

to:

Lecture: Dynamic programming - subset sums and knapsack problems [ slides ].

Changed line 4 from:

Lecture: Dynamic programming - subset sums and knapsack problems.

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Lecture: Dynamic programming - subset sums and knapsack problems.

Changed line 4 from:

Lecture: Dynamic programming - subset sums and knapsack problem.

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Lecture: Dynamic programming - subset sums and knapsack problems.

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Thursday, 3/29
Lecture: Dynamic programming - sequence alignment [ slides ].
Reading: Chapter 6.6, 6.7 in Kleinberg and Tardos

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Lecture: Dynamic programming [ slides ].
Reading: Chapter 6.4 in Kleinberg and Tardos

to:

Lecture: Dynamic programming - weighted interval scheduling [ slides ].
Reading: Chapter 6.1,6.2 in Kleinberg and Tardos

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Week 11:

Tuesday, 3/27
Lecture: Dynamic programming - subset sums and knapsack problem. Reading: Chapter 6.4 in Kleinberg and Tardos

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Reading: Chapter 6.1,6.2,6.4 in Kleinberg and Tardos

to:

Reading: Chapter 6.4 in Kleinberg and Tardos

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Lecture: Dynamic programming [ slides ].

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Lecture: Dynamic programming [ slides ].

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Lecture: Dynamic programming Reading: Chapter 6 in Kleinberg and Tardos

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Lecture: Dynamic programming [ slides ].
Reading: Chapter 6.1,6.2,6.4 in Kleinberg and Tardos

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Lecture: Divide and conquer - finding closest pair of points [ slides ].
Reading: Chapter 5.4 in Kleinberg and Tardos.

to:

Lecture: Divide and conquer - finding closest pair of points [ slides ], integer multiplication [ slides ].
Reading: Chapter 5.4,5.5 in Kleinberg and Tardos.

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Lecture: Divide and conquer - integer multiplication [ slides ].
Reading: Chapter 5.5 in Kleinberg and Tardos.

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Lecture: Dynamic programming Reading: Chapter 6 in Kleinberg and Tardos

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Lecture: Divide and conquer - integer multiplication [ slides ].

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Lecture: Divide and conquer - integer multiplication [ slides ].

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Week 8:

Tuesday, 3/6

to:

Week 10:

Tuesday, 3/20

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Thursday, 3/22
Lecture: Divide and conquer - integer multiplication [ slides ].
Reading: Chapter 5.5 in Kleinberg and Tardos.

Week 9:

Spring break

Week 8:

Tuesday, 3/6
Lecture: Divide and conquer and preparation for midterm.

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Week 7:

to:

Week 8:

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Week 7:

Tuesday, 3/6
Lecture: Divide and conquer - finding closest pair of points [ slides ].
Reading: Chapter 5.4 in Kleinberg and Tardos.
Thursday, 3/8
Midterm.

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Fun: Here's a cute youtube video on divide and conquer.

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Here's a cute youtube video on divide and conquer.

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Fun: Here's a cute youtube video on divide and conquer.

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Thursday, 3/1
Lecture: Divide and conquer [ slides ].
Reading: Chapter 5.1,5.2 in Kleinberg and Tardos.

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Week 7:

Tuesday, 2/28
Lecture: Huffman encoding [ slides ].
Reading: Chapter 4.8 in Kleinberg and Tardos.

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Lecture: Data clustering, Dijkstra's algorithm [ slides ]. Huffman encoding [ slides ].
Reading: Chapter 4.4, 4.7,4.8 in Kleinberg and Tardos.

to:

Lecture: Data clustering, Dijkstra's algorithm [ slides ].
Reading: Chapter 4.4, 4.7 in Kleinberg and Tardos.

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Lecture: More MST algorithms (cont).

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Lecture: More MST algorithms (cont).

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Lecture: More MST algorithms, data clustering. Reading: Chapter 4.5, 4.7 in Kleinberg and Tardos.

to:

Lecture: More MST algorithms (cont). Reading: Chapter 4.5 in Kleinberg and Tardos.

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Lecture: Dijkstra's algorithm [ slides ]. Huffman encoding [ slides ].
Reading: Chapter 4.4, 4.8 in Kleinberg and Tardos.

to:

Lecture: Data clustering, Dijkstra's algorithm [ slides ]. Huffman encoding [ slides ].
Reading: Chapter 4.4, 4.7,4.8 in Kleinberg and Tardos.

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Lecture: Dijkstra's algorithm [ slides ]
. Huffman encoding [ slides ].

to:

Lecture: Dijkstra's algorithm [ slides ]. Huffman encoding [ slides ].

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Lecture: Dijkstra's algorithm [ slides ]
. Huffman encoding [ slides ] .

to:

Lecture: Dijkstra's algorithm [ slides ]
. Huffman encoding [ slides ].

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Lecture: More MST algorithms, data clustering. Dijkstra's algorithm [ slides ]
Reading: Chapter 4.4, 4.5, 4.7 in Kleinberg and Tardos.

to:

Lecture: More MST algorithms, data clustering. Reading: Chapter 4.5, 4.7 in Kleinberg and Tardos.

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Lecture: Dijkstra's algorithm (cont). Huffman encoding [ slides ] .

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Lecture: Dijkstra's algorithm [ slides ]
. Huffman encoding [ slides ] .

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Lecture: Dijkstra's algorithm (cont). Huffman encoding.

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Lecture: Dijkstra's algorithm (cont). Huffman encoding [ slides ] .

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Lecture: More MST algorithms, data clustering. Dijkstra's algorithm [ slides

to:

Lecture: More MST algorithms, data clustering. Dijkstra's algorithm [ slides ]

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Lecture: More MST algorithms, data clustering.
Reading: Chapter 4.5, 4.7 in Kleinberg and Tardos.

to:

Lecture: More MST algorithms, data clustering. Dijkstra's algorithm [ slides
Reading: Chapter 4.4, 4.5, 4.7 in Kleinberg and Tardos.
Thursday, 2/23
Lecture: Dijkstra's algorithm (cont). Huffman encoding.
Reading: Chapter 4.4, 4.8 in Kleinberg and Tardos.

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Week 6:

Tuesday, 2/21
Lecture: More MST algorithms, data clustering.
Reading: Chapter 4.5, 4.7 in Kleinberg and Tardos.

Added lines 6-10:

Thursday, 2/16
Lecture: Greedy algorithms for the minimum spanning tree problem [ slides ].
Reading: Chapter 4.5, 4.7 in Kleinberg and Tardos.

Added lines 1-6:

Week 5:

Tuesday, 2/14
Lecture: Introduction to greedy algorithms [ slides ].
Reading: Chapter 4.1 in Kleinberg and Tardos.

Added lines 7-11:

Thursday, 2/9
Lecture: Graphs - Analysis of BFS, connected components, bipartite graphs.
Reading: Chapter 3.5-3.6 in Kleinberg and Tardos.
Written assignment #3 is due.

Added lines 1-7:

Week 4:

Tuesday, 2/7
Lecture: Graphs - Analysis of BFS, connected components, bipartite graphs.
Reading: Chapter 3.2-3.4 in Kleinberg and Tardos.
Programming assignment #2 is available.

Changed line 14 from:

Lecture: Graphs [ slides ]. Written homework 2 is due.

to:

Lecture: Graphs (representations of graphs and BFS) [ slides ]. Written homework 2 is due.

Changed lines 4-6 from:

Lecture: Finish the discussion of big O, and start on graphs [ slides ].
Reading: Chapter 3 in Kleinberg and Tardos.

to:

Lecture: Finish the discussion of big O.

Changed line 7 from:

Lecture: More graphs - continuing tuesday's slide set. Written homework 2 is due.

to:

Lecture: Graphs [ slides ]. Written homework 2 is due.

Added lines 1-11:

Week 3:

Tuesday, 1/31
Lecture: Finish the discussion of big O, and start on graphs [ slides ].
Reading: Chapter 3 in Kleinberg and Tardos.
Thursday, 2/2
Lecture: More graphs - continuing tuesday's slide set. Written homework 2 is due.
Reading: Chapter 3 in Kleinberg and Tardos.

Changed line 7 from:

Tuesday, 1/26

to:

Thursday, 1/26

Changed lines 1-2 from:

Week 1:

to:

Week 2:

Added lines 1-12:

Week 1:

Tuesday, 1/24
Lecture: Big O [ slides ].
Reading: Chapter 2 in Kleinberg and Tardos.
Tuesday, 1/26
Lecture: Big O continued. There will be quiz on big O. Written homework is due.
Reading: Chapter 2 in Kleinberg and Tardos.

Changed lines 4-6 from:

Lecture: Course introduction - the stable marriage problem [ slides ]

to:

Lecture: Course introduction
A crash course in Python. Here's the set Python class I showed.
The stable matching problem [ slides ] (slides updated on 1/19 to include the example shown in class)

Changed line 10 from:

Lecture: We will continue with the stable marriage problem. Here is the set python class.

to:

Lecture: We continued with the stable matching problem, and talked about representative problems that will be discussed in the course (almost finished the slides I posted on Tuesday).

Deleted line 0:
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Tuesday, 1/18

to:

Tuesday, 1/17

Changed line 7 from:

Thursday, 1/20

to:

Thursday, 1/19

Changed lines 1-150 from:

Week 16:

Tuesday, 5/3
Lecture: No class

Thursday, 4/28
Lecture: Review for final

Week 15:

Tuesday, 4/26
Lecture: Local search algorithms [ slides ].
Reading: Sections 12.1 - 12.5 in Kleinberg and Tardos

Thursday, 4/28
Lecture: Local search (continued).

Week 14:

Tuesday, 4/19
Lecture: NP, NP-completeness and the class co-NP.
Reading: Section 8.4 and 8.9 in Kleinberg and Tardos. Papadimitriou has a nice retrospective on the importance of NP-completeness [ pdf ]
Thursday, 4/21
Lecture: NP-complete problems.
Reading: Sections 8.5,8.7 in Kleinberg and Tardos [ slides ] .

Week 13:

Tuesday, 4/12
Lecture: NP and computational intractability - polynomial reductions [ slides ].
Reading: Section 8.1 and 8.2 in Kleinberg and Tardos.
Thursday, 4/14
Lecture: NP and NP-completeness [ slides ]
Reading: Sections 8.3 and 8.4 in Kleinberg and Tardos.

Week 12:

Tuesday, 4/5
Lecture: Sequence alignment in linear space using dynamic programming and divide and conquer.
Reading: Section 6.6 in Kleinberg and Tardos.
Thursday, 4/7
Lecture: Shortest paths using dynamic programming [ slides ].
Reading: Section 6.8 in Kleinberg and Tardos.

Week 11:

Tuesday, 3/29
Lecture: Dynamic programming [ slides ]
Reading: Sections 6.1, 6.2,6.4 in Kleinberg and Tardos.
Thursday, 3/31
Lecture: Dynamic programming [ slides ]
Reading: Sections 6.6 in Kleinberg and Tardos.

Week 10:

Tuesday, 3/22
Lecture: Recurrence relations, counting inversions [ slides ]
Reading: Sections 5.2, 5.3 in Kleinberg and Tardos.

Thursday, 3/24
Lecture: Closest pair of points [ slides ]
Reading: Sections 5.5 in Kleinberg and Tardos.

Week 9:

Spring break!

Week 8:

Tuesday, 3/8
Lecture: Exam prep, Divide and conquer algorithms [ slides ]
Reading: Sections 5.1,5.2 in Kleinberg and Tardos.
Thursday, 3/10
Lecture: Midterm exam.

Week 7:

Tuesday, 3/1
Lecture: Greedy algorithms for the minimum spanning tree problem [ slides ]
Reading: Sections 4.5,4.7 in Kleinberg and Tardos.
Thursday, 3/3
Lecture: More on the minimum spanning tree problem.

Week 6:

Tuesday, 2/22
Lecture: Greedy scheduling algorithms
Reading: Sections 4.1,4.2 in Kleinberg and Tardos.
Thursday, 2/24
Lecture: Shortest paths and Dijkstra's algorithm [ slides ]
Reading: Sections 4.4 in Kleinberg and Tardos.

Week 5:

Tuesday, 2/15
Lecture: Finish graph algorithms - DAGs and topological ordering. Greedy algorithms [ slides ]
Reading: Sections 4.1,4.2 in Kleinberg and Tardos.
Written assignment 2 has been posted.
Thursday, 2/17
Lecture: Greedy algorithms - interval scheduling
Reading: Sections 4.1,4.2 in Kleinberg and Tardos.

Week 4:

Tuesday, 2/8
Lecture: Graph algorithms. Analysis of BFS and DFS. Bipartite graphs.
Reading: Chapter 3 in Kleinberg and Tardos.
Thursday, 2/10
Lecture: Graph algorithms. Connectivity in directed graphs
Reading: Chapter 3 in Kleinberg and Tardos.

Week 3:

Tuesday, 2/1
Lecture: Continued discussion of big-O
Reading: Chapter 2 in Kleinberg and Tardos.
Thursday, 2/3
Lecture: Graphs. Graph traversal with BFS [ slides ]
Reading: Chapter 3 in Kleinberg and Tardos.

Week 2:

Tuesday, 1/25
Lecture: Representative problems
Reading: Section 1.2 in Kleinberg and Tardos.
Thursday, 1/27
Lecture: Measuring algorithm efficiency [ slides ]
Reading: Chapter 2 in Kleinberg and Tardos.

to:
Changed line 9 from:

Lecture: We will continue with the stable marriage problem. Here is the set python class that I showed.

to:

Lecture: We will continue with the stable marriage problem. Here is the set python class.

Changed line 13 from:

Lecture: Local search algorithms [ slides ].

to:

Lecture: Local search algorithms [ slides ].

May 05, 2011, at 03:13 PM MST by 129.82.44.191 -
Added lines 1-9:

Week 16:

Tuesday, 5/3
Lecture: No class

Thursday, 4/28
Lecture: Review for final

Added lines 16-17:

Thursday, 4/28
Lecture: Local search (continued).

Added lines 1-7:

Week 15:

Tuesday, 4/26
Lecture: Local search algorithms [ slides ].
Reading: Sections 12.1 - 12.5 in Kleinberg and Tardos

Changed lines 9-11 from:

Reading: Sections 8.5,8.7 in Kleinberg and Tardos [ slides ] .

to:

Reading: Sections 8.5,8.7 in Kleinberg and Tardos [ slides ] .

Changed line 19 from:

Lecture: NP and NP-completeness [ slides ]

to:

Lecture: NP and NP-completeness [ slides ]

Changed line 9 from:

Reading: Sections 8.5-8.8 in Kleinberg and Tardos.

to:

Reading: Sections 8.5,8.7 in Kleinberg and Tardos [ slides ] .

Changed line 5 from:

Reading: Section 8.4 and 8.9 in Kleinberg and Tardos.

to:

Reading: Section 8.4 and 8.9 in Kleinberg and Tardos. Papadimitriou has a nice retrospective on the importance of NP-completeness [ pdf ]

Added lines 1-11:

Week 14:

Tuesday, 4/19
Lecture: NP, NP-completeness and the class co-NP.
Reading: Section 8.4 and 8.9 in Kleinberg and Tardos.
Thursday, 4/21
Lecture: NP-complete problems.
Reading: Sections 8.5-8.8 in Kleinberg and Tardos.

Changed lines 5-6 from:

Reading: Section 8.1,8.2 in Kleinberg and Tardos.

to:

Reading: Section 8.1 and 8.2 in Kleinberg and Tardos.
Thursday, 4/14
Lecture: NP and NP-completeness [ slides ]
Reading: Sections 8.3 and 8.4 in Kleinberg and Tardos.

Changed line 17 from:

Tuesday, 4/7

to:

Thursday, 4/7

Added lines 1-6:

Week 13:

Tuesday, 4/12
Lecture: NP and computational intractability - polynomial reductions [ slides ].
Reading: Section 8.1,8.2 in Kleinberg and Tardos.

Changed line 8 from:

Lecture: Shortest paths using dynamic programming [ slides ].

to:

Lecture: Shortest paths using dynamic programming [ slides ].

Changed lines 1-2 from:

Week 10:

to:

Week 12:

Tuesday, 4/5
Lecture: Sequence alignment in linear space using dynamic programming and divide and conquer.
Reading: Section 6.6 in Kleinberg and Tardos.
Tuesday, 4/7
Lecture: Shortest paths using dynamic programming [ slides ].
Reading: Section 6.8 in Kleinberg and Tardos.

Week 11:

Changed line 20 from:

Reading: Sections 6.6, 6.7 in Kleinberg and Tardos.

to:

Reading: Sections 6.6 in Kleinberg and Tardos.

Changed lines 5-9 from:

Reading: Sections 6.1, 6.2 in Kleinberg and Tardos.

to:

Reading: Sections 6.1, 6.2,6.4 in Kleinberg and Tardos.
Thursday, 3/31
Lecture: Dynamic programming [ slides ]
Reading: Sections 6.6, 6.7 in Kleinberg and Tardos.

Added lines 3-9:

Tuesday, 3/29
Lecture: Dynamic programming [ slides ]
Reading: Sections 6.1, 6.2 in Kleinberg and Tardos.

Week 10:

Changed line 15 from:

Tuesday, 3/24

to:

Thursday, 3/24

Added lines 6-10:

Tuesday, 3/24
Lecture: Closest pair of points [ slides ]
Reading: Sections 5.5 in Kleinberg and Tardos.

Changed line 4 from:

Lecture: Divide and conquer algorithms and Counting Inversions [ slides ]

to:

Lecture: Recurrence relations, counting inversions [ slides ]

Added lines 1-10:

Week 10:

Tuesday, 3/22
Lecture: Divide and conquer algorithms and Counting Inversions [ slides ]
Reading: Sections 5.2, 5.3 in Kleinberg and Tardos.

Week 9:

Spring break!

Added lines 1-9:

Week 8:

Tuesday, 3/8
Lecture: Exam prep, Divide and conquer algorithms [ slides ]
Reading: Sections 5.1,5.2 in Kleinberg and Tardos.
Thursday, 3/10
Lecture: Midterm exam.

Added lines 7-8:

Thursday, 3/3
Lecture: More on the minimum spanning tree problem.

Added lines 1-7:

Week 7:

Tuesday, 3/1
Lecture: Greedy algorithms for the minimum spanning tree problem [ slides ]
Reading: Sections 4.5,4.7 in Kleinberg and Tardos.

Added lines 1-11:

Week 6:

Tuesday, 2/22
Lecture: Greedy scheduling algorithms
Reading: Sections 4.1,4.2 in Kleinberg and Tardos.
Thursday, 2/24
Lecture: Shortest paths and Dijkstra's algorithm [ slides ]
Reading: Sections 4.4 in Kleinberg and Tardos.

Changed line 6 from:

Written assignment 2 has been posted.

to:

Written assignment 2 has been posted.

Changed line 4 from:

Lecture: Finish graph algorithms - DAGs and topological ordering. Greedy algorithms - interval scheduling [ slides ]

to:

Lecture: Finish graph algorithms - DAGs and topological ordering. Greedy algorithms [ slides ]

Added lines 8-10:

Thursday, 2/17
Lecture: Greedy algorithms - interval scheduling
Reading: Sections 4.1,4.2 in Kleinberg and Tardos.

Changed line 4 from:

Lecture: DAGs and topological ordering. Greedy algorithms - interval scheduling [ slides ]

to:

Lecture: Finish graph algorithms - DAGs and topological ordering. Greedy algorithms - interval scheduling [ slides ]

Changed line 4 from:

Lecture: DAGs and topological ordering. Greedy algorithms - interval scheduling slides ]

to:

Lecture: DAGs and topological ordering. Greedy algorithms - interval scheduling [ slides ]

Added lines 1-8:

Week 5:

Tuesday, 2/15
Lecture: DAGs and topological ordering. Greedy algorithms - interval scheduling slides ]
Reading: Sections 4.1,4.2 in Kleinberg and Tardos.
Written assignment 2 has been posted.

Changed line 16 from:

Lecture: Graph algorithms. Connectivity in directed graphs, DAGs and topological ordering.

to:

Lecture: Graph algorithms. Connectivity in directed graphs

Added lines 5-8:

Reading: Chapter 3 in Kleinberg and Tardos.
Thursday, 2/10
Lecture: Graph algorithms. Connectivity in directed graphs, DAGs and topological ordering.

Changed line 11 from:

Lecture: We will continue the discussion of big-O

to:

Lecture: Continued discussion of big-O

Changed line 15 from:

Lecture: Graphs. We started the discussion of BFS [ slides ]

to:

Lecture: Graphs. Graph traversal with BFS [ slides ]

Added lines 1-7:

Week 4:

Tuesday, 2/8
Lecture: Graph algorithms. Analysis of BFS and DFS. Bipartite graphs.
Reading: Chapter 3 in Kleinberg and Tardos.

Changed line 15 from:

Lecture: Graph algorithms [ slides ]

to:

Lecture: Graphs. We started the discussion of BFS [ slides ]

Added lines 6-11:

Thursday, 2/3
Lecture: Graph algorithms [ slides ]
Reading: Chapter 3 in Kleinberg and Tardos.

Added lines 1-5:

Week 3:

Tuesday, 2/1
Lecture: We will continue the discussion of big-O
Reading: Chapter 2 in Kleinberg and Tardos.

Added lines 1-12:

Week 2:

Tuesday, 1/25
Lecture: Representative problems
Reading: Section 1.2 in Kleinberg and Tardos.
Thursday, 1/27
Lecture: Measuring algorithm efficiency [ slides ]
Reading: Chapter 2 in Kleinberg and Tardos.

Changed line 8 from:

Lecture: We will continue with the stable marriage problem.

to:

Lecture: We will continue with the stable marriage problem. Here is the set python class that I showed.

Changed line 4 from:

Lecture: Course introduction [ slides ]

to:

Lecture: Course introduction - the stable marriage problem [ slides ]

Added lines 6-8:

Thursday, 1/20
Lecture: We will continue with the stable marriage problem.

Deleted lines 5-6:
Added line 7:
Deleted line 0:
Changed lines 3-10 from:

Wednesday, 1/20
Lecture: Course introduction; why programming? [ slides ]
Reading: Chapter 1 in How to think like a computer scientist.

Friday, 1/22
Lecture: Our first program?, programming errors?, Python types?, variables?
Reading: Chapter 2.

to:

Tuesday, 1/18
Lecture: Course introduction [ slides ]
Reading: Chapter 1 in Kleinberg and Tardos.

Changed lines 1-212 from:

Week 15:

Monday, 4/26

Lecture: Plotting with matplotlib. Here's code for a simple plot?.
Reading: The matplotlib tutorial.
Lab: lab 14?

Wednesday, 4/28

Lecture: Plotting: Generating subplots?, histograms?, legends?.

Friday, 4/30

Lecture: Review for exam.

Week 14:

Monday, 4/26

Lecture: Using biopython for DNA sequence motifs motifs?. Example data: the E2F1 motif and human promoter sequences.
Lab: lab 13?

Wednesday, 4/28

Lecture: More about motif finding.

Friday, 4/30

Lecture: Finish motif finding with biopython.

Week 13:

Monday, 4/19
Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation. Also see the biopython install instructions.
Lab: lab 12?

Wednesday, 4/21
Lecture: We will start playing with biopython sequence objects?.
Reading: Chapter 3 in the biopython tutorial.

Friday, 4/23
Lecture: We will use biopython to parse? sequence files.
Here's the data for these examples: Calmodulin sequences in fasta, uniprot, and genbank formats.
Reading: Chapter 2 in the biopython tutorial.

Week 12:

Monday, 4/12
Lecture: Inheritance in python the shapes example?.
Lab: lab 11?
Assignment: Assignment 11?

Wednesday, 4/14
Lecture: interfaces? in Python. New style classes example?. See also the python documentation.

Friday, 4/16
Lecture: Methods for solving assignment 9?.

Week 11:

Monday, 4/5
Lecture: Python classes - representing shapes?; digression: random numbers?
Lab: lab 10?
Assignment: Assignment 10?

Wednesday, 4/7
Lecture: Operator overloading example?; the cards? example.
Reading: Chapter 15.

Friday, 4/9
Lecture: Python classes (cont)

Week 10:

Monday, 3/29
Lecture: Using Python object - continued.
Lab: lab 9?
Assignments: Assignment 9?

Wednesday, 3/31
Lecture: Introduction to Python classes. code examples?.
Reading: chapter 13 and chapter 15

Friday, 4/2
Lecture: No lecture today due to future visions.

Week 9:

Monday, 3/22
Lecture: dictionaries. code examples?.
Lab: lab 8?
Assignments: Assignment 8?
Reading: chapter 12

Wednesday, 3/24
Lecture: tuples (examples?); functions revisited: variable length argument lists using tuples? and dictionaries?.

Friday, 3/26
Lecture: Using python objects - object methods of strings, lists, and dictionaries?.

Week 8:

Monday, 3/8
Lecture: recursion [ slides ]. code examples?.
Lab: lab 7?
Assignments: Assignment 7?
Reading: chapter 11

Wednesday, 3/10
Lecture: recursion - continued. More examples: factorial?, recursive binary search?.

Friday, 3/12
Lecture: midterm

Week 7:

Monday, 3/1
Lecture: binary search code?; measuring the efficiency of algorithms [ slides ]
Lab: lab 6?
Assignments: Assignment 6?

Wednesday, 3/3
Lecture: algorithm efficiency (cont).

Friday, 3/5
Lecture: Exceptions code?; command line arguments example?.
Reading: Exceptions section in chapter 11.

Week 6:

Monday, 2/22
Lecture: Strings and lists (code?), iterators (code?), files (code?).
Lab: lab 5?
Assignments: Assignment 5?

Wednesday, 2/24
Lecture: Sorting algorithms [ slides ]; here's the code?.

Friday, 2/26
Lecture: Sorting algorithms, continued;

Week 5:

Monday, 2/15
Lecture: Strings (continued), string formatting (examples?).
Lab: lab 4?
Assignments: Assignment 4

Wednesday, 2/17
Lecture: Lists (lists?)
Reading: Chapter 9.

Friday, 2/19
Lecture: Lists are mutable (code?), lists as function parameters (code?), nested lists (code?).

Week 4:

Monday, 2/8
Lecture: While loops (cont): printing tables?. Iteration using for loops?.
Lab: Lab 3?
Assignments: Assignment 3

Wednesday, 2/10
Lecture: For loops (cont): nested loops?. Strings (examples?).
Reading: Chapter 7.

Friday, 2/12
Lecture: Strings (continued).

Week 3:

Monday, 2/1
Lecture: Conditionals - the if statement boolean variables?, conditionals?, sort names?, letter grade? calculator, a better version of letter grade?.
Reading: Chapter 4.
Lab: Lab 2?
Assignments: Assignment 2

Wednesday, 2/3
Lecture: Functions that return a value. Examples: area?, divisibility?, absolute value?.
Iteration - the while statement. Here's an example?.
Reading: Chapter 5, chapter 6

Friday, 2/5
Lecture: While loops: input validation?.

Week 2:

Monday, 1/25
Lecture: Python expressions?, and input?. Putting it together: Celsius to fahreheit converter?
Lab: lab1?
Assignments: Assignment1

Wednesday, 1/27
Lecture: Functions [ slides ]. draw_rectangle?, celsius2fahrenheit?, functions?. Reading: Chapter 3.

Friday, 1/29
Lecture: Functions - continued local variables?, conditionals - the if statement boolean variables?.
Reading: Chapter 4.

to:
Deleted lines 11-12:

Changed line 5 from:

Lecture: Plotting with matplotlib. Here's code for a simple plot?. Generating subplots?.

to:

Lecture: Plotting with matplotlib. Here's code for a simple plot?.

Added lines 8-15:

Wednesday, 4/28

Lecture: Plotting: Generating subplots?, histograms?, legends?.

Friday, 4/30

Lecture: Review for exam.

Changed line 6 from:

Reading: The matplotlib tutorial.

to:

Reading: The matplotlib tutorial.

Added line 7:

Lab: lab 14?

Changed lines 5-7 from:

Lecture: Plotting with matplotlib. Here's code for a simple plot?. Generating subplots?.

to:

Lecture: Plotting with matplotlib. Here's code for a simple plot?. Generating subplots?.
Reading: The matplotlib tutorial.

May 03, 2010, at 07:37 AM MST by 71.196.160.210 -
Changed lines 1-2 from:

Week 14:

to:

Week 15:

Added lines 5-10:

Lecture: Plotting with matplotlib. Here's code for a simple plot?. Generating subplots?.

Week 14:

Monday, 4/26

Changed line 20 from:

Lecture: Finish motif finding with biopython. Start plotting with matplotlib. Here's code for a simple plot?.

to:

Lecture: Finish motif finding with biopython.

April 29, 2010, at 09:21 PM MST by 71.196.160.210 -
Added lines 7-14:

Wednesday, 4/28

Lecture: More about motif finding.

Friday, 4/30

Lecture: Finish motif finding with biopython. Start plotting with matplotlib. Here's code for a simple plot?.

Changed lines 6-7 from:
to:

Lab: lab 13?

Changed line 12 from:

Lab: lab 12?

to:

Lab: lab 12?

Changed line 1 from:

Week 13:

to:

Week 14:

Added lines 3-8:

Monday, 4/26

Lecture: Using biopython for DNA sequence motifs motifs?. Example data: the E2F1 motif and human promoter sequences.

Week 13:

Changed lines 18-19 from:

Lecture: We will use biopython to parse? sequence files, and to hanld motifs?.
Here's the data for these examples: Calmodulin sequences in fasta, uniprot, and genbank formats. The E2F1 motif and human promoter sequences.

to:

Lecture: We will use biopython to parse? sequence files.
Here's the data for these examples: Calmodulin sequences in fasta, uniprot, and genbank formats.

Changed line 13 from:

Here's the data for these examples: Calmodulin sequences in fasta, uniprot, and genbank formats. The E2F1 motif and human promoter sequences.

to:

Here's the data for these examples: Calmodulin sequences in fasta, uniprot, and genbank formats. The E2F1 motif and human promoter sequences.

Added line 13:

Here's the data for these examples: Calmodulin sequences in fasta, uniprot, and genbank formats. The E2F1 motif and human promoter sequences.

Added lines 10-13:

Friday, 4/23
Lecture: We will use biopython to parse? sequence files, and to hanld motifs?.
Reading: Chapter 2 in the biopython tutorial.

Deleted line 4:

Reading: Chapter 3 in the biopython tutorial.

Added line 9:

Reading: Chapter 3 in the biopython tutorial.

Changed line 4 from:

Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation. Also see the biopython install instructions. We will start playing with biopython sequence objects?.

to:

Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation. Also see the biopython install instructions.

Added lines 7-9:

Wednesday, 4/21
Lecture: We will start playing with biopython sequence objects?.

Added lines 1-7:

Week 13:

Monday, 4/19
Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation. Also see the biopython install instructions. We will start playing with biopython sequence objects?.
Reading: Chapter 3 in the biopython tutorial.
Lab: lab 12?

Deleted lines 20-23:

Monday, 4/19
Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation. Also see the biopython install instructions. We will start playing with biopython sequence objects?.
Reading: Chapter 3 in the biopython tutorial.

Added lines 13-15:

Lecture: Methods for solving assignment 9?.

Monday, 4/19

Changed line 13 from:

Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation. Also see the biopython install instructions. We will start playing with biopython sequence objects?.//

to:

Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation. Also see the biopython install instructions. We will start playing with biopython sequence objects?.

Changed lines 13-14 from:

Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation. Also see the biopython install instructions. We will start playing with biopython sequence objects?.

to:

Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation. Also see the biopython install instructions. We will start playing with biopython sequence objects?.// Reading: Chapter 3 in the biopython tutorial.

Changed line 13 from:

Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation. Also see the biopython install instructions.

to:

Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation. Also see the biopython install instructions. We will start playing with biopython sequence objects?.

Changed line 13 from:

Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation.

to:

Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation. Also see the biopython install instructions.

Changed line 13 from:

Lecture: Installing packages?. As an example, we will install the biopython package.

to:

Lecture: Installing packages?. As an example, we will install the biopython package. More info at the python documentation.

Added lines 12-13:

Friday, 4/16
Lecture: Installing packages?. As an example, we will install the biopython package.

Changed line 9 from:

Lecture: New style classes example?. See also the

to:

Lecture: interfaces? in Python. New style classes example?. See also the

Changed lines 4-5 from:

Lecture: Inheritance in python the shapes example?. New style classes example?. See also the python documentation.

to:

Lecture: Inheritance in python the shapes example?.

Added lines 7-11:

Wednesday, 4/14
Lecture: New style classes example?. See also the python documentation.

April 10, 2010, at 09:19 AM MST by 71.196.160.210 -
Changed line 17 from:

Lecture: Operator overloading example?; another example?.

to:

Lecture: Operator overloading example?; the cards? example.

April 10, 2010, at 09:18 AM MST by 71.196.160.210 -
Changed line 4 from:

Lecture: Inheritance in python example?. New style classes example?. See also the

to:

Lecture: Inheritance in python the shapes example?. New style classes example?. See also the

Changed line 12 from:

Lecture: Python classes - more examples?; digression: random numbers?

to:

Lecture: Python classes - representing shapes?; digression: random numbers?

April 10, 2010, at 09:15 AM MST by 71.196.160.210 -
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Monday, 4/12

to:

Monday, 4/12

April 10, 2010, at 09:15 AM MST by 71.196.160.210 -
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python documentation.

to:

python documentation.

April 10, 2010, at 09:15 AM MST by 71.196.160.210 -
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Week 12:

Monday, 4/12 Lecture: Inheritance in python example?. New style classes example?. See also the python documentation. Lab: lab 11?
Assignment: Assignment 11?

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Assignments: Assignment 10?

to:

Assignment: Assignment 10?

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Lecture: New style classes example?. See also the python documentation. Inheritance example?.

to:

Lecture: Python classes (cont)

April 08, 2010, at 09:39 PM MST by 71.196.160.210 -
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Reading:: Chapter 15.

to:

Reading: Chapter 15.

Friday, 4/9
Lecture: New style classes example?. See also the python documentation. Inheritance example?.

April 07, 2010, at 06:26 PM MST by 71.196.160.210 -
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Lecture: No lecture today due to .

to:

Lecture: No lecture today due to future visions.

April 07, 2010, at 06:25 PM MST by 71.196.160.210 -
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Friday, 4/2
Lecture: No lecture today due to .

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Wednesday, 4/7
Lecture: Operator overloading example?; another example?.
Reading:: Chapter 15.

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Lecture: Python classes - more examples?.

to:

Lecture: Python classes - more examples?; digression: random numbers?

April 04, 2010, at 10:27 PM MST by 71.196.160.210 -
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Week 11:

Monday, 4/5
Lecture: Python classes - more examples?.
Lab: lab 10?
Assignments: Assignment 10?

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Wednesday, 3/24

to:

Wednesday, 3/31

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Assignments: Assignment 9?

to:

Assignments: Assignment 9?

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Lecture: Introduction to Python classes. code examples?.

to:

Lecture: Using Python object - continued.

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Wednesday, 3/24
Lecture: Introduction to Python classes. code examples?.

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March 28, 2010, at 09:55 PM MST by 71.196.160.210 -
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Week 10:

Monday, 3/29
Lecture: Introduction to Python classes. code examples?.
Lab: lab 9?
Assignments: Assignment 9?
Reading: chapter 13 and chapter 15

March 25, 2010, at 08:20 AM MST by 71.196.160.210 -
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Lecture: tuples (examples?); functions revisited: beyond fixed size argument lists. Using tuples? and dictionaries?.

to:

Lecture: tuples (examples?); functions revisited: variable length argument lists using tuples? and dictionaries?.

Friday, 3/26
Lecture: Using python objects - object methods of strings, lists, and dictionaries?.

March 23, 2010, at 11:11 PM MST by 71.196.160.210 -
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Wednesday, 3/24
Lecture: tuples (examples?); functions revisited: beyond fixed size argument lists. Using tuples? and dictionaries?.

March 21, 2010, at 09:39 PM MST by 71.196.160.210 -
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Week 9:

Monday, 3/22
Lecture: dictionaries. code examples?.
Lab: lab 8?
Assignments: Assignment 8?
Reading: chapter 12

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Friday, 3/12
Lecture: midterm

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Wednesday, 3/10
Lecture: recursion - continued. More examples: factorial?, recursive binary search?.

March 07, 2010, at 06:42 PM MST by 71.196.160.210 -
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Assignments: Assignment 7?

to:

Assignments: Assignment 7?
Reading: chapter 11

March 07, 2010, at 06:37 PM MST by 71.196.160.210 -
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Week 8:

Monday, 3/8
Lecture: recursion [ slides ]. code examples?.
Lab: lab 7?
Assignments: Assignment 7?

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Lecture: Exceptions code?.

to:

Lecture: Exceptions code?; command line arguments example?.

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Lecture: algorithm efficiency (cont).

to:

Lecture: algorithm efficiency (cont).

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Lecture: algorithm efficiency (cont); Exceptions code?.

to:

Lecture: algorithm efficiency (cont).
Friday, 3/5
Lecture: Exceptions code?.

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Lecture: algorithm efficiency (cont); Exceptions code?.

to:

Lecture: algorithm efficiency (cont); Exceptions code?.

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Wednesday, 3/3
Lecture: algorithm efficiency (cont); Exceptions code?. Reading: Exceptions section in chapter 11.

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Lecture: binary search code?; measuring the efficiency of algorithms [ [[Path:../../pdfs/04_complexity.pdf

to:

Lecture: binary search code?; measuring the efficiency of algorithms [ slides ]

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Week 7:

Monday, 3/1
Lecture: binary search code?; measuring the efficiency of algorithms [ lab 6
Assignments: Assignment 6?

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Lecture: Sorting algorithms, continued; binary search code?.

to:

Lecture: Sorting algorithms, continued;

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Lecture: Sorting algorithms [ slides ]; here's the code?.

to:

Lecture: Sorting algorithms [ slides ]; here's the code?.

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Lecture: Sorting algorithms, continued; binary search code?.

to:

Lecture: Sorting algorithms, continued; binary search code?.

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Lecture: Sorting algorithms [ slides ]

to:

Lecture: Sorting algorithms [ slides ]; here's the code?.
Friday, 2/26
Lecture: Sorting algorithms, continued; binary search code?.

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Lecture: Sorting algorithms ([ slides ])

to:

Lecture: Sorting algorithms [ slides ]

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Wednesday, 2/24
Lecture: Sorting algorithms ([ slides ])

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Lecture: Strings (continued), string formatting (examples?).

to:

Lecture: Strings and lists (code?), iterators (code?), files (code?).

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Week 6:

to:

Week 5:

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Lecture: Strings and lists (code?), iterators (code?), files (code?).

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Lecture: Strings (continued), string formatting (examples?).

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Week 5:

Monday, 2/15

to:

Week 6:

Monday, 2/22

Added lines 5-13:

Lab: lab 5?
Assignments: Assignment 5?

Week 6:

Monday, 2/15
Lecture: Strings and lists (code?), iterators (code?), files (code?).

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Lecture: Lists are mutable (code?), lists as function parameters (code?), nested lists (code?), strings and lists (code?).

to:

Lecture: Lists are mutable (code?), lists as function parameters (code?), nested lists (code?).

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Lecture: Lists are mutable (code?), lists as function parameters (code?), nested lists code?, strings and lists ( code? ).

to:

Lecture: Lists are mutable (code?), lists as function parameters (code?), nested lists (code?), strings and lists (code?).

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Lecture: Lists are mutable code?, lists as function parameters code?, nested lists code?, strings and lists code?.

to:

Lecture: Lists are mutable (code?), lists as function parameters (code?), nested lists code?, strings and lists ( code? ).

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Lecture: Lists are mutable code?, lists as function parameters code?, nested lists code?.

to:

Lecture: Lists are mutable code?, lists as function parameters code?, nested lists code?, strings and lists code?.

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Reading: Chapter 9.

to:

Reading: Chapter 9.

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Friday, 2/19
Lecture: Lists are mutable code?, lists as function parameters code?, nested lists code?.

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Lecture: Lists (examples?)

to:

Lecture: Lists (lists?)

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Lecture: Lists (lists?)

to:

Lecture: Lists (examples?)

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Lecture: String formatting (examples?). Lists (lists?)
Reading: Chapter 9.

to:

Lecture: Strings (continued), string formatting (examples?).

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Wednesday, 2/17
Lecture: Lists (lists?)
Reading: Chapter 9.

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Assignments: Assignment 3

to:

Assignments: Assignment 4

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Week 5:

Monday, 2/15
Lecture: String formatting (examples?). Lists (lists?)
Reading: Chapter 9.
Lab: lab 4?
Assignments: Assignment 3

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Lecture: String formatting (examples?). Lists (lists?)
Reading: Chapter 9.

to:

Lecture: Strings (continued).

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Reading: Chapter 7.

to:

Reading: Chapter 7.

Added lines 11-15:

Friday, 2/12
Lecture: String formatting (examples?). Lists (lists?)
Reading: Chapter 9.

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Lecture: For loops (cont): nested loops?. Strings (examples?.

to:

Lecture: For loops (cont): nested loops?. Strings (examples?).

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Lecture: For loops (cont): nested loops?.

to:

Lecture: For loops (cont): nested loops?. Strings (examples?.
Reading: Chapter 7.

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Lecture: While loops (cont): printing tables?, nested loops?. Iteration using for loops?.

to:

Lecture: While loops (cont): printing tables?. Iteration using for loops?.

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Wednesday, 2/10
Lecture: For loops (cont): nested loops?.

Changed lines 4-5 from:

Lecture: While loops (cont): printing tables?, nested loops?. Iteration using for loops?
.

to:

Lecture: While loops (cont): printing tables?, nested loops?. Iteration using for loops?.
Lab: Lab 3?
Assignments: Assignment 3

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Lecture: While loops: input validation?
.

to:

Lecture: While loops: input validation?.

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'Lecture:'' While loops (cont): printing tables?, nested loops?. Iteration using for loops?
.

to:

Lecture: While loops (cont): printing tables?, nested loops?. Iteration using for loops?
.

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Week 4:

Monday, 2/8
'Lecture:'' While loops (cont): printing tables?, nested loops?. Iteration using for loops?
.

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Lecture: While loops: input validation?, printing tables?, nested loops?. Iteration using for loops?
.

to:

Lecture: While loops: input validation?
.

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Added lines 15-16:

Friday, 2/5
Lecture: While loops: input validation?, printing tables?, nested loops?. Iteration using for loops?
.

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Iteration - the while statement. Here's an example?.

to:

Iteration - the while statement. Here's an example?.

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Lecture: Functions that return a value. Examples: area?, divisibility?, absolute value?. Reading: Chapter 5.

to:

Lecture: Functions that return a value. Examples: area?, divisibility?, absolute value?.
Iteration - the while statement. Here's an example?. Reading: Chapter 5, chapter 6

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Monday, 2/3

to:

Wednesday, 2/3

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Reading: Chapter 5.

to:

Reading: Chapter 5.

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Monday, 2/3
Lecture: Functions that return a value. Examples: area?, divisibility?, absolute value?. Reading: Chapter 5.

Added lines 6-8:

Lab: Lab 2?
Assignments: Assignment 2

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Week 3:

Monday, 2/1
Lecture: Conditionals - the if statement boolean variables?, conditionals?, sort names?, letter grade? calculator, a better version of letter grade?.
Reading: Chapter 4.

Changed line 20 from:

Lecture: Functions - continued local variables?, conditionals - the if statement boolean variables?, conditionals?, sort names?, letter grade? calculator, a better version of letter grade?.

to:

Lecture: Functions - continued local variables?, conditionals - the if statement boolean variables?.

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Lecture: Functions - continued local variables?, conditionals - the if statement boolean variables?, conditionals?, sort names?, letter grade? calculator, a better version of letter grade?.

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Lecture: Functions - continued local variables?, conditionals - the if statement boolean variables?, conditionals?, sort names?, letter grade? calculator, a better version of letter grade?.

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to:

Reading: Chapter 4.

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to:

Friday, 1/29
Lecture: Functions - continued local variables?, conditionals - the if statement boolean variables?, conditionals?, sort names?, letter grade? calculator, a better version of letter grade?.

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to:
Added lines 8-12:

Wednesday, 1/27
Lecture: Functions [ slides ]. draw_rectangle?, celsius2fahrenheit?, functions?. Reading: Chapter 3.

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Wed, 1/20

to:

Wednesday, 1/20

Changed line 18 from:

Fri, 1/22

to:

Friday, 1/22

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Week 1:

to:

Week 1:

Added lines 1-7:

Week 2:

Monday, 1/25
Lecture: Python expressions?, and input?. Putting it together: Celsius to fahreheit converter?
Lab: lab1?
Assignments: Assignment1

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Week 2:

Lecture: Python expressions?, and input?.
Lab: lab1?
Assignments: Assignment1

to:

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Lab: lab1?

to:

Lab: lab1?
Assignments: Assignment1

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Lecture: Python expressions?, and input?.

to:

Lecture: Python expressions?, and input?.
Lab: lab1?

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Lecture: Pythonexpressions?, and input?.

to:

Lecture: Python expressions?, and input?.

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to:
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Week 2:

Lecture: Pythonexpressions?, and input?.

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to:
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Lectures: Course introduction; why programming? [ slides ]

to:

Lecture: Course introduction; why programming? [ slides ]

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to:

Fri, 1/22
Lecture: Our FirstProgram?, programming errors?, Python types?, variables?, expressions?, and input?.
Reading: Chapter 2.

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Week 1:

Wed, 1/20

to:

Week 1:

Wed, 1/20

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Week 1: 1/20

to:

Week 1:

Wed, 1/20

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Assignments: Coming soon

to:
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Lectures: Course introduction; why programming?

to:

Lectures: Course introduction; why programming? [ slides ]

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Lectures: Course introduction;
Reading:

to:

Lectures: Course introduction; why programming?
Reading: Chapter 1 in How to think like a computer scientist.

Changed lines 1-92 from:

Week 1: 8/25

Lectures: Course introduction; cs160 recap [ slides ] (updated)
Reading: 160 material: chapters 1-4, 7 in the Java book.
Recitation: cs160 recap?
Assignments: First programming assignment is available

Week 2: 9/1

Lectures: Java classes, objects, and object oriented programming [ slides ]. Here's the code for the Die? class. Quiz on Thu.
Reading: Chapter 5 in the Java book.
Recitation: Getting familiar with Classes?
Assignments: Programming assignment is available

Week 3: 9/8

Lectures: More on Java classes [ slides ] (updated thu). The code for the Account? class. Quiz on Thu.
Reading: Chapters 5-6 in Savitch (5 in Lewis).
Recitation: More on Classes?

Week 4: 9/15

Lectures: Assertions, pre/post conditions [ slides ]. Javadoc commenting of code. Here's an example?. ArrayList [ slides ]. Here's the example? we worked on in class . Quiz on Thu.
Reading: Assertions - chapter 4.2 in Savitch. ArrayList - chapter 12.1 in Savitch;
Recitation: A Break from Classes?

Week 5: 9/22

Lectures: Recursion [ slides ]. Quiz on Thu. More recursion [ slides ]. The maze? example.
Reading: Chapter 11 in Savitch, or Chapter 12 in Lewis, or Chapter 3 in Walls and Mirrors.
Recitation: Recursion?

Week 6: 9/29

Lectures: Counting [ slides ]. Midterm on Thu.
Reading: Chapter 5 in Rosen.
Recitation: Recursion?

Week 7: 10/6

Lectures: Permutations, r-permutation, combinations, and the traveling salesman problem [ slides ] (updated on thursday). Quiz on Thu.
Reading: Chapter 5 in Rosen.
Recitation: Enumeration and Counting?

Week 8: 10/13

Lectures: Induction [ slides ]. Quiz on Thu.
Reading: Chapter 4.1,4.2 in Rosen.
Assignments: A written assignment on induction is available

Week 9: 10/20

Lectures: Inheritance [ slides ]. Inheritance and polymorphism [ slides ] Quiz on Thu.
Reading: Chapter 8 in either of the Java books.
Recitation: Inheritance?

Week 10: 10/27

Lectures: Interfaces [ slides ]. (updated after thursday's class) [ Code ] for the StaffMember/Employee etc. example. Quiz on Thu.
Reading: Chapter 8 in Savitch, chapter 9 in Lewis.
Recitation: Interfaces?

Week 11: 11/3

Lectures: Midterm on Tue. Static again [ slides ]. Linked lists [ slides ]
Reading: Chapter 5 in Walls and Mirrors, 12.1 in Savitch, 14.4 in Lewis.
Recitation: Programming quiz

Week 12: 11/10

Lectures: Linked lists [ slides ] (updated on wed). Linked list code? and doubly linked list code?.
Reading: Chapter 5 in Walls and Mirrors, 12.1 in Savitch, 14.4 in Lewis.
Recitation: Linked Lists?

Week 13: 11/17

Lectures: Sorting [ slides ] (updated on thu) Here's a nice java applet that illustrates the sorting algorithms we looked at. Obama being asked about sorting
Reading: Chapter 13 in Lewis, Chapter 10 in Walls and Mirrors
Recitation: Sorting?

Week 14: 12/1

Lectures: Java packages [ slides ]. JUnit and testing [ slides ]. Graphics, GUI and Applets in Java [ slides ] and [ code ]
Reading: Packages: Chapter 11 in Lewis, 6.7 in Savitch. Lewis covers version 3 of JUnit.
Recitation: JUnit?

Week 15: 12/8

Lectures: Java Graphics, GUI and Applets - continued (tuesday). Review (thursday).
Recitation: Programming final.

to:

Week 1: 1/20

Lectures: Course introduction;
Reading:
Assignments: Coming soon

Added lines 89-92:

Week 15: 12/8

Lectures: Java Graphics, GUI and Applets - continued (tuesday). Review (thursday).
Recitation: Programming final.

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Lectures: Java packages [ slides ]. JUnit and testing [ slides ]. Graphics, GUI and Applets in Java [ slides ]

to:

Lectures: Java packages [ slides ]. JUnit and testing [ slides ]. Graphics, GUI and Applets in Java [ slides ] and [ code ]

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Lectures: Java packages [ slides ]. JUnit and testing [ slides ]

to:

Lectures: Java packages [ slides ]. JUnit and testing [ slides ]. Graphics, GUI and Applets in Java [ slides ]

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Recitation:

to:

Recitation: JUnit?

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Lectures: Java packages [ slides ]. JUnit and testing [ slides ]

to:

Lectures: Java packages [ slides ]. JUnit and testing [ slides ]

Changed lines 81-88 from:

Recitation: Sorting?

to:

Recitation: Sorting?

Week 14: 12/1

Lectures: Java packages [ slides ]. JUnit and testing [ slides ]
Reading: Packages: Chapter 11 in Lewis, 6.7 in Savitch. Lewis covers version 3 of JUnit.
Recitation:

Changed line 79 from:

Lectures: Sorting [ slides ] (updated on thu) Here's a nice java applet that illustrates the sorting algorithms we looked at

to:

Lectures: Sorting [ slides ] (updated on thu) Here's a nice java applet that illustrates the sorting algorithms we looked at. Obama being asked about sorting

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Lectures: Sorting [ slides ] (updated on thu)

to:

Lectures: Sorting [ slides ] (updated on thu) Here's a nice java applet that illustrates the sorting algorithms we looked at

Changed line 79 from:

Lectures: Sorting [ slides ]

to:

Lectures: Sorting [ slides ] (updated on thu)

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Recitation: Sorting?

to:

Recitation: Sorting?

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Recitation:

to:

Recitation: Sorting?

Added lines 76-81:

Week 13: 11/17

Lectures: Sorting [ slides ]
Reading: Chapter 13 in Lewis, Chapter 10 in Walls and Mirrors
Recitation:

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Lectures: Linked lists [ slides ] (updated on wed). Linked list code?

to:

Lectures: Linked lists [ slides ] (updated on wed). Linked list code? and doubly linked list code?.

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Lectures: Linked lists [ slides ] (updated on wed)

to:

Lectures: Linked lists [ slides ] (updated on wed). Linked list code?

Changed line 73 from:

Lectures: Linked lists [ slides ]

to:

Lectures: Linked lists [ slides ] (updated on wed)

Changed line 75 from:
to:

Recitation: Linked Lists?

Added lines 70-75:

Week 12: 11/10

Lectures: Linked lists [ slides ]
Reading: Chapter 5 in Walls and Mirrors, 12.1 in Savitch, 14.4 in Lewis.

Changed lines 63-69 from:

Recitation: Interfaces?

to:

Recitation: Interfaces?

Week 11: 11/3

Lectures: Midterm on Tue. Static again [ slides ]. Linked lists [ slides ]
Reading: Chapter 5 in Walls and Mirrors, 12.1 in Savitch, 14.4 in Lewis.
Recitation: Programming quiz

Changed line 61 from:

Lectures: Interfaces [ slides ]. [ Code ] for the StaffMember/Employee etc. example. Quiz on Thu.

to:

Lectures: Interfaces [ slides ]. (updated after thursday's class) [ Code ] for the StaffMember/Employee etc. example. Quiz on Thu.

Changed line 63 from:
to:

Recitation: Interfaces?

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Lectures: Interfaces [ slides ]. Quiz on Thu.

to:

Lectures: Interfaces [ slides ]. [ Code ] for the StaffMember/Employee etc. example. Quiz on Thu.

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Week 9: 10/27

to:

Week 10: 10/27

Added lines 58-63:

Week 9: 10/27

Lectures: Interfaces [ slides ]. Quiz on Thu.
Reading: Chapter 8 in Savitch, chapter 9 in Lewis.

Changed line 55 from:

Lectures: Inheritance [ slides ]. Quiz on Thu.

to:

Lectures: Inheritance [ slides ]. Inheritance and polymorphism [ slides ] Quiz on Thu.

Changed line 57 from:
to:

Recitation: Inheritance?

Added lines 52-57:

Week 9: 10/20

Lectures: Inheritance [ slides ]. Quiz on Thu.
Reading: Chapter 8 in either of the Java books.

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Assignments: A written assignment on induction is available

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Reading: Chapter 11 in Savitch, or Chapter 12 in Lewis, or Chapter 3 in Walls and Mirrors.

to:

Reading: Chapter 11 in Savitch, or Chapter 12 in Lewis, or Chapter 3 in Walls and Mirrors.

Changed line 38 from:

Reading: Chapter 5 in Rosen.

to:

Reading: Chapter 5 in Rosen.

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Reading: Chapter 5 in Rosen.

to:

Reading: Chapter 5 in Rosen.

Added lines 47-50:

Week 8: 10/13

Lectures: Induction [ slides ]. Quiz on Thu.
Reading: Chapter 4.1,4.2 in Rosen.

Changed line 43 from:

Lectures: Permutations, r-permutation, combinations, and the traveling salesman problem [ slides ]. Quiz on Thu.

to:

Lectures: Permutations, r-permutation, combinations, and the traveling salesman problem [ slides ] (updated on thursday). Quiz on Thu.

Added line 45:
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Lectures: Permutations, r-permutation, combinations, and the traveling salesman problem [ slides ]. Midterm on Thu.

to:

Lectures: Permutations, r-permutation, combinations, and the traveling salesman problem [ slides ]. Quiz on Thu.

Added lines 40-44:

Week 7: 10/6

Lectures: Permutations, r-permutation, combinations, and the traveling salesman problem [ slides ]. Midterm on Thu.
Reading: Chapter 5 in Rosen.

Added line 39:

Recitation: Recursion?

Added lines 34-38:

Week 6: 9/29

Lectures: Counting [ slides ]. Midterm on Thu.
Reading: Chapter 5 in Rosen.

Changed line 31 from:

Lectures: Recursion [ slides ]. Quiz on Thu. More recursion [ slides ]

to:

Lectures: Recursion [ slides ]. Quiz on Thu. More recursion [ slides ]. The maze? example.

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Lectures: Recursion [ slides ]. Quiz on Thu.

to:

Lectures: Recursion [ slides ]. Quiz on Thu. More recursion [ slides ]

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to:

Recitation: Recursion?

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to:

Week 5: 9/22

Lectures: Recursion [ slides ]. Quiz on Thu.
Reading: Chapter 11 in Savitch, or Chapter 12 in Lewis, or Chapter 3 in Walls and Mirrors.

Changed line 25 from:

Lectures: Assertions, pre/post conditions [ slides ]. Javadoc commenting of code. Here's an example?. ArrayList [ slides ]. Quiz on Thu.

to:

Lectures: Assertions, pre/post conditions [ slides ]. Javadoc commenting of code. Here's an example?. ArrayList [ slides ]. Here's the example? we worked on in class . Quiz on Thu.

Changed lines 25-26 from:

Lectures: Assertions, pre/post conditions [ slides ]. Javadoc commenting of code. Here's an example?. Quiz on Thu.
Reading: Assertions - chapter 4.2 in Savitch.

to:

Lectures: Assertions, pre/post conditions [ slides ]. Javadoc commenting of code. Here's an example?. ArrayList [ slides ]. Quiz on Thu.
Reading: Assertions - chapter 4.2 in Savitch. ArrayList - chapter 12.1 in Savitch;

Changed line 27 from:

Recitation:

to:
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Lectures: More on Java classes [ slides ]. Quiz on Thu.

to:

Lectures: Assertions, pre/post conditions [ slides ]. Javadoc commenting of code. Here's an example?. Quiz on Thu.

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Week 4: 9/8

to:

Week 3: 9/8

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Week 3: 9/15

to:

Week 4: 9/15

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Week 3: 9/8

to:

Week 4: 9/8

Added lines 22-30:

Week 3: 9/15

Lectures: More on Java classes [ slides ]. Quiz on Thu.
Reading: Assertions - chapter 4.2 in Savitch.
Recitation:

Changed line 19 from:

Lectures: More on Java classes [ slides ]. The code for the Account? class. Quiz on Thu.

to:

Lectures: More on Java classes [ slides ] (updated thu). The code for the Account? class. Quiz on Thu.

Changed line 21 from:

Recitation:

to:

Recitation: More on Classes?

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Lectures: More on Java classes [ slides ]. Quiz on Thu.

to:

Lectures: More on Java classes [ slides ]. The code for the Account? class. Quiz on Thu.

Changed lines 14-21 from:
to:

Recitation: Getting familiar with Classes?
Assignments: Programming assignment is available

Week 3: 9/8

Lectures: More on Java classes [ slides ]. Quiz on Thu.
Reading: Chapters 5-6 in Savitch (5 in Lewis).
Recitation:

Changed line 12 from:

[ slides ]. Here's the code for the Die? class.

to:

[ slides ]. Here's the code for the Die? class. Quiz on Thu.

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[ slides ]

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[ slides ]. Here's the code for the Die? class.

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[ slides ] (updated)

to:

[ slides ]

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Week 1: 8/25

to:

Week 2: 9/1

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Week 1: 8/25

Lectures: Java classes, objects, and object oriented programming [ slides ] (updated)
Reading: Chapter 5 in the Java book.

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[ slides ]

to:

[ slides ] (updated)

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[ slides ]
>><< Reading: Chapters 1-4, 7 in the Java book.
Recitation:

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[ slides ]
Reading: 160 material: chapters 1-4, 7 in the Java book.
Recitation: cs160 recap?

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Lectures: Course introduction; cs160 recap [ slides ]
Reading: Chapter 1 in Walls and Mirrors.

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Lectures: Course introduction; cs160 recap

[ slides ]
>><< Reading: Chapters 1-4, 7 in the Java book.

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Reading: Chapter 4 in Walls and Mirrors.

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Reading: Chapter 1 in Walls and Mirrors.

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Week 1: 1/21 - 1/23

Lectures: Course introduction; abstract data types (ADTs) [ slides ]

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Week 1: 8/25

Lectures: Course introduction; cs160 recap [ slides ]

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Recitation: No recitations this week

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Recitation:

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Week 2: 1/26 - 1/30

Lectures: Measuring the efficiency of algorithms [ slides ]
Reading: Sections 3.2,3.3 in Rosen, Section 10.1 in Walls and Mirrors.
Recitation: Using checkin, review of linked lists, help on programming assignment

Week 3: 2/2 - 2/6

Lectures: Stacks and Queues [ slides ]
Reading: chapters 7 and 8 in Walls and Mirrors
Recitation: Review of big-O analysis, generics, stacks
Assignments: Second programming assignment is available

Week 4: 2/9 - 2/13

Lectures: Queues (cont). Advanced sorting algorithms using divide and conquer strategies; evaluating complexity of recursive algorithms [ slides ]
Reading: Walls and Mirrors 10.2, Rosen 7.1, 7.3
Recitation: Programming a queue; work on programming assignment

Week 5: 2/16 - 2/20

Lectures: Sorting algorithms using divide and conquer strategies (cont)
Reading: Walls and Mirrors 10.2, Rosen 7.1, 7.3
Recitation: recursion
Assignments: Second written assignment is available

Week 6: 2/23 - 2/27

Lectures: Wednesday: Midterm. Mon, Fri: Trees, binary search trees
[ slides ]
Reading: Walls and Mirrors ch. 11
Recitation: Review for midterm, recursion

Week 7: 3/2 - 3/6

Lectures: Trees, binary search trees (cont)
Reading: Walls and Mirrors ch. 11
Recitation: Iterators, recursion

Week 8: 3/9 - 3/13

Lectures: Priority queues and heaps [ slides ]
Reading: Walls and Mirrors ch. 12.2
Recitation: More iterators

Week 9: 3/23 - 3/27

Lectures: Monday: grammars [ slides ] Wednesday: Working in teams - a talk by Debbie Bartlett. Friday: Balanced search trees [ slides ]
Reading: Walls and Mirrors ch. 6.2, ch. 12,13
Recitation: implementing a heap

Week 10: 3/30 - 4/3

Lectures: Balanced search trees (cont). Friday: graphs [ slides ]
Reading: Walls and Mirrors ch. 13; ch. 14.1-14.2
Recitation: programming quiz. You will use the binary tree and tree node classes.

Week 11: 4/6 - 4/10

Lectures: Monday: graphs (cont). Wednesday: midterm. Friday: more graphs [ slides ]
Reading: Walls and Mirrors ch. 14
Recitation: help with programming assignment, go over written hw, command-line arguments, review for midterm

Week 12: 4/13 - 4/17

Lectures: graphs - directed acyclic graphs and topological sorting of graphs; graph algorithms [ slides ], relations [ slides ]
Reading: Walls and Mirrors ch. 14, Rosen 8.1-8.5 (relations)
Recitation: Implementing graphs.

Week 14: 4/27 - 5/1

Lectures: Dijkstra's algorithm (slides in the graph algorithms set), more problems on graphs [ slides ]
hash tables [ slides ]
Reading: Walls and Mirrors ch. 14 (graphs), 13 (hash tables)
Recitation: Review of relations and grammars.

Week 15: 5/4 - 5/8

Lectures: hash tables (cont); discussion of final [ slides ]
Reading: Walls and Mirrors ch. 13
Recitation: Programming part of final.

Week 16:

Wed -- special review session 1-3pm at CSB130. Thu -- final exam at 7am.

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Week 16:

Wed -- special review session 1-3pm at CSB130. Thu -- final exam at 7am.

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Week 15: 5/4 - 5/8

Lectures: hash tables (cont); discussion of final [ slides ]
Reading: Walls and Mirrors ch. 13
Recitation: Programming part of final.

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hash tables [ slides ]

to:

hash tables [ slides ]

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Reading: Walls and Mirrors ch. 14

to:

hash tables [ slides ] Reading: Walls and Mirrors ch. 14 (graphs), 13 (hash tables)

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Lectures: Dijkstra's algorithm (slides in the graph algorithms set), more problems on graphs [ slides ]

to:

Lectures: Dijkstra's algorithm (slides in the graph algorithms set), more problems on graphs [ slides ]

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Lectures: Dijkstra's algorithm, more problems on graphs [ slides ]

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Lectures: Dijkstra's algorithm (slides in the graph algorithms set), more problems on graphs [ slides ]

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Lectures: Relations, Dijkstra's algorithm, more problems on graphs [ slides ] Reading: Walls and Mirrors ch. 14, Rosen 8.1-8.5 (relations)

to:

Lectures: Dijkstra's algorithm, more problems on graphs [ slides ]
Reading: Walls and Mirrors ch. 14

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Week 13: 4/27 - 5/1

to:

Week 14: 4/27 - 5/1

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Week 13: 4/27 - 5/1

Lectures: Relations, Dijkstra's algorithm, more problems on graphs [ slides ] Reading: Walls and Mirrors ch. 14, Rosen 8.1-8.5 (relations)
Recitation: Review of relations and grammars.

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Lectures: graphs - directed acyclic graphs and topological sorting of graphs; graph algorithms [ slides ]
Reading: Walls and Mirrors ch. 14

to:

Lectures: graphs - directed acyclic graphs and topological sorting of graphs; graph algorithms [ slides ], relations [ slides ]
Reading: Walls and Mirrors ch. 14, Rosen 8.1-8.5 (relations)

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Lectures: graphs - directed acyclic graphs and topological sorting of graphs

to:

Lectures: graphs - directed acyclic graphs and topological sorting of graphs; graph algorithms [ slides ]

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Week 12: 4/13 - 4/17

Lectures: graphs - directed acyclic graphs and topological sorting of graphs
Reading: Walls and Mirrors ch. 14
Recitation: Implementing graphs.

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Lectures: Monday: graphs (cont). Wednesday: midterm. Friday: more graphs

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Lectures: Monday: graphs (cont). Wednesday: midterm. Friday: more graphs [ slides ]

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Reading: Walls and Mirrors ch. 13; beginning ch. 14

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Reading: Walls and Mirrors ch. 13; ch. 14.1-14.2

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Lectures: Balanced search trees (cont). Friday: graphs

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Lectures: Balanced search trees (cont). Friday: graphs [ slides ]

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Lectures: Balanced search trees (cont)
Reading: Walls and Mirrors ch. 13

to:

Lectures: Balanced search trees (cont). Friday: graphs
Reading: Walls and Mirrors ch. 13; beginning ch. 14

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Week 11: 4/6 - 4/10

Lectures: Monday: graphs (cont). Wednesday: midterm. Friday: more graphs
Reading: Walls and Mirrors ch. 14
Recitation: help with programming assignment, go over written hw, command-line arguments, review for midterm

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Reading: Walls and Mirrors ch. 6.2

to:

Reading: Walls and Mirrors ch. 6.2, ch. 12,13

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Week 10: 3/30 - 4/3

Lectures: Balanced search trees (cont)
Reading: Walls and Mirrors ch. 13
Recitation: programming quiz. You will use the binary tree and tree node classes.

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Lectures: Monday: grammars [ slides ] Wednesday: Working in teams - a talk by Debbie Bartlett Friday: Balanced search trees [ slides ]

to:

Lectures: Monday: grammars [ slides ] Wednesday: Working in teams - a talk by Debbie Bartlett. Friday: Balanced search trees [ slides ]

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Lectures: Monday: grammars [ slides ] Wednesday: Working in teams - a talk by Debbie Bartlett

to:

Lectures: Monday: grammars [ slides ] Wednesday: Working in teams - a talk by Debbie Bartlett Friday: Balanced search trees [ slides ]

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Recitation:

to:

Recitation: implementing a heap

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Lectures: Priority queues and heaps [ slides ] grammars [ slides ]
Reading: Walls and Mirrors ch. 12.2, ch. 6.2

to:

Lectures: Priority queues and heaps [ slides ]
Reading: Walls and Mirrors ch. 12.2

Added lines 52-57:

Week 9: 3/23 - 3/27

Lectures: Monday: grammars [ slides ] Wednesday: Working in teams - a talk by Debbie Bartlett
Reading: Walls and Mirrors ch. 6.2
Recitation:

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Lectures: Priority queues and heaps [ slides ]
Reading: Walls and Mirrors ch. 12.2

to:

Lectures: Priority queues and heaps [ slides ] grammars [ slides ]
Reading: Walls and Mirrors ch. 12.2, ch. 6.2

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Lectures: Priority queues and heaps slides ]

to:

Lectures: Priority queues and heaps [ slides ]

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Recitation: recursion

to:

Recitation: recursion

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Week 8: 3/9 - 3/13

Lectures: Priority queues and heaps slides ]
Reading: Walls and Mirrors ch. 12.2
Recitation: More iterators

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 Reading:  Walls and Mirrors ch. 11
to:

Reading: Walls and Mirrors ch. 11

Added lines 41-45:

Week 7: 3/2 - 3/6

Lectures: Trees, binary search trees (cont)

 Reading:  Walls and Mirrors ch. 11
Recitation: Iterators, recursion
Changed line 37 from:

Lectures: Wednesday: Midterm. Mon, Fri: Trees, binary search trees ]

to:

Lectures: Wednesday: Midterm. Mon, Fri: Trees, binary search trees
[ slides ]

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Lectures: Wednesday: Midterm. Mon, Fri: Trees, binary search trees [ slides ]

to:

Lectures: Wednesday: Midterm. Mon, Fri: Trees, binary search trees ]

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Week 5: 2/23 - 2/27

to:

Week 6: 2/23 - 2/27

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Lectures: Wednesday: Midterm. Mon, Fri: Trees, binary search trees slides ]

to:

Lectures: Wednesday: Midterm. Mon, Fri: Trees, binary search trees [ slides ]

Added lines 34-39:

Week 5: 2/23 - 2/27

Lectures: Wednesday: Midterm. Mon, Fri: Trees, binary search trees slides ]
Reading: Walls and Mirrors ch. 11
Recitation: Review for midterm, recursion

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Recitation:

to:

Recitation: recursion Assignments: Second written assignment is available

Added lines 27-32:

Week 5: 2/16 - 2/20

Lectures: Sorting algorithms using divide and conquer strategies (cont)
Reading: Walls and Mirrors 10.2, Rosen 7.1, 7.3
Recitation:

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Lectures: Queues (cont). Advanced sorting algorithms using divide and conquor strategies; evaluating complexity of recursive algorithms [ slides ]

to:

Lectures: Queues (cont). Advanced sorting algorithms using divide and conquer strategies; evaluating complexity of recursive algorithms [ slides ]

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Lectures: Queues (cont). Advanced sorting algorithms using divide and conquor strategies; evaluating complexity of recursive algorithms

to:

Lectures: Queues (cont). Advanced sorting algorithms using divide and conquor strategies; evaluating complexity of recursive algorithms [ slides ]

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Week 4: 2/2 - 2/6

Lecture: [ slides ] Reading: Walls and Mirrors 10.2, Rosen 7.1, 7.3

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Week 4: 2/9 - 2/13

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Recitation: Review of big-O analysis, generics, stacks

to:

Recitation: Programming a queue; work on programming assignment

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Added lines 20-28:

Week 4: 2/2 - 2/6

Lecture: [ slides ] Reading: Walls and Mirrors 10.2, Rosen 7.1, 7.3

Lectures: Queues (cont). Advanced sorting algorithms using divide and conquor strategies; evaluating complexity of recursive algorithms
Reading: Walls and Mirrors 10.2, Rosen 7.1, 7.3
Recitation: Review of big-O analysis, generics, stacks

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Recitation: Review of big-O analysis, generics, stacks

to:

Recitation: Review of big-O analysis, generics, stacks

Added line 20:

Assignments: Second programming assignment is available

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Recitation: Review of big-O analysis, generics

to:

Recitation: Review of big-O analysis, generics, stacks

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Lectures: Course introduction; abstract data types (ADTs) [ slides ]

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Lectures: Course introduction; abstract data types (ADTs) [ slides ]

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Lectures: Measuring the efficiency of algorithms [ slides ]

Deleted line 11:

Lectures: Measuring the efficiency of algorithms [ slides ]

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Week 3: 2/2 - 2/6

Lectures: Stacks and Queues [ slides ]
Reading: chapters 7 and 8 in Walls and Mirrors
Recitation: Review of big-O analysis, generics

Changed line 12 from:

Recitation: Using checkin, review of linked lists, file IO, help on programming assignment

to:

Recitation: Using checkin, review of linked lists, help on programming assignment

Changed line 12 from:

Recitation: Using checkin, review of linked lists and file IO

to:

Recitation: Using checkin, review of linked lists, file IO, help on programming assignment

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Week 1: 1/26 - 1/30

to:

Week 2: 1/26 - 1/30

Changed line 12 from:

Recitation:

to:

Recitation: Using checkin, review of linked lists and file IO

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Reading: Sections 3.2,3.3 in Rose, Section 10.1 in Walls and Mirrors.

to:

Reading: Sections 3.2,3.3 in Rosen, Section 10.1 in Walls and Mirrors.

Added lines 7-13:

Week 1: 1/26 - 1/30

Reading: Sections 3.2,3.3 in Rose, Section 10.1 in Walls and Mirrors.
Lectures: Measuring the efficiency of algorithms [ slides ]
Recitation:

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Lectures: Course introduction; abstract data types (ADTs) slides

to:

Lectures: Course introduction; abstract data types (ADTs) [ slides ]

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Lectures: Course introduction; abstract data types (ADTs)

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Lectures: Course introduction; abstract data types (ADTs) slides

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Reading: Chapter 4 in Walls and Mirrors.

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Reading: Chapter 4 in Walls and Mirrors.

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Recitation: No recitations this week

to:

Recitation: No recitations this week

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Lectures: Course introduction; abstract data types (ADTs)

to:

Lectures: Course introduction; abstract data types (ADTs)

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Reading: Chapter 4 in Walls and Mirrors.
Lectures: Course introduction; abstract data types (ADTs)
Recitation: No recitations this week
to:

Reading: Chapter 4 in Walls and Mirrors. Lectures: Course introduction; abstract data types (ADTs) Recitation: No recitations this week Assignments: First programming assignment is available

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Week 1: 1/21 - 8/23

to:

Week 1: 1/21 - 1/23

Changed line 1 from:

Week 1: 8/25 - 8/29

to:

Week 1: 1/21 - 8/23

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Coming soon!

to:

Week 1: 8/25 - 8/29

Reading: Chapter 4 in Walls and Mirrors.
Lectures: Course introduction; abstract data types (ADTs)
Recitation: No recitations this week
Added lines 1-2:

Coming soon!