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Textbook: John Zelle, Python Programming: An Introduction to Computer Science, Franklin Beedle & Associates, 2003.

 Your Mission: for your assigned topic(s)/class(es), prepare and present:

  • Topics / learning objectives ("students should be able to...")
  • Course slides (using HTML template developed by Wes and Patti)
  • Homework assignment (programming "project" - mostly one-week projects; later in semester, will probably want one to three 2-week projects; some assignments could be based in the Python tutor and not necessarily hand-graded)
  • Laboratory activity (that reinforces concepts and helps students prepare to do the programming assignment)
  • Sample exam questions (some multiple choice, some short answer / mini programming)

(We recognize that these may not all be completely developed and polished by the time you present, and will probably evolve as the course evolves; the idea is that over the course of the second half of the semester, each student in 691P will develop 1 or 2 weeks worth of course material.)
Additional tasks:

  • David W - Python tutor (from MIT)
  • Wes & Patti - HTML template for slides
  • Will - grading scripts; Subversion repository for course materials 

Other Topics (that span the semester & should be worked in throughout):

  • Problem-solving skills and approaches; choosing the right data structure for the problem
  • Debugging & testing
  • Computer science areas (databases, AI, graphics/visualization, information retrieval, operating systems, computer architecture/digital logic, networks, crypto/security, social/ethical issues...) - the idea is to work these in with a few slides of commentary, or in the programming/lab assignments, where possible, to give students a broader exposure to the field of CS ("beyond just programming")

Tentative Course Topics (by week):

Week

Topic

Reading

Who

1

Introduction to Python and Linux

Chap 1-2

Patti

2

Numbers and Strings

Chap 3-4 (skip 4.6?)

Patti

3

Conditionals and Booleans

Chap 7

James

4

Functions, documentation, I/O

Chap 6

James

5

Graphics, Objects, and Methods

Chap 5

Wes

6

Loops, functional decomposition

Chap 8, 9

Don

7

Loops, design II

Chap 8, 9

Don

8

Abstract data types: Lists, dictionaries, sets, stacks, queues, etc

Chap 11

David W

9

Searching, algorithm analysis

Chap 13.1

Travis

10

Recursion, sorting

Chap 13.2-13.3

Will

11

Recursion, sorting II

Chap (question)

Will

12

Defining new classes

Chap 10

David R

13

Object-oriented design

Chap 12

David R

14

(one class - review? leave open for snow day / slippage?)

N/A

N/A


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