Full materials

Below is a mirror of the website previously hosted at:

http://www.sfu.ca/~jlumbros/Courses/CMPT120/

CMPT 120 webpage for Spring 2014

Disclaimer: some of the materials in this course, and on this site, are inspired or borrowed with permission from past instructors, including Diana Cukierman.

Teaching Team

• Instructor: Jeremie Lumbroso

• TAs:

  • Bhavesh Gupta
  • Dan Lin
  • Zhensong Qian

• Note 1: when contacting us generally about course information, please use cmpt-120-help@sfu.ca: all of us will receive your email at the same time, and so all four of us gets a chance to reply, so faster responses.

• Note 2: please put “CMPT 120” at the beginning of your subject line when contacting any of us.

Office hours: in TASC 1 9025, on appointment; for general help, tutorials are scheduled in TASC 1 9204, Thursday 12:30pm-2:30pm (and sometimes Friday 12:30pm-2:30pm).

Assignments

• Assignment 1 due by Saturday March 15th at 11:55pm on CourSys and its solution.
• Assignment 2 due by Saturday April 12th at 11:55pm on CourSys its solution.

Lecture Slides

Week 1

• Lecture 0, a general overview of the course (Jan. 6th)
• Lecture 1, what is an algorithm? (Jan. 8th)
• Lecture 2, from algorithms to pseudocode (Jan. 10th)

Week 2

• Lecture 3, what are variables, and some example algorithms (Jan. 13th)
• Lecture 4, a brief history of programming languages, and first steps in Python (Jan. 15th)
• Lecture 5, elementary data type and basic control structures (Jan. 17th)

Week 3

• Lecture 6, introduction to functions and modules (Jan. 20th)
• Lecture 7, turtles (Jan. 22nd) and the code snippets
• Lecture 8, turtles (Jan. 24th)

Week 4

• Lecture 9, strings (Jan. 27th)
• Lecture 10, correction of Course Exercise 3, which you may look up here (Jan. 29th)
• Lecture 11, correction of the turtle spiral

Week 5

• Lecture 12, the associated video (using password “cmpt120”) and PeerWise questions (Course ID: 8709 and Identifier: SFU ID) (Feb. 3rd)
• Quiz 1 and the answers (Feb. 5th)
• Lecture 13 by guest lecturer, Diana Cukierman, flag variables (Feb. 7th)

Week 6

• Lecture 14, the associated video (using password “cmpt120”), user input and complex flags example, intro to nested fors (Feb. 17th)
• Lecture 15, no slides, overhead correction of search and replace
• Lecture 16, no slides, overhead correction of search and replace (continued)

Week 7

• Lecture 17, with code for replace_substr both using nested for loops and a while loop (Feb. 24th)
• Lecture 18, clarification on if statements and more on while loops (Feb. 26th)
• Lecture 19, the while loop continued and more examples (Feb. 28th)

Week 8

• Lecture 20, immutability of strings and iClicker interactive discovery of lists (Mar. 3rd)
• Lecture 21, iClicker prep (Mar. 5th)
• Quiz 2 and the answers (Mar. 7th)

Week 9

• Lecture 21, manipulating lists is just like strings (Mar. 10th)
• Lecture 22, index vs slice, and functions that create new lists, and the is_matrix(L) correction (Mar. 12th)
• Lecture 23, built-in operations on lists, and their mutability; and some experiments on list mutability (Mar. 14th)

Week 10

• Lecture 24, deleting an element from a list and Course Exercise 7 and its solution (Mar. 17th)
• Lecture cancelled on March 19th
• Midterm and its solution (Mar. 21st)

Week 11

• Lecture 25, introduction to files, reading/writing; a help guide on how to access the Python folder and the solution to the two course questions (Mar. 24th)
• Lecture 26, continuing file access (and the work files)
• Lecture 27, writing to files (Mar. 28th)

Week 12

• Lecture 28
• Lecture 29
• Lecture 30

Week 13

• Recap Lecture and practice questions (April 7th)
• Practice exam

Labs

Lab Week 3
Lab Week 4 (should be submitted on CourSys)
Lab Week 5 (should be submitted on CourSys)
Lab Week 6 and the beginning source code (should be submitted on CourSys)

Resources

CodeWrite

Python

• Get Python and IDLE v2.7.6 on the official webpage:
  • if you have Windows, you can either get the 64-bit version if you have a 64-bit computer (“X86-64”), or if you don’t know what kind of computer, you can take the 32 bit version (the first one in the list)
  • if you have a Macintosh, pick according to your version of Mac OS X
• Python Tutor to visualize the execution of Python code.
• an online environment to code Python

Puzzles

• Pseudocode exercises with Blocky: http://code.org/api/hour/begin/codeorg
• Puzzles for algorithmic training with Lightbot: http://light-bot.com/hoc.html