Overview

Description

CALENDAR DESCRIPTION:

An elementary introduction to computing science and computer programming, suitable for students with little or no programming background. Students will learn fundamental concepts and terminology of computing science, acquire elementary skills for programming in a high-level language, e.g. Python. The students will be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode; data types and control structures; fundamental algorithms; recursion; reading and writing files; measuring performance of algorithms; debugging tools; basic terminal navigation using shell commands. Treatment is informal and programming is presented as a problem-solving tool. Students with credit for CMPT 102, 128, 130 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129, 130 or 135 first may not then take this course for further credit. Quantitative/Breadth-Science.

COURSE DETAILS:

CMPT 120 Placement Test
Do you have enough computing knowledge to pass our placement test? Have you taken Computing Science courses in High School or elsewhere? Have you worked in a business or volunteered as a computer programmer? Have you written programs of 200-300 lines of code or more?
IF YES you may NOT have to take CMPT 120 and could enroll directly into the next required course – CMPT 125. Challenge yourself and take our placement test.  https://courses.cs.sfu.ca/forms/cmpt-cmpt-120-placement-test/
IF NO – please go ahead and enroll in CMPT 120! You are in the right place!

Course Info
You will learn computer science concepts and solve real-world problems using the Python programming language. This course will be offered in person, face-to-face. Details of technology and tools needed in class and for tests will be provided in the first class of the semester. 

This course's lecture time will often feature live coding exercises where we will collaboratively work through creating a program. Students are recommended to bring a laptop to lecture, if possible. Labs will help you apply the ideas you have learned with the support of TAs. Assignments will help further build your confidence with problem solving through programming. Some assignments will allow you to work with a partner (if you choose). Once you have successfully completed the course, you will have the necessary skills to program the computer to solve interesting problems. Plus, you will appreciate and write quality code for good causes.

New AI tools (like ChatGPC and Co-pilot) can complement many of the skills taught in this class. However, students must learn to write the code themselves and not just rely on an AI. To ensure students are learning the material by completing assignments, there will be an in-class quiz announced for most assignments. A student's mark for each assignment will be calculated as: (their percentage on the assignment submission) * (their percentage on the assignment's quiz). For example, a student who earns 95% on their assignment submission, and 86% on the associated quiz will earn 81.7% for that assignment overall.

Topics

• Algorithms and computational thinking
• Procedural programming in Python
• Data types and control structures
• Application areas within computing science
• Fundamental algorithms, including searching, sorting, basics of recursion
• Computability and complexity, introduction
• Basics of binary encoding

Grading

Materials

MATERIALS + SUPPLIES:

Reference Books

• Computer Science Illuminated, Nell Dale, John Lewis, Jones & Bartlett, 2012, 9781449672843
• Starting out with Programming Logic and Design, Tony Gaddis, Pearson, 2015, 9780133985078
• Starting out with Python-4th Edition, Tony Gaddis, Pearson, 2017, 9780134543666

REQUIRED READING:

REQUIRED READING NOTES: