Simon Fraser University
Engaging the World

Course Outlines

Summer 2025 - CMPT 353 D100

Computational Data Science (3)

Class Number: 3819

Delivery Method: In Person

Overview

  • Course Times + Location:

    May 12 – Aug 8, 2025: Tue, 12:30–2:20 p.m.
    Burnaby

    May 12 – Aug 8, 2025: Fri, 12:30–1:20 p.m.
    Burnaby

  • Prerequisites:

    CMPT 225 and (BUS 232, STAT 201, STAT 203, STAT 205, STAT 270, STAT 271, ENSC 280, MSE 210, or SEE 241), with a minimum grade of C-.

Description

CALENDAR DESCRIPTION:

Basic concepts and programming tools for handling and processing data. Includes data acquisition, cleaning data sources, application of machine learning techniques and data analysis techniques, large-scale computation on a computing cluster.

COURSE DETAILS:

This course will be an introduction to the tools and techniques in data science. We will explore common challenges and solutions used in analysis of data.

Topics

  • Basics of data science: concepts, goals, motivation, expectations.
  • Introduction to selected data processing tools: Python with numpy and pandas.
  • Working with data. Cleaning data; extract, transform, load tasks; applying concepts from statistics.
  • Machine learning basics with existing implementations (such as scikit-learn).
  • Data analysis strategies: selecting techniques from statistics and machine learning.
  • Big data tools.
  • Data visualization and summarizing results.

Grading

NOTES:

Will include weekly exercises, quizzes (in lecture time), a project, and a final exam. Details will be discussed in the first week of class.

Students must attain an overall passing grade on the weighted average of exams in the course in order to obtain a clear pass (C- or better).

Materials

REQUIRED READING NOTES:

Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

At SFU, you are expected to act honestly and responsibly in all your academic work. Cheating, plagiarism, or any other form of academic dishonesty harms your own learning, undermines the efforts of your classmates who pursue their studies honestly, and goes against the core values of the university.

To learn more about the academic disciplinary process and relevant academic supports, visit: 


RELIGIOUS ACCOMMODATION

Students with a faith background who may need accommodations during the term are encouraged to assess their needs as soon as possible and review the Multifaith religious accommodations website. The page outlines ways they begin working toward an accommodation and ensure solutions can be reached in a timely fashion.