Fall 2023 - CMPT 353 D100
Computational Data Science (3)
Class Number: 6139
Delivery Method: In Person
Course Times + Location:
Sep 6 – Dec 5, 2023: Mon, 12:30–2:20 p.m.
Oct 10, 2023: Tue, 12:30–2:20 p.m.
Sep 6 – Dec 5, 2023: Wed, 12:30–1:20 p.m.
Exam Times + Location:
Dec 13, 2023
Wed, 8:30–11:30 a.m.
1 778 782-5755
Prerequisites:CMPT 225 and (STAT 101, STAT 270, STAT 271, ENSC 280, or MSE 210), with a minimum grade of C-.
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.
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.
- 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.
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).
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.
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity website http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the university community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the university. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the university. http://www.sfu.ca/policies/gazette/student/s10-01.html
Students with a faith background who may need accommodations during the semester 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.