EECS 2502 S: Data Structures for Data Science
Winter 2026
General Information
Instructor: Suprakash Datta
Office: LAS, room 3043
Lectures: Tue, Thu: 4-5:20 pm in CB 115
Lab: Fri 10-11:20 am, 11:30 am -12:50 pm in Ross S 110
Office Hours (tentative): Mon, Wed 5:00-6:00 pm LAS 3043, or by appointment
Email: [lastname]@yorku.ca
TA: TBA
News
- Welcome to EECS 2502 S. This public webpage and the course eClass page will together have all the course information.
Lectures
Slides and videos are on eClass.
Resources
Textbook
Michael T. Goodrich, Roberto Tamassia, Michael H. Goldwasser. Data Structures and Algorithms in Python , 1st Edition. Wiley, 2013.
Assessment Components
The lower scoring midterm test is worth 15% for each student so the 2 tests are together worth 35%.
| Classroom activities |
10% |
| wLabs |
15% |
| Test 1 |
20% |
| Test 2 |
20% |
| Exam |
40% |
Course Learning Outcomes
Upon successful completion of the course a student will be able to:
-
Select, and implement foundational data structures using an Object-Oriented language
- Determine appropriate algorithmic patterns for a given problem.
- Analyze the time and space complexity of algorithms using asymptotic notation
- Apply data structures to address practical programming tasks and problems in data science
Important dates
- Winter classes start: Jan 5
- No Classes: Reading Week (Feb 14 - 20)
- Last date to drop course without receiving a grade : March 14
- Classes end: April 6
- Exam period: April 8 - 24 (both inclusive)
- Holiday: April 3 (Good Friday)
- Test 1: Tentatively Feb 10, syllabus : On eClass
- Test 2: Tentatively Mar 17, syllabus: On eClass
- Final: scheduled by the registrar, syllabus: Everything covered in the course.