About DS2500
Provides intermediate to advanced python programming for data science with the aim of preparing students for more advanced courses in data science and to enable practical contributions to software development and data science projects in a commercial setting. Covers object-oriented design patterns using Python, including encapsulation and composition. Through case studies, the course will survey key concepts in data science with an emphasis on machine-learning (classification, clustering, deep learning), data visualization, and natural language processing.
Accompanied by DS2501: Lab for DS2500 (1.000 credits) in which students will practice the programming techniques discussed in lecture through hands-on experimentation.
| Topics |
Data Science techniques: data visualization, fundamental data statistics, linear regression, correlation and covariance, scaling and normalization, k-means clustering, k-nearest neighbor classification, cross-validation, decision trees, polynomial regression.
Intermediate Programming: loops, functions, files, Python data structures, classes and objects, command-line, code design and quality, unit testing.
Python Libraries and Tools: Jupyter Notebooks, Pandas, NumPy, Scikit, Seaborn, Geopandas.
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| Syllabus
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DS2500 Spring '25 |
| Piazza
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https://piazza.com/northeastern/spring2025/ds2500 |
| Lecture Questions
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https://bit.ly/ds2500_lecture_q
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| Grading Guidelines
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Code quality & Visualizations
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Gradescope
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https://www.gradescope.com/courses/915440 |
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TA Appreciation
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Feedback form |
Professor & Office Hours
Laney's Office Hours begin Tuesday, January 7th. We do not hold office hours on university holidays. (TA office hours begin on Monday, January 13th -- details on the TA page.)
Laney Strange (she/her)
| laneys@northeastern.edu | |
| Web | https://northeastern.edu/home/laney |
| Zoom (for OH) | https://northeastern.zoom.us/my/laney |
| Office Hours | M 9-10:30am, R 11am-12:30pm (schedule a 15-min slot during OH or just drop in. Meserve 313, or my Zoom. Appointments take priority, though!)
Some weeks the hours might vary a tiny bit. Check the calendly link for the most updated hours! If the Mon and Thur office hours get booked quickly, or if they don't work for you, please just email me and we'll set up something else. |
Lecture Schedule
- DS2500 lectures introduce key concepts and dive into examples and applications. Lectures are in-person and attendance is expected. We don't want or expect anyone to come to class when they're sick, though, so we'll post notes and code after class every day, which you can use to catch up on any missed material. We'll alternate weeks focusing on Python programming, and focusing on data science techniques.
- DS2501 labs will have a graded assignment each week, due at 9pm on Monday. Most of these assignments are auto-graded, so we need you to follow the specs exactly (function names, files names, etc.). There are generally 5 problems per lab, and 3 of them need to pass the autograder for full credit.
| DS2500-01 (Lecture) | TF 9:50-11:30am
CH 101 |
| DS2500-02 (Lecture) | TF 1:35-3:15pm
SN 168 |
| DS2500-03 (Lecture) | TF 3:25-5:05pm
SN 168 |
| DS2501-01 & -03 (Lab) | M 8:00-9:40am
WVH 210A (both sections meet in 210A) |
| DS2501-04 (Lab) | M 9:50-11:30am
WVH 210A |
| DS2501-05 (Lab) | M 9:50-11:30am
WVH 210B |
| DS2501-06 (Lab) | M 11:45am-1:25pm
WVH 210A |
| DS2501-07 (Lab) | M 11:45am-1:25pm
WVH 210B |
| DS2501-08 (Lab) | M 1:35-3:15pm
WVH 210A |
| DS2501-09 (Lab) | M 1:35-3:15pm
WVH 210B |
| DS2501-10 (Lab) | M 3:25-5:05pm
WVH 210A |
| DS2501-13 (Lab) | M 3:25-5:05pm
WVH 210B |
New to Python or feeling a little rusty?
Below we've collected helpful videos from DS2000 and some other useful links.| DS2500 Videos - Python Review | |
| DS2000 Videos - Basic Python | |
| DS2000 Videos - Functions, Scope, Data Structures | |
| DS2000 Videos - Classes & Objects; Data Science Techniques | |
| Additional Python Resources |