DS 2500: Intermediate Programming with Data
Class Schedule
| Lectures | Sec 1: TF 8:00-9:40am (RI 236 - Recording request form)
Sec 2: TF 9:50-11:30am (RI 236 - Remote attendance form) Sec 3: TF 1:35-3:15pm (CH 101 - Remote attendance form) |
| Labs (DS2501) |
Lab Sec 1. M 8:00-9:40am (WVH 212)
Lab Sec 2. M 9:50-11:30am (WVH 212) Lab Sec 3. M 11:45am-1:25pm (WVH 212) Lab Sec 4. M 11:45am-1:25pm (WVH 210B) Lab Sec 5. M 1:35-3:15pm (WVH 212) Lab Sec 6. M 1:35-3:15pm (WVH 210B) Lab Sec 7. M 3:25-5:05pm (WVH 212) Lab Sec 8. M 3:25-5:05pm (WVH 210B) Lab Sec 9. M 5:15-6:55pm (WVH 212) |
Felix Muzny (he/him & they/them) - Sections 2, 3
| f.muzny@northeastern.edu | |
| Web | https://nlp.stanford.edu/~muzny/ |
| Office Hours | On Calendly: T 12 - 1 and 3:30 - 4:30pm, W 1:30 - 3pm, Th 9 - 11am (reserve a spot) |
Laney Strange (she/her) - Section 1
| laneys@northeastern.edu | |
| Web | https://northeastern.edu/home/laney |
| Office Hours | M,W 10am-12pm EST on https://northeastern.zoom.us/my/laney
Reserve OH time or just drop in. |
Syllabus
| DS2500 Syllabus: | Download (PDF) |
| Homework Grading Policy: | Download (PDF) |
| Late/Missing Forms: | See policies page for more information.
Missing Lab Late Project |
Teaching Assistants
| Name | Office Hours -- Zoom |
|---|---|
Siddhant Sukhatankar (he/him) |
Thu 3-5pm; 5:30-6:30pm -- Zoom Link |
Yashvi Bhandari (she/her) |
Thu 9am-12pm -- Zoom Link |
Shiva Keerthan Jalla (he/him) |
Fri 9am-12pm -- Zoom Link |
Omkar Pradhan (he/him) |
Weds 8:30-11:30am -- Zoom Link |
Hongyu Li (he/him) |
Weds, Thu 12pm-2pm -- Zoom Link |
Unnat Goenka (he/him) |
Tue 12-3pm -- Zoom Link |
|
Neha Cholera (she/her) |
Mon 4:30-7:30pm -- Zoom Link |
Julian Benitez Mages (he/him) |
Weds 11am-1pm, Thu 3-5pm -- Weds Zoom Link, Thurs Zoom Link |
Preethi Kurra (she/her) |
Weds 10am-1pm -- Zoom Link |
Sree Nukala (he/him) |
Tue 3:30-6:30 -- Zoom Link |
Anish Satalkar (he/him) |
Fri 12-3pm -- Zoom Link |
About the course
Catalog Discription
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, composition, and inheritance. Advanced programming skills will cover software architecture, recursion, profiling, unit testing and debugging, lineage and data provenance, using advanced integrated development environments, and software control systems. 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. Additional assigned readings will survey topics in ethics, model bias, and data privacy pertinent to today's big data world. Accompanied by DS2501: Lab for DS2500 (1.000 credits) in which students will practice the programming techniques discussed in lecture through hands-on experimentation.5.000 Credit Hours (4.000 Lecture, 1.000 Lab - DS 2501 - required corequisite)
Prerequisites: DS 2000
Quick links
| Python | python.org |
| Anaconda | Python+Libraries+Tools Install python, libraries, Spyder, Jupyter in one step. |
| Piazza | http://piazza.com/northeastern/spring2022/ds2500/home Course discussion board. Pose questions. Answer questions. (Don't post code!) |
| Gradescope | https://www.gradescope.com/courses/334279 (access code: 3YJX7G) Submit your DS2500 homework here! |
| Other helpful links | |
| DS2000 Python Handouts |