Class Schedule

Lectures Sec 1: TF 11:45am - 12:50pm. Online only. Rachlin.
Sec 2: TF 9:50am - 10:55am. RI 236. Muzny.
Sec 3: TF 1:35pm - 2:40pm. RI 236. Muzny.
Sec 4: TF 3:25pm - 4:30pm. CH 103. Muzny.
Practicum (DS2001)
Section Topic/Focus Area Time Location Instructor Website
1 Computer & Info Sci R 11:45am - 1:25pm Online Only Rachlin Canvas
2 Health Sci W 9:50am - 11:30am WVH 212 Sathyanarayana
3 Computer & Info Sci W 9:50am - 11:30am WVH 210B Mosca Canvas
4 Social Sciences & Humanities W 9:50am - 11:30am KA 005 Zhang
5 Social Sciences & Humanities W 11:45am - 1:25pm WVH 210A Zhang
6 Business Admin W 11:45am - 1:25pm WVH 212 Luo Canvas
8 Business Admin W 2:50 - 4:30 pm WVH 210A Gillani Canvas
9 Business Admin W 2:50 - 4:30 pm WVH 212 Luo Canvas
10 Social Sciences & Humanities W 2:50 - 4:30 pm WVH 210B Uslu
11 Business Admin W 4:40 - 6:20 pm WVH 210A Gillani Canvas
13 Computer & Info Sci R 9:50am - 11:30am WVH 210B Strange Canvas
14 Computer & Info Sci R 9:50am - 11:30am WVH 212 Mosca Canvas
15 Computer & Info Sci R 11:45am - 1:25pm WVH 210A Strange Canvas
16 Computer & Info Sci R 11:45am - 1:25pm WVH 212 Mosca Canvas
17 Business Admin R 11:45am - 1:25pm WVH 210B Luo Canvas
18 Social Sci & Humanities R 2:50 - 4:30 pm WVH 212 Qu
20 Business Admin R 2:50 - 4:30 pm WVH 210B Luo Canvas


DS2000 Syllabus: Download (PDF)
DS2000 Grading Rubric: Download (PDF)
DS2000 Style Guide: Download (PDF)


Felix Muzny (they/he) - Sections 2, 3, 4

Office Hours Some Mondays, all Thursdays AM and early PM
OH Link Reserve OH time

John Rachlin (he/him) - Section 1

OH Link
Office Hours W, R
Reserve OH time or email to set up a different time.

Teaching Assistants

All information about TAs and their office hours can be found on the office hours/TAs page.

About DS2000

Introduces programming for data and information science through case studies in business, sports, education, social science, economics, and the natural world. Presents key concepts in programming, data structures, and data analysis through Python. Integrates the use of data analytics libraries and tools. Surveys techniques for acquiring and programmatically integrating data from different sources. Explains the data analytics pipeline and how to apply programming at each stage. Discusses the programmatic retrieval of data from application programming interfaces (APIs) and from databases. Applies data visualization techniques to summarize and communicate the analysis of data.

New programmers are welcome; we don't assume any previous knowledge and we'll start from the very beginning.

The practicum that accompanies the lecture is DS2001. It's an interdisciplinary structure where you gain hands-on experience applying data science techniques and knowledge to specific topical areas. Each DS2001 section is taught by an instructor from Khoury, Bouve, D'Amore-McKim, or CSSH.

DS2000 and DS2001 grades are separate. Your DS2001 instructor will have their own syllabus, assignments, and grading structure. DS2001 assignments typically contextualize what we learn in lecture to a specific topic, but are separate from, and not necessarily related to, the DS2000 homework assignments.

Classroom Environment & Expectations

Please read the syllabus for complete information on classroom environment and expectations.

In summary, we design our classes to be interactive. Please ask questions, and answer questions! In programming, we seldom get anything right on the first try. We see how an attempt turned out, and we try again. We like our classrooms to reflect that approach as well; so please answer a question that's been posed, even if you're not sure of the answer.

To create and preserve a classroom atmosphere that optimizes teaching and learning, all participants share a responsibility in creating a respectful and non-disruptive forum for the discussion of ideas.

Students are expected to conduct themselves at all times in a manner that does not disrupt teaching or learning. This class is designed for beginners. If you happen to have some experience with Python, we expect you to be supportive and respectful of your classmates who don't.

Course Website & Canvas

This is the website to find everything on. Please bookmark it. We will always link assignments from the schedule page to where you'll need to turn them in.

We use Canvas for its grade-book functionality. About a week after your grades have been posted on Gradescope, we'll post them to Canvas. On Canvas, you'll find links to this website and turn-in links to your assignments on Canvas.