Class |
Section 1: TF 9:50-10:55 (Int. Village 019) Section 2: TF 11:45-12:50 (Hurtig Hall 129) Section 3: TF 1:35-2:40 (Int. Village 019) |
r.sanghrajka@northeastern.edu | |
Office Hours | Wed 9a-1p, Thu 1p-5p in Meserve 309 or Zoom by appointment You may make an appointment or just drop in. Appointments take priority! |
Class | Section 4: TF 1:35-2:40 (Online. See Canvas for Zoom info.) |
j.rachlin@northeastern.edu | |
Office Hours | Wed 10a-12p, Thu 2p-5p on Zoom and by appointment only. |
k.mclaughlin@northeastern.edu For logistical questions about the course or extension requests. Please note that due to the large class size, assignment extensions can only be granted under extraordinary circumstances. Otherwise, our late submission policy (10% penalty 1-48 hours late) will apply. |
Title | Deitel and Deitel (2019): Intro to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud, 1ed. (Pearson) |
Buy online | Amazon.com Digital (free) |
Description | The Deitels’ Introduction to Python for Computer Science and Data Science: Learning to Program with AI, Big Data and the Cloud offers a unique approach to teaching introductory Python programming, appropriate for both computer-science and data-science audiences. Providing the most current coverage of topics and applications, the book is paired with extensive traditional supplements as well as Jupyter Notebooks supplements. Real-world datasets and artificial-intelligence technologies allow students to work on projects making a difference in business, industry, government and academia. Hundreds of examples, exercises, projects (EEPs), and implementation case studies give students an engaging, challenging and entertaining introduction to Python programming and hands-on data science. |
Title | Downey (2015): Think Python: How to think like a Computer Scientist (O'Reilly) | |
Buy online | Amazon.com Digital (free) |
|
Description | If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3. |
Anaconda | A python distribution. Includes the python programming language, libraries, and development tools. |
Piazza | The course discussion board. Have questions? Get answers fast! |
Canvas | Obtain lecture notes and assignments. Attendance. |
Other helpful links |
Section | Instructor | Topic | When | Where |
---|---|---|---|---|
01 | Rachlin | Data Science | W 2:50p - 4:30p | Online See the DS2001-01 canvas page for Zoom connection links. |
02 | Muzny | Data Science | W 11:45p - 1:25p | West Village H 210A |
03 | Muzny | Data Science | W 2:50p - 4:30p | West Village H 210B |
06 | Muzny | Data Science | R 2:50p - 4:30p | West Village H 210A |
07 | Zhang | Soc Sci | F 1:35p - 3:15p | West Village H 210A |
08 | Muzny | Data Science | R 11:45a - 1:25p | West Village H 210B |
09 | Zhang | Soc Sci | F 3:25p - 5:05p | West Village H 210A |
10 | Yin | Business | T 1:35p - 3:15p | Snell Library 011 |
11 | Yin | Business | T 3:25p - 5:05p | East Village 010 |
12 | Yin | Business | R 9:50a - 11:30a | Cahners 004 |
13 | Yin | Business | R 11:45p - 1:25p | East Village 010 |
14 | Matherly | Business | W 11:45a - 1:25p | Richards 241 |