DS 2000: Programming with Data

Rush Sanghrajka

Assistant Teaching Professor

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)
E-mail 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!

John Rachlin

Associate Teaching Professor

Class Section 4: TF 1:35-2:40 (Online. See Canvas for Zoom info.)
E-mail j.rachlin@northeastern.edu
Office Hours Wed 10a-12p, Thu 2p-5p on Zoom
and by appointment only.

Kayla McLaughlin

Course Coordinator

E-mail 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.

About the course

Catalog Description

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 and Excel. 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. Introduces predictive analytics for forecasting and classification. Demonstrates the limitations of statistical techniques.

2.000 Credit Hours
Corequisites: DS2001 (Practicum for DS2000) 2.000 credits.

Textbooks

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.

DS2001: Programming Practicum

Weekly tutorials and a final class project relevant to your practicum topic.

SectionInstructorTopicWhenWhere
01RachlinData ScienceW 2:50p - 4:30pOnline
See the DS2001-01 canvas page
for Zoom connection links.
02MuznyData ScienceW 11:45p - 1:25pWest Village H 210A
03MuznyData ScienceW 2:50p - 4:30pWest Village H 210B
06MuznyData ScienceR 2:50p - 4:30pWest Village H 210A
07ZhangSoc SciF 1:35p - 3:15pWest Village H 210A
08MuznyData ScienceR 11:45a - 1:25pWest Village H 210B
09ZhangSoc SciF 3:25p - 5:05pWest Village H 210A
10YinBusinessT 1:35p - 3:15pSnell Library 011
11YinBusinessT 3:25p - 5:05pEast Village 010
12YinBusinessR 9:50a - 11:30aCahners 004
13YinBusinessR 11:45p - 1:25pEast Village 010
14MatherlyBusinessW 11:45a - 1:25pRichards 241
Note: There is no Section 04 or 05