Course Goals

This course introduces programming for data and information science...

Lectures will focus on developing an advanced understanding of programming using Python by way of examples and case studies germane to Data Science.
Homework will apply conceptual knowledge via problems and code implementation.
Labs will practice concepts from lecture
Project will analyze and visualize a dataset programmatically.

Attendance Policy

Please do not come to class or lab when you're sick. We'd much rather you stay home and take care of yourself.

Attendance is not required in lecture, unless you are scheduled to give a presentation. If you need to stay home and miss class, there is no need to notify us in advance. Just let us know, and we'll make a recording of one lecture section available to you.

Participation IS required in lab. If you ever need to miss lab, fill out this Missing Lab form by Sunday night.

Recommended Textbook

The textbook is available online via Northeastern's digital library. Relevant chapters will be listed alongside lecture topics on the schedule page. You do not need to read the textbook ahead of lecture; it's most useful as reference materials or for looking up new examples. Keep it handy when working on the homework or reviewing your lecture notes.

Title Deitel and Deitel (2019): Intro to Python for Computer Science and Data Science (Pearson)
Buy online Amazon.com
Digital (free) (Login by selecting "not listed?" and providing your NEU email.)

Evaluation

The grades for DS 2500 and DS 2501 (Lab) are merged. You will receive the same grade for both the lecture and the lab. You grade is determined as follows:

  • Homework: 10%
  • Project #1: 30%
  • Project #2: 30%
  • Lab Assignments (lowest dropped): 30%

Final grades for DS 2500 will be assigned based on the following scale:

LetterRange
A94 - 100
A-90 - 93
B+87 - 89
B83 - 86
B-80 - 82
C+77 - 79
C73 - 76
C-70 - 72
D+67 - 69
D63 - 66
D-60 - 62
F<60

Homework

Homework for DS 2500 will be submitted through Gradescope. You’ll submit two components each week:

  1. A self-reflection, answering questions about how the assignment went and what you learned.
  2. The programming assignment itself, usually .py or .ipynb files.

Your self-reflection will be graded. You receive full homework credit for answering all self-reflection questions.

Your solution to the programming assignment will not be traditionally graded. In your self-reflection, you have the option to ask us for feedback, and we’ll review and comment on any components that you like.

This policy applies only to weekly homework assignments; projects will be graded traditionally on an A-F scale.

DS2501 Lab

The DS2501 will follow the model of the DS2001 Practicums (except that the topic will always be general Data Science). We'll gain hands-on practice with recent material, prepare for upcoming homeworks, and/or review recent homework solutions.

You'll be graded on the lab assignment. Scores will be in the range 0-5, and it is based on participation and effort on the lab assignments.

Participation in lab is required, and your attendance is expected in the section you're officially registered in. However, we don't expect anyone to attend in-person when they are unwell. If you ever need to miss lab, fill out this Missing Lab form by Sunday night.

Projects

You'll do two projects this semester. They will be traditionally graded on an A-F scale. The goal of the projects are to gain hands-on experience with data science.

The first project will be a solo effort, and the second project will be team-based.

Project deliverables include source code, a written paper (project #2 only), and a presentation. Communication is an essential skill for data scientists. We expect that your written work and oral presentations will be top-notch, and they will be evaluated accordingly.

You are expected to present your project in the time slot you signed up for. However, we don't expect anyone to power through a time they are unwell. If needed, fill out this Late Project form at least 24 hours before your scheuled presentation or the project deadline.

Late Policy

You may submit your homework up to 48 hours late for full credit. If you submit late, you will not receive any feedback on your code.

You may not submit your projects late, and you may not miss your project presentations. However, we don't expect anyone to attend in-person when they are unwell. In case of extenuating circumstances, fill out this Late Project form at least 24 hours before your scheduled presentation or the project deadline.

Your attendance in lab is required. Submit your lab work at the end of your section. No late submissions will be accepted, but we drop your lowest lab grade at the end of the semester. However, we don't expect anyone to attend in-person when they are unwell. In case of extenuating circumstances, fill out this Missing Lab form by Sunday night.

Academic Conduct

You are free to discuss homeworks and share code with your classmates. You may not post code on piazza.

Finding and using code you find online is acceptable, as long as (1) you cite it in a comment, and (2) you do not ask TAs or instructors to help you fix it if it doesn’t work. We’ll help you work out problems with your code, not someone else’s.

Classroom Environment

To create and preserve a classroom atmosphere that optimizes teaching and learning, all participants share a responsibility in creating a civil 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. Your comments to others should be constructive and free from harassing statements. You are encouraged to disagree with other students and the instructor, but such disagreements need to respectful and be based upon facts and documentation (rather than prejudices and personalities). The instructor reserves the right to interrupt conversations that deviate from these expectations. Repeated unprofessional or disrespectful conduct may result in a lower grade or more severe consequences. Part of the learning process in this course is respectful engagement of ideas with others.

Title IX

Title IX of the Education Amendments of 1972 protects individuals from sex or gender-based discrimination, including discrimination based on gender-identity, in educational programs and activities that receive federal financial assistance.

Northeastern’s Title IX Policy prohibits Prohibited Offenses, which are defined as sexual harassment, sexual assault, relationship or domestic violence, and stalking. The Title IX Policy applies to the entire community, including male, female, transgender students, faculty and staff.

If you or someone you know has been a survivor of a Prohibited Offense, confidential support and guidance can be found through University Health and Counseling Services staff (http://www.northeastern.edu/uhcs/) and the Center for Spiritual Dialogue and Service clergy members (http://www.northeastern.edu/spirituallife/). By law, those employees are not required to report allegations of sex or gender-based discrimination to the University.

Alleged violations can be reported non-confidentially to the Title IX Coordinator within The Office for Gender Equity and Compliance at: titleix@northeastern.edu and/or through NUPD (Emergency 617.373.3333; Non-Emergency 617.373.2121). Reporting Prohibited Offenses to NUPD does NOT commit the victim/affected party to future legal action.

Faculty members are considered "responsible employees" at Northeastern University, meaning they are required to report all allegations of sex or gender-based discrimination to the Title IX Coordinator.

In case of an emergency, please call NUPD Emergency line 617-373-3333.

Please visit http://www.northeastern.edu/titleix for a complete list of reporting options and resources both on- and off-campus.

Students with Disabilities

Students who have disabilities who wish to receive academic services and/or accommodations should visit the Disability Resource Center at 20 Dodge Hall or call (617) 373-2675. If you have already done so, please provide your letter from the DRC to me early in the semester so that I can arrange those accommodations.