Description
DS 121 is the second in the three-course sequence (DS 120, 121, 122) that introduces students to theoretical foundations of Data Science. DS 121 covers an introduction to key concepts from Linear Algebra (vector space, independence, orthogonality and matrix factorizations). The DS theme running through the course is exploratory data analysis, enabling a better understanding of the data at hand. The course will link mathematical concepts with computational thinking, specifically through the use of problem sets that require students to answer mathematically-posed questions using computation. Effective Fall 2021, this course fulfills a single unit in each of the following BU Hub areas: Digital/Multimedia Expression, Quantitative Reasoning I, Critical Thinking. Prerequisites: DS 110 and 120, or equivalents.
General Information
Lectures and office hours
The course instructor is Prof. Mayank Varia. This class meets twice per week, on Tuesdays and Thursdays, at 11am-12:15pm in room EPC 209. I actively encourage questions and interactive discussion during lectures and recitation labs. There is a lesson plan on the right half of this page, which is subject to updates over time. I will post lecture notes and videos on Piazza after each lecture. If an IT problem prevents me from uploading a video, I will find a link to a video on a similar topic available online. Lectures are accessible via Zoom: https://bostonu.zoom.us/j/93180698061?pwd=OTlqTWR2cnkxRHRjaElHbkdZL1Jpdz09
Discussion section
Discussion sections will be led by TA Erfan Khalaj. There are two discussion sections: Wed 10:10-11:00am in **MCS 141** [location updated!], and Wed 1:25-2:15pm in EOP 270. Since the class size is small, I will run a poll on Piazza to see if we can compress the discussion into a single section.
Office hours
I will hold office hours on Tuesday afternoons at 2-3:30pm in MCS 138R. Any changes from the usual time will be noted both in class and here on Piazza. If you want to meet with me but cannot make office hours, send me a private note on Piazza with at least 2 suggestions for times that you are available, and we will find a time to meet (either in person or on Zoom).
Absences
This course follows BU’s policy on religious observance. Otherwise, it is generally expected that students attend lectures and discussion sections. If you need to attend classes virtually for awhile, for instance due to isolation/quarantine, please join the class via Zoom. If you miss a lecture, please review the lecture notes and video posted on Piazza. If I need to teach class virtually due to isolation/quarantine, I will send a Piazza immediate announcement.
Websites and textbooks
We will use 2 websites in this class: this Piazza page for course announcements and discussion, and Gradescope for submitting homework assignments. Please sign up for both websites immediately! Additionally, we will use 3 textbooks in this class, all of which are available for free download using the links in the resources tab: https://piazza.com/bu/spring2022/ds121/resources
Assignments and Grading Criteria
Your grade in this course will come from four sources: homework (40%), two in-class tests (15% each), a class project (15%), and a final exam (20%), with a -5% adjustment for the weight of the worst test/exam score. (That is, one test will count for 10% of your grade rather than 15%, or the final exam will count 15% rather than 20%.) I will drop your lowest homework assignment; the average of the remaining ones will count for 40% of your grade. I will then convert the numerical score into a letter grade following the rubric at https://www.bu.edu/academics/wheelock/policies/grades-course-credits-incomplete-coursework/. Optionally, I might curve grades upward (but never downward!) and I might give extra credit for students who participate extensively in class and on Piazza. In summary: you should always be able to compute a lower bound on your grade in the course so far.
Academic honesty
You must adhere to BU’s Academic Conduct Code at all times. Please be sure to read it here: https://www.bu.edu/academics/policies/academic-conduct-code. In particular: cheating on an exam, passing off another student’s work as your own, or plagiarism of writing or code are grounds for a grade reduction in the course and referral to BU’s Academic Conduct Committee. If you have any questions about the policy, please send me a private Piazza note immediately, *before* taking an action that might be a violation.
Collaboration policy
I encourage you to collaborate with classmates when studying lecture materials and preparing for tests. You may also discuss ideas and approaches to the homework assignments with *one* other student, as long as (a) you write the name of the student collaborator at the top of your solution and (b) you keep these discussions at a conceptual level. You may *not* share solved homework solutions with classmates or search on the Internet for answers (though feel free to search the Internet for "IT" style issues like how to install Python packages). The same rules apply on Piazza: feel free to discuss the homework problems at a conceptual level, but don't give away specific solutions. If you are uncertain whether a particular kind of interaction with someone else violates these rules, please ask me beforehand. Finally, all tests are intended to reflect individual activity, so any form of collaboration is strictly prohibited; computers and notes are also forbidden during tests unless I explicitly state otherwise.
Homework
I will assign homework on most weeks, with breaks so you have time to study for tests and prepare your project. Homeworks will be given on Thursdays and due on the Friday of the following week at 8pm. Homeworks are accepted up to 12 hours late with a 10% grade reduction; later assignments are not accepted. Each homework problem will clearly state whether it must be solved by hand or if a computer is allowed. For the computer-based problems, please install on your personal computer the following: Python, Jupyter notebook, and several machine learning-related packages that we will discuss in lecture (e.g., by using pip or anaconda).
Gradescope for homework submission
All homework assignments must be submitted to Gradescope: https://www.gradescope.com/courses/353582 (use entry code 5VGJ3R to sign up). This is the only method to have your assignments graded. Make sure to show your work! Submissions that only state the final answer without any context will receive 0 credit. For pencil-and-paper questions, you may write your solutions on a computer using LaTeX or Word and upload a PDF, or write on paper and upload images of each page. For computer-based questions, you must submit a PDF rendering of a Jupyter notebook that shows all of your input source code and the resulting outputs, as well as comments that explain your rationale. For instructions on how to submit your assignment, see https://help.gradescope.com/article/ccbpppziu9#submitting_a_pdf. Always review your file after uploading to check that it is legible and complete!
Midterm tests
We will have 2 in-class tests on Thursday, February 17 and Tuesday, March 29. Please reserve these dates on your calendar *now*! If you have a valid conflict with an exam date, you must tell me as soon as you are aware, and with a minimum of 1 week notice (unless there are extenuating circumstances) so we can arrange a make-up exam. Any material from lectures, discussion sections, homeworks, and the required assigned reading is fair game to cover in the tests and final exam.
Project
There will be a project due in mid-April, with two components. First, you will prepare a blog post-style report on an (existing or new) application of techniques you've seen in this course. Second, you will give a short presentation about your work to the class.
Final exam
This course will have a final exam on the week of May 9, with the exact date and time set by the university. The final exam is cumulative: material from the entire semester may be included in the exam.
Update: The final exam is on Tuesday, May 10 at 12-2pm in our normal classroom -- EPC 209.
Update: The final exam is on Tuesday, May 10 at 12-2pm in our normal classroom -- EPC 209.
Re-grading policy
You have the right to request a re-grade of any homework or test. All regrade requests must be submitted using the Gradescope interface. If you request a re-grade for a portion of an assignment, then we may review the entire assignment, not just the part in question. This may potentially result in a lower grade.
Learning environment
This course follows all BU policies regarding accommodations for students with documented disabilities. I actively encourage discussion and debate on ideas, but I won’t tolerate criticism of other people. Additionally, while you can use a computer for note-taking, do not use your laptop in class for web surfing, sending messages, or anything else that can cause a distraction. Please respect your fellow classmates and contribute toward a positive learning environment.
Course feedback
I welcome feedback from you at any time about any material you would like me to cover or suggestions for how I can improve the course. I promise to consider all suggestions, though I cannot promise that I will always be able to incorporate your feedback. Please send me any comments as a private Piazza note; you can send feedback anonymously if needed.
Announcements
Final project description
4/12/22 10:07 AM
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Course schedule
1/17/22 12:28 AM
This page contains the lesson plan for DS 121 lectures. It is intended to form the course syllabus, together with the policies listed at https://piazza.com/bu/spring2022/ds121/info
The schedule will be continually updated as new textbook reading, video viewing, and homework assignments are posted. All lecture notes are available in a Google drive folder.
Part 1: The algebra and geometry of data
| Week | Topic and lecture materials | Reading / viewing | Homework |
|---|---|---|---|
| 1 |
Linearity [Lecture 1 video] |
Aggarwal section 1.1-1.2 | HW 1 assigned |
| 2 |
Vector spaces [Lecture 2 video] [Lecture 3 video] | Aggarwal sections 1.3-1.4 [Optional] Deisenroth-Faisal-Ong chapter 2 3Blue1Brown video 3, video 4, and video 5 | HW 1 due 1/30 HW 2 assigned |
| 3 |
Matrices and linear transformations [Lecture 4 video] [Lecture 5 video] | Aggarwal sections 2.1-2.3 | HW 2 due 2/4 HW 3 assigned |
| 4 |
LU decomposition [Lecture 6 video] [Lecture 7 video] | Aggarwal sections 2.4-2.5 3Blue1Brown video 6, video 7, and video 8 | HW 3 due 2/11 |
| 5 |
Bases and subspaces [Lecture 8 video] | Review Aggarwal sections 1.1-2.5 for the test |
TEST 1 on 2/17 (covers weeks 1-4) |
| 6 |
Geometry of matrices and vectors (note: no class on Tuesday 2/22) [Lecture 9 video] |
Aggarwal sections 2.4 and 2.6 Boyd-Vandenberghe chapter 3 | HW 4 assigned |
| 7 |
QR Decomposition, Eigenvalues and eigenvectors [Lecture 10 video] [Lecture 11 video] | Aggarwal sections 2.6-2.7.2 and 3.1-3.2 3Blue1Brown video 13 and video 14 | HW 5 assigned |
| (spring break) |
Part 2: Computational linear algebra
| Week | Topic | Reading | Homework |
|---|---|---|---|
| 8 |
Least squares and regression [Lecture 12 video] [Lecture 13 video] | Boyd-Vandenberghe chapter 12 |
HW 4 due on 3/14 |
| 9 |
Diagonalization and Cholesky decomposition [Lecture 14 video] [Lecture 15 video] | Aggarwal section 3.3 | HW 6 due on 3/25 |
| 10 |
Markov chains and PageRank [Lecture 16 video] [Lecture 17 video] | Aggarwal sections 10.1-10.3 and 10.6 |
TEST 2 on 3/29 (covers weeks 5-8) |
| 11 |
Singular value decomposition [Lecture 18 video] | Aggarwal sections 7.1-7.2 | HW 7 assigned |
| 12 |
Principal component analysis [Lecture 19 video] [Lecture 20 video] | Aggarwal sections 7.3-7.4 | HW 7 due on 4/11 HW 8 assigned |
| 13 |
Unstructured clustering [Lecture 21 video] [Lecture 22 video] | Aggarwal section 8.1-8.2 Boyd-Vandenberghe chapter 4 |
HW 8 due on 4/22 Project plan due on 4/22 |
| 14 |
Structured classification [Lecture 23 - no video, sorry] [Lecture 24 video] |
Aggarwal section 4.8 [Optional] Boyd-Vandenberghe chapter 14 | [none, work on the project] |
| 15 |
Class presentations + course recap (note: no class on Thursday 5/5) [Lecture 25 - no video, just look at the lecture notes for review] | [None] | PROJECT due 5/2 |
| FINAL EXAM on Tues 5/10 at 12-2pm (emphasis on week 9 onward) |
| Name | Office Hours | |
|---|---|---|
Mayank Varia | When? Where? | |
ekhalaj@bu.edu | When? Where? | |
Allison McDonald | When? Where? |