PSTAT10 Data Science Fundamentals
Summer 2026
My name is John Inston and I will be the instructor for this course, I am a 5th year Ph.D. candidate in the Department of Statistics and Applied Probability here at UC Santa Barbara. Thank you all for taking this course. I hope that you find it both interesting and informative.
This course introduces students to the fundamentals of programming for data science using R and SQL. We will cover descriptive statistics, distributions, and graphics in R, as well as relational database management systems, including the relational model, relational algebra, database design principles, and data manipulation using SQL.
🔍 Reference Material
The contents of this course was prepared using past teaching material provided by Isaiah Katz and Robin Lui as well as historical course material made available online by the UCSB Department of Statistics and Applied Probability.
📚 Material
- Course Syllabus:
- Lecture Notes:
- Online lecture notes
- Course Readings:
- Helpful Resources:
✏️ Information
Teaching Staff
| Name | Role | Office Hours | |
|---|---|---|---|
| John Inston | Instructor | johninston@ucsb.edu | SH 5431T W 1:00PM - 4:00PM |
| Abhijit Brahme | TA | abhijitbrahme@umail.ucsb.edu | Zoom Meeting R 1:00PM - 3:00PM |
| Siyu Chen | TA | siyu_chen@umail.ucsb.edu | Zoom Meeting T 10:00AM - 11:00AM |
For zoom meeting links please check the course Canvas page.
Instruction
Course instruction will comprise of 20 lectures (held four times per week) and 10 programming labs (held twice per week).
- Lecture:
- MTWR 11:00AM - 12:20PM Theater and Dance West (Room 1701).
- Labs:
- MW 12:30PM - 1:20PM Phelps Hall 1513 - Abhijit Brahme
- MW 2:00PM - 2:50PM Phelps Hall 1513 - Abhijit Brahme
- MW 3:30PM - 4:20PM Phelps Hall 1513 - Siyu Chen
Assessments
You will be required to complete 10 lab worksheets which will be due for submission every Wednesday and Friday (2 days after lab) at midnight on Canvas.
You will be required to complete 5 assignments which will be due for submission every Wednesday at midnight starting in Week 2.
You final assessment will be an in-person final exam which will be held on Thursday of finals week from 11:00AM to 12:20PM in the same location as the lecture, Theater and Dance West (Room 1701).
Course Schedule
Please check this schedule regularly throughout the term as it is updated with the latest material and reading suggestions.
| Week | Lecture | Date | Topics | Materials |
|---|---|---|---|---|
| 1 | 1 | Mon, Aug 3 | Course Introduction, R Basics | Lec01 |
| 2 | Tue, Aug 4 | Vectors | Lec02 | |
| 3 | Wed, Aug 5 | Matrices and Arrays | Lec03 | |
| 4 | Thu, Aug 6 | Functions, Branching and Loops | Lec04 | |
| 2 | 5 | Mon, Aug 10 | Algorithms | Lec05 |
| 6 | Tue, Aug 11 | Dataframes | Lec06 | |
| 7 | Wed, Aug 12 | Tibbles | Lec07 | |
| 8 | Thu, Aug 13 | Plotting | Lec08 | |
| 3 | 9 | Mon, Aug 17 | Probability | Lec09 |
| 10 | Tue, Aug 18 | Discrete Random Variables | Lec10 | |
| 11 | Wed, Aug 19 | Continuous Random Variables | Lec11 | |
| 12 | Thu, Aug 20 | Monte-Carlo Methods | Lec12 |