Training guide
UC San Diego Python for Data Science on edX: Course Guide
A plain guide to Python for Data Science from the University of California, San Diego (UC San Diego), on edX.
EU Job Hub Editorial Team · Updated 1 October 2026 · Based on the UC San Diego course syllabus and edX course listings
Introduction
UC San Diego Python for Data Science is the first course in the Data Science MicroMasters on edX. The old page called it a “Purdue” course for beginners. Both points are wrong. The university is UC San Diego, and the listings describe the course as advanced.
It lasts 10 weeks and uses Jupyter notebooks, Pandas, NumPy, Matplotlib and Git. The final weeks are an end-to-end project.
This guide explains who it suits, what it covers and how to prepare.
Quick Information
| Institution | University of California, San Diego, on edX |
| Length | 10 weeks |
| Effort | 8 to 10 hours a week, per the syllabus |
| Level | Advanced in most listings; not an introduction to Python |
| Pass mark | 70 per cent, per the syllabus |
| Part of | Data Science MicroMasters |
Key Points at a Glance
- The university is UC San Diego, not Purdue.
- The syllabus expects 8 to 10 hours a week for 10 weeks.
- You need a score of 70 per cent or more to pass.
- Tools include Python, Jupyter, Pandas, NumPy, Matplotlib and Git.
- Weeks 9 and 10 are a final project.
Correcting the Details
The course comes from UC San Diego. Purdue has no part in it.
The old page said it was for beginners. Listings call it advanced, and one says plainly that it is not an introductory course.
Correct details matter on your CV. They show that you read the source.
Who It Suits
It suits people who already know some programming and want to learn data tools. A week 2 in the syllabus gives an optional Python refresher.
Complete beginners may struggle. Learn basic Python first with a gentler course.
If you can write a function and a loop, you are ready.
What the Syllabus Covers
Week 1 introduces the data science process. Week 2 is the optional Python background. Week 3 covers Jupyter and NumPy.
Later weeks teach data wrangling, visualisation, basic statistics and an introduction to machine learning, according to the course description.
Weeks 9 and 10 are the final project. You choose a dataset, clean the data, ask questions, visualise results and present conclusions.
Time and Effort
The syllabus expects 8 to 10 hours a week. One reviewer reported about 70 hours in total, with much time on the projects.
Third-party listings give slightly different weekly figures, so plan for the higher end.
Set aside time for peer review. Projects are reviewed by other learners.
Grading and Pace
The syllabus says you must score 70 per cent or above to pass.
The course is self-paced in the syllabus version available, with no deadlines for single assignments.
edX sessions change, so check whether your session is instructor-paced.
Audit and Certificate
Listings describe a free audit track and a paid verified track. One third-party site shows a verified price, but prices change.
Check edX for the current price and whether the course is open for enrolment.
Decide whether you need the certificate before you pay.
Practice Ideas
Download a public dataset about your city, such as bike trips or air quality. Load it in a notebook.
Write three questions the data could answer. Build one chart for each.
Put the notebook on GitHub with a short explanation.
Preparing Before Week One
Install Python and Jupyter on your computer, or choose a hosted notebook. Run a short test.
Refresh basic Python, such as lists, dictionaries and functions. Do a few small exercises.
Read a short guide on Git. Make one repository and one commit before the course starts.
Planning the Final Project
Choose a topic you care about. You will spend many hours with the data.
Check that the dataset is public and has enough rows to analyse. Note the licence.
Write your questions first. Then clean the data and build your charts.
Questions to Ask Before You Enrol
Can I write a loop and a function without help?
Can I give about ten hours a week for ten weeks?
Do I need the verified track, or is audit access enough?
Using It in Europe
Roles include junior data analyst, research assistant and BI trainee.
Add the course to your Europass CV, naming UC San Diego and the year.
The course does not give a right to work. Check national rules if you need a visa.
Frequently Asked Questions
Who runs the course?
The University of California, San Diego, on edX.
Is it for beginners?
No. Most listings call it advanced.
How long is it?
Ten weeks, with 8 to 10 hours a week in the syllabus.
What is the pass mark?
70 per cent, according to the syllabus.
Is it free?
The audit track is free in listings. The verified track is paid.
Find Jobs
Titles to search for include junior data analyst, research assistant and BI trainee. Search current vacancies on the EURES portal.
Official Course Page
Read the current details on the edX Python for Data Science page.
Disclaimer
This guide is independent and is not affiliated with the course provider. Prices, course lists and exam rules change, so check the official page before you enrol. A certificate does not give you the right to work in any country.