Applied Data Science with Python Specialization
About this course
Michigan's Applied Data Science with Python Specialization is the most tool-focused data science path on Coursera — five courses that go deep into practical Python data science rather than conceptual foundations. Course 1 covers pandas and Python for data manipulation; course 2 covers matplotlib and visualization; course 3 covers scikit-learn for applied machine learning; course 4 covers text analysis and NLP with Python; course 5 covers social network analysis with NetworkX. Every course uses real datasets and emphasizes applied skill.
The specialization fills a specific niche: practitioners who want deep, hands-on Python data science skills taught with real datasets rather than toy examples. The NLP and network analysis courses are rarely found in beginner-level certificates, making this an unusually comprehensive applied Python DS credential.
What you'll learn
This course includes
Compare alternatives for Applied Data Science with Python Specialization
- Price
- PaidSubscription-based, free to audit
- Duration
- 200 hrs
- Level
- Intermediate
- Certificate
- Specialization Certificate
- Price
- FreeCompletely free, openly licensed — no certificate
- Duration
- 34 hrs
- Level
- Intermediate
- Certificate
- Price
- FreeFree lecture materials; some versions paid
- Duration
- 50 hrs
- Level
- Advanced
- Certificate
- Price
- FreeFree lecture materials; some versions paid
- Duration
- 50 hrs
- Level
- Advanced
- Certificate
Instructor
Taught by Christopher Brooks and Kevyn Collins-Thompson, University of Michigan School of Information faculty specializing in applied data science and information retrieval.
Requirements
- Python programming fundamentals; basic statistics helpful
Who this course is for
- Python practitioners who want structured applied data science skills
- Analysts who want to graduate from Excel and BI tools to Python
- Data scientists who want NLP and network analysis beyond the standard ML curriculum