Certification
Certification in Building AI Models and Data Pipelines with Python
Get certified in Python for AI & Data Science. Build from a blank screen: set up a pro env, call APIs, analyze with pandas, plot in Matplotlib, manage secrets, use Git/GitHub, and ship a real weather analysis app.

The exam
Take the certification exam
Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.
What the exam covers
2 questions from each of the 15 chapters of the course
20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.
- 01Installing Python26:23
- 02Environments and packages16:28
- 03Imports, Jupyter and programming basics23:12
- 04Comments, data types and strings24:59
- 05Operators and control flow16:09
- 06Loops and data structures27:51
- 07Parameters and scope13:48
- 08Return values and modules19:58
- 09requirements.txt and APIs17:32
- 10Data with pandas and matplotlib20:17
- 11Files, modules, errors and classes intro22:32
- 12Your first class16:14
- 13Inheritance and Git22:49
- 14Repositories and .gitignore15:53
- 15Secrets and Ruff31:26
Python for AI & Data Science: Beginner Course with Projects (Video Course) is a hands-on certification that takes you from a blank screen to a working app, step by step. Expect increased productivity, a competitive advantage, improved decision-making, adaptability and growth toward a future-proof career,and even higher income potential. Join today to set up a pro Python environment, learn the essentials, call APIs, analyze with pandas, plot with Matplotlib, manage secrets, and ship a real weather analysis tool with Git and GitHub,no fluff, just progress.
This certification covers the following topics:
- Professional Python setup and isolated virtual environments
- Python essentials: syntax, variables, types, operators, control flow, loops
- Core data structures: lists, dictionaries, tuples, sets
- Functions and object-oriented basics (classes)
- Package management: pip, requirements.txt, and uv
- Working with APIs and JSON workflows
- Data analysis with pandas DataFrames
- Visualization with Matplotlib
- Secrets and configuration with .env and environment variables
- Version control and collaboration with Git and GitHub
- Developer tooling: Jupyter/VS Code Interactive and code quality with Ruff
- End-to-end project: weather data analysis app (fetch, clean, visualize, save)
Jobs this certification suits
Our AI checked this certification against 500 jobs; these get the most out of it. Each job links to its learning path.