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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.

Exam of 10 to 20 questionsCertificate for LinkedInBeginner

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.

  1. 01Installing Python26:23
  2. 02Environments and packages16:28
  3. 03Imports, Jupyter and programming basics23:12
  4. 04Comments, data types and strings24:59
  5. 05Operators and control flow16:09
  6. 06Loops and data structures27:51
  7. 07Parameters and scope13:48
  8. 08Return values and modules19:58
  9. 09requirements.txt and APIs17:32
  10. 10Data with pandas and matplotlib20:17
  11. 11Files, modules, errors and classes intro22:32
  12. 12Your first class16:14
  13. 13Inheritance and Git22:49
  14. 14Repositories and .gitignore15:53
  15. 15Secrets and Ruff31:26
About the course

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.