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Video course · 15 chapters · 316 min · certificate

Python for AI & Data Science: Beginner Course with Projects

Python from zero for AI and data science: installing Python, environments and packages, Jupyter, data types and strings, operators and control flow, loops and data structures, functions and scope, modules, APIs, pandas and matplotlib, files and errors, classes, Git and GitHub, .env secrets and Ruff.

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What you'll learn

  • Install Python and manage environments and packages
  • Use core data types, control flow and data structures
  • Write functions and understand scope
  • Call APIs and analyse data with pandas
  • Write classes and handle errors
  • Use Git, GitHub, .env secrets and a linter

Chapters

15 chapters · 315:31
  1. 26:23 01Setup Members Installing Python Course overview and installing Python on Windows and Mac.
  2. 16:28 02Setup Members Environments and packages Virtual environments, pip and course resources.
  3. 23:12 03Basics Members Imports, Jupyter and programming basics Using packages, interactive Python and what programming is.
  4. 24:59 04Basics Members Comments, data types and strings Comments, numbers, strings, f-strings and string methods.
  5. 16:09 05Control Members Operators and control flow Arithmetic, comparison, logical operators and conditionals.
  6. 27:51 06Structures Members Loops and data structures For loops, range, lists, dicts, tuples, sets and functions.
  7. 13:48 07Functions Members Parameters and scope Function parameters, arguments and variable scope.
  8. 19:58 08Functions Members Return values and modules Returning values, modules, packages and import styles.
  9. 17:32 09APIs Members requirements.txt and APIs Managing dependencies and calling APIs with requests.
  10. 20:17 10Data Members Data with pandas and matplotlib Working with data, files and an intro to projects.
  11. 22:32 11Practice Members Files, modules, errors and classes intro File types, organizing code, try/except and classes.
  12. 16:14 12OOP Members Your first class __init__, self, attributes and methods.
  13. 22:49 13OOP/Git Members Inheritance and Git Class inheritance, classes vs functions, and Git fundamentals.
  14. 15:53 14Git Members Repositories and .gitignore Creating repos and ignoring files.
  15. 31:26 15Tooling Members Secrets and Ruff .env, python-dotenv, and Ruff linter/formatter.

Jobs this course suits

Our AI checked this course against 500 jobs; these get the most out of it. Each job links to its learning path.

BioinformaticiansStatisticiansData AnalystsInsurance Data AnalystsResearch ScientistsAstronomersEpidemiologistsBusiness Intelligence AnalystsComputer Science StudentsData EngineersMarket Research AnalystsPostdoctoral Researchers