Data Scholar

Course

Python Foundations

From zero to confident everyday Python, taught through real situations and the bugs they cause: values, collections, functions, the mutation model, errors, and files, all practiced by writing and running code in the browser.

Start course

A from-zero foundation in everyday Python for anyone heading into AI and agent engineering. It is not a syntax tour. Every concept is taught through a small, realistic situation, a billing total, a support ticket, a corrupted conversation transcript, and the bugs that situation creates in real code.

You begin by running your first line and finish able to write clear, correct Python with confidence: values and arithmetic, decisions and loops, the core collections, functions, the names-and-mutation model that prevents an entire class of state bugs, comprehensions, error handling, files and JSON, and small modules. You work in pure standard-library Python and practice in the browser, writing and running real code rather than only reading it.

By the end you can read and write the everyday Python that later work in data, machine learning, and agents takes for granted.

Curriculum

M1Your first Python6 topics
·Module overview
  1. 1.1Running Python and the REPL
  2. 1.2Variables and names
  3. 1.3Numbers and arithmetic
  4. 1.4Strings: indexing and slicing
  5. 1.5String methods and f-strings
  6. 1.6Practice: first values
M2Decisions, None, and loops7 topics
·Module overview
  1. 2.1Booleans and comparisons
  2. 2.2None and missing values
  3. 2.3Truthiness and logic
  4. 2.4if, elif, else
  5. 2.5for loops and range
  6. 2.6while, break, and continue
  7. 2.7Practice: control flow
M3Collections7 topics
·Module overview
  1. 3.1Lists
  2. 3.2Tuples
  3. 3.3Dictionaries: basics
  4. 3.4Working with dicts safely
  5. 3.5Sets
  6. 3.6Choosing the right collection
  7. 3.7Practice: collections
M4Functions6 topics
·Module overview
  1. 4.1Defining and calling functions
  2. 4.2Arguments and default values
  3. 4.3Return values and scope
  4. 4.4Readable functions
  5. 4.5Flexible arguments
  6. 4.6Practice: functions
M5How Python really works5 topics
·Module overview
  1. 5.1Names, objects, and identity
  2. 5.2Mutable versus immutable
  3. 5.3Mutation versus rebinding
  4. 5.4The three traps and the fixes
  5. 5.5Practice: write it, run it
M6Comprehensions and cleaner iteration5 topics
·Module overview
  1. 6.1List comprehensions
  2. 6.2Dict and set comprehensions
  3. 6.3enumerate and zip
  4. 6.4A first look at generators
  5. 6.5Practice: comprehensions
M7Errors, debugging, and checking your work6 topics
·Module overview
  1. 7.1Exceptions and reading tracebacks
  2. 7.2try, except, else, and finally
  3. 7.3Raising and custom exceptions
  4. 7.4Debugging in practice
  5. 7.5Checking your work with assert
  6. 7.6Practice: errors and debugging
M8Files, JSON, and modules5 topics
·Module overview
  1. 8.1Reading and writing files with pathlib
  2. 8.2Context managers (with)
  3. 8.3JSON
  4. 8.4Modules, imports, and the entry point
  5. 8.5Practice: files and JSON