Introduction to Python

Much of modern AI relies on Python, this course leads non-coders through exercises to learn enough Python to begin their AI explorations.

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Learning Objectives

1. Navigate within the Jupyter Notebook / Jupyter Lab environment
2. Create a new Python script
3. Create a Jupyter notebook
4. Understand the difference between a Python script and a Jupyter notebook
5. Create Markdown cells in a notebook
6. Create and run Python cells in a notebook
7. Understand the rules which govern Python variable behavior
8. Write simple programs that assign values to variables and perform calculations with those values
9. Correctly trace variable changes in a Python program
10. Explain key differences between integers and floating point numbers
11. Explain key differences between numbers and character strings
12. Explain the purpose of functions
13. Correctly call built-in Python functions
14. Correctly nest calls to built-in functions
15. Use help to display documentation for built-in functions
16. Correctly describe situations in which SyntaxError and NameError occur
17. Explain what software libraries are and why programmers create and use them
18. Write programs that import and use modules from Python’s standard library
19. Find and read documentation for the standard library interactively (in the interpreter) and online
20. Import the Pandas or cudf library
21. Use Pandas or cudf to load a simple CSV data set
22. Get some basic information about a Pandas or cudf DataFrame
23. Select individual values from a dataframe
24. Select entire rows or entire columns from a dataframe
25. Select a subset of both rows and columns from a dataframe in a single operation
26. Select a subset of a dataframe by a single Boolean criterion
27. Select and transform data and then plot it
28. Plot data directly from a dataframe
29. Create a time series plot showing a single data set
30. Create a scatter plot showing relationship between two data sets
31. Explain why programs need collections of values
32. Write programs that create flat lists, index them, slice them, and modify them through assignment and method calls
33. Explain what for loops are normally used for
34. Trace the execution of a simple (unnested) loop and correctly state the values of variables in each iteration
35. Write for loops that use the Accumulator pattern to aggregate values
36. Correctly write programs that use if and else statements and simple Boolean expressions (without logical operators)
37. Trace the execution of unnested conditionals and conditionals inside loops
38. Explain and identify the difference between function definition and function call
39. Write a function that takes a small, fixed number of arguments and produces a single result
40. Provide sound justifications for basic rules of coding style
41. Refactor one-page programs to make them more readable and justify the changes
42. Use Python community coding standards (PEP-8)