Course Map

This map shows how the notebooks fit together. It is useful for instructors, students who want a big-picture view, and anyone reviewing the course structure.

The course includes a getting-started notebook followed by Modules 1-12.

Module Map

Module #	Module Name	Notebook File	Key Concepts	Skills Developed
0	Getting Started	notebooks/00_getting_started.ipynb	Notebook workflow, running cells, checking output	Open notebooks, run code, build confidence
1	Python in the Real World	notebooks/01_python_in_the_real_world.ipynb	What Python is, practical uses, simple examples	Connect Python to real-world IT tasks
2	Variables, Output, and Errors	notebooks/02_variables_output_errors.ipynb	Variables, print(), basic error awareness	Store values, display output, notice simple mistakes
3	Input and Type Behavior	notebooks/03_input_and_type_behavior.ipynb	input(), strings, numbers, type conversion	Collect user input and prepare values for calculations
4	Arithmetic and Comparison	notebooks/04_arithmetic_and_comparison.ipynb	Math operators, comparison operators, order of operations	Calculate totals, compare values, check results
5	Decision Making	notebooks/05_decision_making.ipynb	if, if-else, decision rules	Write programs that choose different actions
6	Multi-Condition Logic	notebooks/06_multi_condition_logic.ipynb	Multiple conditions, and, or	Build simple rules with more than one condition
7	Loops	notebooks/07_loops.ipynb	Repetition, for loops, range()	Repeat actions and trace loop output
8	Lists as Data	notebooks/08_lists_as_data.ipynb	Lists, indexing, processing several values	Store related data and process it with loops
9	Functions	notebooks/09_functions.ipynb	Function definitions, calling functions, reusable steps	Organize repeated logic into simple functions
10	Debugging and Validation	notebooks/10_debugging_and_validation.ipynb	Error messages, testing, validation	Find mistakes, test changes, improve reliability
11	Python Tools and Applications	notebooks/11_python_tools_and_applications.ipynb	Light exposure to dictionaries, libraries, and next steps	Recognize additional Python capabilities without a mastery expectation
12	Guided Mini Project	notebooks/12_guided_mini_project.ipynb	Program workflow, integration, testing, reflection	Build and explain a small complete program

Optional Teaching Supports

Before continuing to Module 7, an instructor may replace Module 6's end reflection with the mid-course check-in, retaining its real-world logic question. The peer exchange or solo equivalent can replace the Comparing AND vs OR practice segment. Stretch prompts are optional after the named lesson; they add no learning objectives or full-credit requirements. See the instructor guide for time budgeting and substitution details.

OER Outcome Mapping

The author-written OER learning outcomes are the shared reference. This map describes the materials, not alignment certified by a university. Module objectives are unchanged.

OER outcome	Supporting modules	Existing evidence of learning
1. Read and predict	0–10	Predict-before-running prompts, output explanations, and tracing examples
2. Build small programs	2–8, 12	Guided changes, mini labs, and the small project
3. Organize repeated tasks	9	Define and call a simple function with a parameter
4. Test and explain changes	2–10, 12	Intentional-error practice, testing, and the project Fix Log
5. Apply and reflect	1, 4–10, 12	Real-world connections, reflections, and project explanation

Module 11 offers light exposure rather than additional mastery requirements. Functions are practiced in Module 9; this map does not add a function requirement to the final project. Adopters supply their own institutional alignment separately.

Progression Summary

The course moves from basic notebook use to practical program building:

1. Start by running notebooks and reading output.
2. Store information with variables.
3. Get input and handle basic type behavior.
4. Calculate and compare values.
5. Make decisions with conditions.
6. Repeat actions with loops.
7. Store and process multiple values with lists.
8. Organize code with simple functions.
9. Debug, test, and validate work.
10. Combine course skills in a guided mini project.

The final goal is not advanced programming. The goal is for students to read, run, modify, test, and explain small Python programs with confidence.