Module 3 Objective Mapping

Thomas J. Kennedy

Contents:

1 Module Objectives

You will notice quite a few mappings of Module 3 objectives (row) to Course Objectives (column).

# Module Objective 1 2 3 4 5 6.A 6.B 7.A 7.B 8 9 10 11 12 13 14 15
1 Make use of variables to represent simple types (i.e., int, float, char, and bool).
2 Make use of variables to store strings.
3 Write functions that accept zero or more arguments.
4 Write functions that return zero values.
5 Write functions that return one value.
6 Write functions that return multiple values.
7 Make use of modules to organize functions.
8 Document functions with Type Hints & pydoc.

2 Lectures & Objectives

The following table shows lectures (rows) vs Module Level Objectives (columns).

Lecture 1 2 3 4 5 6 7 8
Module 3 Objective Mapping
Basic Data Types & Variables
Basics of Functions
Functions & Modules
Code Documentation & Type Hints
Module 3 Summary

3 Course Level Objectives

The course objectives are listed in section 2.4 of the syllabus and reproduced in this document for reference.

A student who successfully completes this course will be able to (in Python):

  1. Run a program consisting of a single file and containing a main function.
  2. Run a program consisting of multiple modules and containing a main function.
  3. Organize code into multiple modules.
  4. Write tests for a module.
  5. Apply the basics of test-driven development through PyTest and/or unittest.
  6. Make use of the various loops (for and while)
    1. Compare the various loops (for and while)
    2. Choose the most appropriate loop (for or while) for a given problem
  7. Make use of the conditional blocks (i.e., if, if-else, and if-else-if-else).
    1. Compare the various conditional blocks (i.e., if, if-else, and if-else-if-else)
    2. Construct the appropriate conditional block (i.e., if, if-else, and if-else-if-else) for a given problem.
  8. Test and write functions.
  9. Design ADTs in accordance with the Class Checklist.
  10. Discuss when polymorphism is appropriate.
  11. Discuss when it is appropriate to utilize dataclasses, classes, and enums.
  12. Write code that utilizes dunder functions.
  13. Refactor code to follow best practices (e.g., PEP 8 and PEP 20).
  14. Apply code linting tools (e.g., pylint and black) to write idiomatic (Pythonic) code.
  15. Discuss the various NumPy np.array mechanics (e.g., broadcasting).