Module 6 Objective Mapping

Thomas J. Kennedy

Contents:
1 Module Objectives
2 Lectures & Objectives
3 Course Level Objectives

1 Module Objectives

You will notice quite a few mappings of Module 6 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 Compare Python lists to a the Java List and C++ std::vector. ✓ ✓ ✓ ✓
2 Utilize the list slice syntax. ✓
3 Utilize List Comprehensions and generator expressions. ✓ ✓ ✓
4 Compare lists and tuples in the context of mutability. ✓
5 Make use of built-in functions such as sum, min, and max to perform aggregate operations on collections. ✓ ✓
6 Make use of the built-in sort function. ✓ ✓
7 Make use of the built-in sort function with a provided key argument. ✓ ✓ ✓
8 Describe when a dictionary is appropriate over a list. ✓ ✓ ✓

2 Lectures & Objectives

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

Lecture 1 2 3 4 5 6 7 8
Module 6 Objective Mapping
The Basic Python Data Structures ✓ ✓ ✓
Comprehensions - An Overview ✓
Working with Python’s list ✓ ✓ ✓
Module 6 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).
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