Introduction to Computing Science and Programming

1. Introduction to computers and programming

• Hardware and software
• Programming languages, compilers and interpreters
• Programming errors and code debugging
• Integrated development environment
• Representation of data in memory, text encoding and number systems, such as binary, octal and hexadecimal

2. Input, processing and output

• Introduction to pseudocode and flowcharts
• Variables, literals and named constants
• Receiving input and formatting output
• Arithmetic operators and data conversion functions
• Type casting
• Comments and documentation

3. Decision Structures and Boolean logic

• Boolean expressions, relational and logical operators
• If statements
• If-else statements
• If-else if-else statements
• Nested decision structures

4. Repetition Structures

• Condition and count controlled loops
• Sentinels and validation loops
• Infinite loops with break and continue
• Nested loops

5. Procedural programming and functions

• Problem decomposition to support code modularization
• Defining and calling functions
• Passing values to functions
• Scope of variables
• Void and value returning functions
• Use of functions to create reusable code and design programs
• Writing modules
• Standard library functions
• The components of a recursive function

6. Lists & Tuples

• Indexing, accessing and iterating by index vs by element
• Mutable vs immutable types, such as lists and tuples
• Methods and useful built-in operators
• Two-dimensional lists
• Ordering, copying, comparing and slicing lists

7. Strings

• Basic string operations
• String slicing
• Testing, searching and manipulating strings

8. Files

• Sequential file access to a text file
• Reading, writing and appending data from/to a text file
• Records to store complex data
• Processing and creating formatted data files, such as CSV

9. Exceptions

• Raising exceptions
• Re-raising exceptions
• Handling exceptions
• Program control transfer when exceptions occur in a function

10. Complex representations of data

• Creating dictionaries
• Processing dictionaries
• Dictionary methods

11. Fundamental algorithms and introduction to efficiency analysis

• Sorting algorithms, such as selection and bubble sort
• Searching algorithms, such as linear and binary search
• Overview of program efficiency metrics, such as step counting and benchmarking
• Complexity of searching and sorting algorithms