Syllabus

• Week 1

  Python Setup & Fundamental Syntax

  • Start Coding with Python

    Meet the course structure, set up professional development tools, and run your first Python program while learning how comments make code easier to understand.

  • Working with Values in Python

    Explore variables, common data types, type conversion, assignment, arithmetic, comparisons, and Boolean logic, then apply them in practical coding activities.

  • Building and Formatting Text

    Work with Python strings through concatenation, indexing, slicing, membership checks, escape characters, common methods, and formatted string literals.

  • Organising Data with Lists

    Create and modify Python lists, access individual items, apply common list operations, and use nested lists to represent structured collections of data.

• Week 2

  Control Flow, Logic & Meeting NumPy

  • Controlling Program Flow

    Use Boolean expressions and conditional statements to make programs respond to different situations, and practise writing clear branches with correct indentation.

  • Repeating Work Efficiently

    Automate repeated actions with for and while loops, build list comprehensions, control execution with break and continue, and avoid infinite loops.

  • Designing Reusable Functions

    Define and call functions, work with parameters and return values, document behaviour, use flexible arguments, and explore the principles of recursion.

  • Structuring Code and Introducing NumPy

    Organise Python code with modules and imports, distinguish imported code from executable scripts, and discover why NumPy is useful for numerical data.

• Week 3

  From Lists to Arrays & Advanced Manipulation

  • Creating NumPy Arrays

    Move from Python lists to NumPy arrays, explore ndarray properties and data types, and create arrays from lists, empty structures, ranges, and evenly spaced values.

  • Reshaping Data and Broadcasting

    Use tuples to describe dimensions, change array shapes, transpose data, and understand how broadcasting makes operations between compatible arrays possible.

  • Selecting Data from Arrays

    Access and filter NumPy data with indexes, integer arrays, slices, comparisons, and Boolean masks while tracking how each selection affects the result.

  • Reordering and Combining Arrays

    Sort and partially sort values, generate and shuffle samples, join arrays by concatenating or stacking them, and divide arrays into smaller sections.

• Week 4

  OOP, File Systems & Vectorised Math

  • Modelling Programs with Objects

    Create classes and instances, work with attributes and methods, use constructors and representations, distinguish class and instance variables, and organise code in packages.

  • Reading, Writing, and Exploring Data

    Read and write files with Python, load and save data with NumPy, handle real datasets, and search arrays to locate values and identify maximums.

  • Mapping and Counting Data

    Use dictionaries to organise key-value data, add and retrieve entries, inspect keys and values, and apply NumPy tools to find unique values and frequency counts.

  • Processing Text with Python and NumPy

    Join and transform Python strings, distinguish text from bytes, and apply NumPy string operations across arrays for case changes, checks, encoding, and translation.

  • Fast Array Calculations

    Apply vectorised mathematical operations and reductions to NumPy arrays, then use dot products and matrix multiplication to perform essential linear algebra calculations.

  • Review and Next Steps

    Consolidate the course’s Python and NumPy concepts with a final knowledge check, reflect on the practical skills developed, and identify useful directions for further study.