Unit Review & Final Exam Guide

Aggregate Mark Formula

aggregate_mark =
    moderated_weekly_labs(%)  * 0.25
  + moderated_assignment(%)   * 0.25
  + moderated_final_exam(%)   * 0.50

All marks are moderated first (to iron out marker differences) before computing the aggregate.

Supplementary Assessment

If you score 45–49%, you get a second chance (supplementary exam or assignment). The style, scope, and difficulty is the same as the final exam. If you pass the supplementary, you pass the unit. If you fail, you fail the unit.

Recommended Study Steps

1. Read the lecture notes, topic by topic.
2. Try the code examples from the slides — type them yourself, don't copy-paste. Better: read until you understand, then write from memory.
3. Review all lab exercises. Complete any you didn't finish. Exam questions often resemble lab exercises.
4. Review your assignment.
5. Try the sample exam paper (available on LMS) — it's similar in style, scope, and difficulty.
6. Increase understanding by proposing a hypothesis and testing it by modifying a program.

If You Forget a Function's Exact Syntax

Don't panic! If you can't remember the exact syntax of a function or method, you may write your own notation and explain what it does and what each parameter means. Then use that notation in your answer.

Examiners award marks for demonstrating understanding of what you're doing, not just the exact spelling of a function name.

For Theory Questions — Length of Answer

Look at the marks allocated and the space provided — then decide how much to write. Examiners look for how many critical points you cover and the quality of your answer, not the length.

Topic 1 — Introduction to Python

Algorithms vs programs, Python basics, variables, data types (int, float, str, bool, None), print(), input(), type().

Topic 2 — Expressions, Variables & Types

Arithmetic operators (+, -, *, /, //, %, **), operator precedence, type conversion, string concatenation and repetition.

Topic 3 — Control Flow: Conditions

if, elif, else; comparison operators (==, !=, <, >, <=, >=); logical operators (and, or, not); nested if statements.

Topic 4 — Control Flow: Loops

while and for loops, range(stop/start,stop/start,stop,step), break, continue, nested loops, accumulator pattern.

Topic 5 — Data Structures

Lists (ordered, mutable), tuples (ordered, immutable), sets (unique elements), dictionaries (key-value). Methods, slicing, iteration.

Topic 6 — Functions & Modules

def, parameters, return, default args, scope (local/global), lambda, import, math and random modules, creating modules.

Topic 7 — Files & String Processing

open() with modes r/w/a, with statement, read/readline/readlines, write. String methods, f-strings, string indexing/slicing.

Topic 8 — Testing, Debugging & Exceptions

3 error types (syntax, runtime, logic), try-except-else-finally, common exceptions, raise, assert, defensive programming, debugging tips.

Topic 9 — Object-Oriented Programming

OOP vs procedural, encapsulation/inheritance/polymorphism, class definition, __init__, self, class vs instance variables, @classmethod.

Topic 10 — NumPy & Ndarrays

NumPy install/import, ndarray vs list (50× speed), array(), zeros(), ones(), arange(), linspace(), ndim/shape/size/dtype, indexing, slicing, copy vs view, element-wise ops, ufuncs, matrix mult (@).

Topic 11 — Data Visualisation with Matplotlib

pyplot import, figure vs axes, subplot(), plot() with format strings, title/xlabel/ylabel/xlim/ylim/legend/show, scatter, histogram, bar chart, pie chart.