Monash University Malaysia

Computational methods for solving first-order differential equations, detailing Python implementation alongside an analysis of accuracy and error scaling. 1. ODE vs PDE 2. Numerical Solvers 3. Error Convergence

Foundational quick-reference guide for utilizing the NumPy library in Python, focusing entirely on array creation, mathematical operations, and data restructuring. 1. Array Creation & Properties 2. Mathematical & Statistical Operations 3. Array Restructuring & Addressing

Comprehensive guide to data categorization and the use of Python (specifically Matplotlib) for data visualization and string formatting. 1. String Formatting 2. Data Classification 3. Types of Graphs 4. Plot Customisation

From basic scripting into functional programming and the critical steps required for data validation and cleaning. 1. Custom Functions 2. Importing & Filtering Data 3. Principles of Data Quality 4. Data Cleaning Technique

Principles of statistical error, summary statistics, and the methodology for fitting both linear and non-linear models to data. 1. Types of Error 2. Summary Statistics 3. Curve Fitting Process 4. Non-Linear Models 5. Polynomial Fitting

Fundamentals of controlling program flow, troubleshooting code, and designing efficient algorithms. 1. For Loops 2. Loop Control 3. Debugging Features 4. Algorithm Principles 5. Nested Loops 6. Computational Complexity

Numerical methods for finding the roots of an equation (the point where a function equals zero), which is essential for optimization (maxima/minima), finding intersections, or identifying when a function reaches a specific value. 1. Bracketing Methods 2. Open Methods 3. Convergence Testing

Computational methods for numerical integration, their Python implementations, constraints on their inputs, and a detailed breakdown of their error scaling. 1. Integration Methods 2. Input Testing & Constraints 3. Error Convergence Concepts

1. Microsoft Excel Basic Functions 2. Spreadsheets vs Scripts 3. Generative AI

Clear, concise, and exam-focused notes covering the fundamentals of neurons and memory. This resource summarises neuron structure and function, explains how neurotransmitters and receptors work, and outlines key mechanisms involved in memory formation such as increasing receptor numbers and synaptic contacts. It also covers important behavioural concepts including innate and learned behaviours, fixed action patterns, stereotyped behaviour, and non-associative learning, making it ideal for quick ...

These are my handwritten university notes on stereochemistry, covering key concepts such as chirality, enantiomers, diastereomers, and optical activity. The notes include clear explanations, labeled diagrams, and step-by-step methods for assigning R/S configurations and identifying different types of isomers. They are designed to simplify complex topics and help with quick revision.

This document provides a detailed summary of Week 6 lecture notes on additive manufacturing and material deformation. It covers key concepts such as FDM 3D printing with thermoplastics, the importance of fibre orientation and voids, and the mechanics of work hardening in metals. Also included are explanations of dislocation behaviour, plastic deformation, and effects of annealing.

Handwritten notes for Week 09 Semiconductors

Handwritten notes for Week 10: Extrinsic Semiconductors

Handwritten notes for Week 6 - Advanced Circuit Analysis Pre-Reading

Handwritten notes for Week 07 -Diodes, LEDs and Simple Model Analysis

Hadnwritten notes for Week 11 Frames and Machines II

Handwritten notes for Week 10 Frames and Machines

Handwritten notes for Week 07 - Axial Member Design

This document summarizes Week 5 lecture content focused on stress-strain relationships, types of deformation, and material toughness. Topics include Hooke’s Law, yield stress, ultimate tensile strength, and the distinction between engineering and true stress. Additional notes explain the role of dislocations in deformation and the impact of bonding types on material properties.