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EMT302 MATHEMATICAL MODELING IN ENGINEERING
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A First Course in Mathematical Modelling (Fifth Edition) : Frank R. Giordano, William P. Fox, Steven B. Horton
Artificial Intelligence: A Modern Approach (Stuart J. Russell and Peter Norvig)
The Elements of Statistical Learning Data Mining, Inference, and Prediction (Trevor Hastie, Robert Tibshirani, Jerome Friedman)
Lattice Boltzmann Method (AA Mohamad) Book
22 March - 28 March
Lecturer 1 - Webex
Lecture 1 - Intro to EMT 302
Lecture 2 - Mathematical Modelling Types
Lecture 3 - Solution to Dynamics System and Systems of Difference Equations
Lecture 2 - Webex
29 March - 4 April
Lecture 4 - The Modeling Process
Lecture 3
Lecture 4
Lecture 5 - Model Fitting
Lecture 5
5 April - 11 April
Class cancellation (Thursday 8/4/2021)
12 April - 18 April
Lecture 6
Lecture 6 - Experiment Modelling_part1
Lecture 6 - Experiment Modelling_part2
Lecture 7 - Recorded
19 April - 25 April
Lecture 7 - Optimization of Discrete Model
Lecture note 8
Lecture 8 - Webex
26 April - 2 May
Lecture note 9 - Intro to ML
Lecture 9 - Intro to ML (Webex) _Replacement Class
Lecture Note 10 - Intro to ML Dataset, Linear Prediction and KNN
Lecture 10 - Intro to ML Dataset (Webex)_Lecture 29/4/2021
Handwritten notes for Lecture 10
3 May - 9 May
Lecture note 11 - Perceptron
Handwritten Note ML3
Lecture 11 - Perceptron (Webex)
Class cancellation (6/5/2021) and replaced with Test 1 (10/5/2021)
10 May - 16 May
EMT 302 Test (Google Form Link)
EMT 302 Test 1
17 May - 23 May
Lecture Note 12 - Principal Component Analysis
PCA - Spreadsheet example of PCA calculation File
Lecture 12 - Principal Component Analysis (Webex)
Lecture 13 - Decision Tree
Information Calculation - Decision Tree
Lecture 13 - Decision Tree (Webex)
Assignment to be uploaded
24 May - 30 May
Lecture 14: Introduction to Bagging, Random Forest and Adaboost
Lecture 14: Introduction to Bagging, Random Forest and Adaboost
Preparation for Machine Learning laboratory
ML Programming Lab 1
Submit Programming Lab 1 here
Machine Learning Lab 1 Recordings
31 May - 6 June
Lecture 15 - Introduction to Naive Bayes
Lecture 15: Intro to Naive Bayes (Webex)
Frequency Table_Naive Bayes
ML Programming Lab 2
Webex Link for the lab today
Upload ML Lab 2 here
Lecture 16 - Introduction to Particle Methods (Webex)
Lecture 16 - Introduction to Particle Methods
Machine Learning Project (delayed due to MCO)
7 June - 13 June
Lecture 17: Lattice Gas Automata
Lecture 17: Introduction to LBM formulation
Lecture 17: Introduction to LGA and LBM (Webex)
Lecture 18: LBM Transport Equation (Part 1)
Lecture 18 - LBM Transport Equation Part 1 (Webex)
Lecture 19 - LBM Transport Equation (Part 2)
Lecture 19 - LBM Transport Equation Part 2 (Webex)
14 June - 20 June
Lecture 20 - Introduction to SPH
Lecture 20: Introduction to SPH (Webex)
Lecture 21: Construction of SPH Smoothing Function
Lecture 21: Construction of SPH Smoothing Function (Webex)
Project briefing Monday 21/6/2021 (4 - 5pm)
21 June - 27 June
Project briefing
Project briefing (Webex)
Project grouping
Group project
LBM code (Project part 1)
5 July - 11 July
Submission of final project
Specific Instruction for EMT302 Final Exam
Integrity Declaration Form (EMT302)
Webex link for EMT 302 Final Exam at 2pm
Final Exam EMT 302
12 July - 18 July
EMT302 Marks for Report and Test
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EMT302 MATHEMATICAL MODELING IN ENGINEERING
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ENGINEERING
SCHOOL OF MECHANICAL ENGINEERING
Semester II
EMT302 MATHEMATICAL MODELING IN ENGINEERING
Summary
EMT302 MATHEMATICAL MODELING IN ENGINEERING
Lecturer:
DR. ING. MUHAMMAD RAZI BIN ABDUL RAHMAN
Lecturer:
PROFESOR DR. MOHAMAD AIZAT BIN ABAS
Skill Level
:
Beginner