Teaching & Learning
JUMP TO:
Teaching & Learning
All the material for courses are available at official UMT Integrated Learning Management system at the url below. Feel free to login and download the materials. Online teaching are conducted using Cisco Webex. Extra Materials will be uploaded in the section below.
SEMESTER I: Geometric Modelling (MKP4300)
Please login : Oceania for materials.
Create an Wolfram Cloud account for online Mathematica usage: https://www.wolframcloud.com/
Do introductory programming lab at: https://www.wolfram.com/programming-lab/
Read and try coding using this book: https://www.wolfram.com/language/elementary-introduction/2nd-ed/
Examples Mathematica projects: Wolfram Demonstrations Project demonstrations
New: Mathematica Notebooks: https://www.notebookarchive.org/
SEMESTER I: Systematic Thinking and Programming (MTK3704)
Please login : Oceania for materials.
Online C++ compiler: https://www.programiz.com/cpp-programming/online-compiler/
Dev C++ Installer: https://sourceforge.net/projects/orwelldevcpp/
SEMESTER II: Scientific Computation (MKP3303)
Please login : Oceania or my Github for materials.
Wolfram Mathematica for Symbolic and Numerical Computing
Create a Wolfram Cloud account for online Mathematica usage: https://www.wolframcloud.com/
Do introductory programming lab at: https://www.wolfram.com/language/fast-introduction-for-math-students/en/
Read and try coding using this book: https://www.wolfram.com/language/elementary-introduction/2nd-ed/
Examples Mathematica projects: Wolfram Demonstrations Project demonstrations
New: Mathematica Notebooks: https://www.notebookarchive.org/
Python SciPy for Numerical Computing.
Online Python Compiler: https://www.w3schools.com/python/python_compiler.asp
Complete details on SciPy: https://scipy.org/
SciPy reference notes: for the hands-on lab: https://scipy-lectures.org/
Jupyter Notebook Online: https://jupyter.org/try
Google Collab for Python execution with Jupyter notebook: https://colab.research.google.com/notebooks/intro.ipynb
SEMESTER I: Introduction to Data Science (MDA3003)
Please login : Oceania or my Github for materials.
Python SciPy for Numerical Computing.
Online Python Compiler: https://www.w3schools.com/python/python_compiler.asp
Jupyter Notebook Online: https://jupyter.org/try
Google Collab for Python execution with Jupyter notebook: https://colab.research.google.com/notebooks/intro.ipynb
Data Science resources:
Introduction to Data Mining by Pang-ning Tan, Michael Steinbach, Vipin Kumar
Book: Data Science from Scratch First Principles with Python
Github: Data Science from Scratch First Principles with Python
Jesus Rogel-Salazar, Data Science and Analytics with Python, CRC Press, Year: 2017
Jesus Rogel-Salazar, Advanced Data Science and Analytics with Python, CRC Press, Year: 2020
online ML work by Jean de Dieu Nyandwi
SEMESTER I & II: Final Year project (MTK4998)
Undergraduate students carry out one-year project before graduating. Current projects are related to Topological Data Analysis and clustering methods.
WIP
Topological Data Analysis
WIP