Teaching

Week 1: Introduction (notes)

• 1. Assignment Week 1: Exploring Basic Data Types in Python using Google Colab (pdf)

Week 2: Arrays & Matrices (notes)

• 1. Worksheet Week 2: Understanding the array Module in Python (pdf) 

  2. Assignment Week 2: Exploring Matrix Operations with NumPy (pdf)

Week 3: Linked Lists & Doubly Linked Lists (notes)

• 1. Week 3 Exercises Part 1 (pdf)

  2. Week 3 Exercises Part 2 (pdf)

  3. Assignment Week 3: Write a function to reverse a linked list (NOT Doubly Linked Lists)

Week 4: Stacks (notes)

• 1. Worksheet Week 4 (pdf)

  2. Assignment Week 4 (pdf)

Week 1: Introduction (notes)

Week 2: Literature Review and Critical Evaluation in ICT Research (notes)

• Week 2 Assignment (pdf)

• Research Proposal Template (Three Chapters) for ICT 402 Research Methodology in Information and Communication Technology (Docx)

Week 3: Constructing the Introduction Chapter: Background of the Study (notes)

Week 4: Constructing the Introduction Chapter: Problem Statement (notes)

Weeks 5 and 6: Constructing the Introduction Chapter: Research Objectives and Questions (notes)

Weeks 9-10-11: Constructing the Introduction Chapter: Scope & Significance of the Study & Theoretical Level of Your Study (notes)

• With a little help with Linear Regression in Python (CoLab)

Weeks 12-13: Writing ICT Research Papers (notes)

Week 14: Ethical Principles in ICT Research (notes)

Week 15: Students need to focus on the final project

Week 16: Students need to prepare their final thesis, paper, and presentation for submission and discussion on the webinar (Final Thesis and Paper Submission)

Week 1: Introduction (notes)

Week 2: Ethical Considerations (notes)

Week 3: Metaheuristic (notes)

Week 4: Machine Learning Fundamentals (notes)

Week 5: Neural Networks and Deep Learning (notes)

Week 6: Cognitive Modeling (notes)

Week 7: Social Dynamics Analysis (notes)

• • Final Project Description for Data Science Course (pdf)

Week 9: Data Visualization (notes)

Week 10: Computational Neuroscience (notes)

Week 11: Following up on the final project in data science

Weeks 13-14: Following up on the simulation and results of final project

Week 15: Final Report and Presentation Guidelines (pdf)

Week 16: Final report, presentation, and submission (Report Submission)