Teaching

Undergraduate:

Distributed Network Systems & Internet-of-Things 🔥 (Syllabus) 2/2025

1. - Week 1: Introduction to Distributed Network Systems & Internet-of-Things (notes)
  - Week 2: IoT System Architecture and Distributed Models (notes)
  - Week 3: Communication Models in Distributed IoT Systems (notes)
  - Week 4: IoT Protocol Stacks and Web-Based Communication (notes)
  - Week 5: Security and Privacy in Distributed IoT Systems (notes)
  - Week 6: Self-Study Assignment: Time, Coordination and Reliability in IoT Systems (pdf) (submission)
  - Week 7: Transactions, Fault Tolerance, and Replication (notes)
    - - IoT Workshops Guideline (pdf)

Week 9: Midterm exam
Week 10: IoT Workshop 1 (NodeMCU GPIO Control with LED and Push Button)
Week 11: IoT Workshop 2 (Temperature and Humidity Monitoring using DHT11)
Week 12: IoT Workshop 3 (Smart Lighting System using LDR Sensor)
Week 13: IoT Workshop 4 (Distance Measurement using Ultrasonic Sensor)
Week 14: IoT Workshop 5 (Smart Environment Monitoring System)

Implementation of Information System (Syllabus) 2/2025

1. - Week 1: Introduction (notes)
  - Week 2: Information System Planning (notes)
    - - Week 2 Assignment: ISP Process and Approach Report (pdf) (submission)
  - Week 3: Analysis (notes)
    - - Week 3: Assignment (pdf) (submission)
  - Week 4: Information System Design (notes)
    - - Week 4: Information System Design Report Assignment (submission)
  - Week 5: Development (notes)
  - Week 6: Testing (notes)
  - Week 7: System Deployment (notes)
  - Week 9: Maintenance Troubleshooting (notes)
  - Week 10: Usability Evaluation (notes)
    - - Week 10 Assignment (pdf)

Week 11: Project Management Information System (Part 1) (notes)

Data Science (Syllabus) 2/2025

1. - Week 1: Introduction (notes) (Materials)
  - Week 2: Ethical Considerations (notes) (Materials)
  - Week 3: Foundations of Statistics for Data Science (notes) (Materials)
  - Week 4: Applied Statistics for Data Science Using Python (notes) (Materials)
  - Week 5: Machine Learning Fundamentals (notes) (Materials)
  - Week 6: Metaheuristic Algorithms (notes) (Materials)
  - Week 7: Neural Networks and Deep Learning (notes) (Materials)
  - Week 9: Cognitive Modeling (notes) (Materials)
  - Week 10: Social Dynamics Analysis (notes) (Materials)
    - - Final Project Description for Data Science Course (pdf)
      - Final Report and Presentation Guidelines (pdf)
      - Little help with Deep Learning code (Colab)

Data Structure and Algorithm (Syllabus) 1/2025

1. - 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 5: Queues (notes)
    - 1. Assignment Week 5 (pdf)

Week 6: Binary Tree (notes)
Week 7: Binary Heap (notes)
Week 9: midterms exam
Week 10: Graph (notes)
Week 11: Search Algorithm (notes)
Week 12: Sorting Algorithms (notes)
Week 13: Divide and Conquer (Recursive) (notes)
Week 14: Dynamic Programming (notes)

Intelligent Systems (ICT 338) (Syllabus) 1/2025

Week 1: Introduction and Select a Business Case (notes)
Week 2: Rule-Based Systems & Fuzzy Logic (notes)
Week 3: Case-Based Reasoning (CBR) for Customer Behavior & Ethics (notes)
Week 4: ABMS for Customer Behavior – Part 1 (notes)
Week 5: ABMS for Customer Behavior – Part 2 (notes)
Week 6: Deep Learning with ABMS – Part 1 (notes)
- - Little help with Deep Learning code (Colab)

Week 7: Deep Learning with ABMS – Part 2 (notes)
Week 9: midterms exam
Week 10: Building Flask-RESTful APIs for Customers – Part 1 (notes)
- - Little help with Flask-RESTful APIs code (Colab)
  - Flask RESTful API Usage Guide (pdf)
Week 11: Building Flask-RESTful APIs for Customers – Part 2 - Database Integration & Firebase Deployment (notes)
Week 12: Flask APIs for Customer Dashboards (notes)
Week 13: Flask APIs for Customer IoT (notes)
Week 14: Flask APIs for Customer Automation (notes)
Intelligent Systems Final Project Submission (URL)

Research Methodology (Syllabus) S/2025

1. - 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)

Digital Media Literacy (Syllabus) S/2023
Information Technology Engagement in Community (Syllabus) 1/2023

Postgraduate: (Soon)

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