I'm a Lecturer at Universiti Teknologi Malaysia (UTM) passionate about education and fostering a love for software development.

Explore my projects below, and let's collaborate on something impactful! 😊

• 🆕 Research Design and Analysis in Data Science: This course will cover the fundamental steps and implementation on developing the initial ideas to formal academic writing accordingly.

• 🆕 Software Project Management: This course is designed to provide students with in depth knowledge on software project planning, cost estimation and scheduling, project management tools, factors influencing productivity and success, productivity metrics, analysis of options and risks, software process improvement, software contracts and intelectual property and approaches to maintenance and long term software development.

• 🆕 Advanced Computer System & Architecture: This course focuses on advanced topics in the design and analysis of computer architectures. Topics covered include instruction set design, pipelining, instruction- level parallelism, high-speed memory systems, storage systems, interconnection networks, and multiprocessor architectures.

• 🆕 Special Topic in Software Engineering: This course presents a top-down view of cloud computing, from applications and administration to programming and infrastructure. Its main focus is on parallel programming techniques for cloud computing and large scale distributed systems which form the cloud infrastructure.

• Big Data Management: Focuses on the principles and practices of managing large and complex datasets.

• High Performance Data Processing: Covers techniques and tools for processing data at high speeds for performance-critical applications.

• Special Topic in Data Engineering: An advanced course discussing specialized topics within the realm of data engineering.

• Software Engineering (WBL): A work-based learning approach to software engineering, integrating practical experience with theoretical knowledge.

• Web Programming - PHP: Teaches web development using PHP, covering both basic and advanced concepts.

• Programming Technique III: ASP.NET: A course on ASP.NET, focusing on building robust web applications using this framework.

• Extra-Curricular Experiential Learning: Provides opportunities for students to engage in learning experiences outside of the traditional academic curriculum.

• Value and Identity: Explores the concepts of personal values and identity within the context of societal norms and expectations.

• Obsidian vault for Systematic Literature Reviews in Computer Science: A curated collection of resources for conducting systematic literature reviews with a focus on computer science.

• Obsidian.md for Academic Writing: A guide to using Obsidian.md, a markdown-based knowledge base that works on top of a local folder of plain text Markdown files.

• Python for beginners: A beginner-friendly repository that provides tutorials and resources for learning Python programming.

• Web Scraping: This repository offers guidance and code examples for web scraping using Python.

• Exploratory Data Analysis (EDA): A repository dedicated to teaching exploratory data analysis techniques in Python.

• Big data processing: Focuses on processing large datasets using Python, with examples and best practices.

• Django: A repository for learning Django, the high-level Python web framework for rapid development.

• Dataset: Contains various datasets that can be used for data science projects and learning purposes.

• 🔥 Copywriting with ChatGPT: An e-book that explores the use of ChatGPT for copywriting, providing insights and techniques.

• 📘 AI tools: This e-book compiles a range of AI tools that can be utilized in various fields, including data science and machine learning.

• ✨ Systematic Literature Review: A comprehensive guide to conducting systematic literature reviews, with methodologies and examples.

• The Daily Life of a PhD Student: Offers insights into the routine and experiences of a PhD student, providing valuable tips for navigating academic research.

• Undergraduate projects: A repository dedicated to showcasing undergraduate research projects and their outcomes.

• Research Colloquium Series 1: Best practices for using the cloud in research: Discusses the optimal ways to leverage cloud technology for research purposes, enhancing efficiency and collaboration.

• Learn Github: A comprehensive guide for researchers to learn how to use GitHub for version control and collaboration on research projects.

• Research Material: Contains a collection of materials and resources that can support various aspects of academic research.