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Emerging Trend in Information and Data Science

KMUTNB
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About This Course

Emerging Trend in Information and Data Science is a graduate elective course for the Master of Science Program in Information and Data Science. The course helps students understand fast-changing technologies and methods that shape modern digital organizations. It combines theory, research orientation, and hands-on practice across data science foundations, data wrangling, visualization, advanced machine learning, deep learning, generative AI, MLOps, federated learning, responsible AI, NLP, cloud systems, IoT, edge analytics, agentic AI, and blockchain. Students learn not only how these technologies work, but also how to evaluate their impact, risks, ethics, governance, and practical value. Learning activities include laboratories, literature review, dashboards, model deployment, AI governance cases, and a term project symposium. Assessment balances exams, lab reports, assignments, ethical practice, teamwork, and project presentation. By the end, students should be able to explain, apply, integrate, and communicate emerging IT and data science solutions for real research and professional problems.

Requirements

The skills and knowledge of Python are highly recommended for students to take this course.

Course Staff

Phayung Meesad

Associate Professor Dr. Phayung Meesad is a distinguished academic and researcher in computer science and engineering. He teaches at the Faculty of Information Technology and Digital Innovation, King Mongkut's University of Technology North Bangkok (KMUTNB).

Academic Background

Dr. Meesad completed his doctoral studies in Electrical Engineering at Oklahoma State University, USA, in 2002. Before this, he obtained his Master of Science in Electrical Engineering from the same institution in 1998. His foundational education includes a Bachelor's in Technical Education (Teacher Training in Electrical Engineering) from King Mongkut's Institute of Technology North Bangkok.

Research Interests

His research focuses on several key areas:

  • Artificial Intelligence
  • Business Intelligence
  • Computational Intelligence
  • Data Analytics
  • Data Mining
  • Fuzzy Systems
  • Image Processing
  • Machine Learning
  • Natural Language Processing
  • Stock Price Prediction
  • Time Series Prediction

Professional Activities

At KMUTNB, he actively participates in:

  • Teaching graduate and undergraduate courses
  • Supervising research students
  • Contributing to academic publications

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Course Summary

  1. Course Number

    070125865

  2. Classes Start

  3. Classes End

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