Training Course for University Lecturers

Shaping
FUTURE-READY
Education

"APPLYING AI AND BIG DATA
TO TRANSFORM TEACHING AND
LEARNING IN VIETNAM"

Time 22 Aug - 06 Sept, 2026
Duration 5 sessions
Location UEH University Campus
CALL FOR APPLICANTS
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More Information vidnt@ueh.edu.vn
Contact Us 028.3829.2411 (ext. 17)
About the Course

Pioneering Digital Transformation in Education

Artificial Intelligence (AI) is changing the way lecturers design lessons, develop learning materials, organize learning activities, and evaluate learners. In addition, the development of Big Data, Machine Learning, and Natural Language Processing (NLP) opens up many new possibilities in leveraging data for teaching and research.

The training course is designed for university lecturers, focusing on the practical applications of AI and data analytics. The program combines foundational knowledge, hands-on tool practice, real-world case studies, and applied projects.

No prior in-depth knowledge of programming or AI is required.
AI in Education
Objectives

What will learners achieve after the course?

Instructional Design

Use AI to develop learning materials, design lessons, slides, scenarios, and creative learning activities.

Testing & Assessment

Use AI to assist in designing questions, exercises, and effective testing and assessment activities for learners.

Working Effectively with AI

Construct and refine prompts, collaborate with AI on professional tasks, and verify its reliability.

Leveraging Big Data

Explore Machine Learning and NLP applications through Toolkits, sample data, and real-world problems.

Responsible AI

Identify issues related to accuracy, privacy, ethics, and legality when using AI in education.

Applied Project

Develop an AI application product or solution linked to a specific subject and complete it with expert support.

Content

Training Program

The course consists of 5 sessions, combining theory and in-depth practice

Session 1 (Morning, Aug 22)

AI Fundamentals & Prompting for Education

  • Overview of AI and its applications in education (Generative AI, Trends).
  • Basic Prompt Engineering: Principles & Techniques.
  • Practice: Develop and refine prompts for specific teaching tasks.
Session 2 (Afternoon, Aug 22)

AI for Teaching, Learning and Assessment

  • Working effectively with AI: Advanced prompting & Co-working.
  • AI in instructional design and assessment.
  • Responsible use of AI (Ethics, legality, bias).
  • Practice: Co-working with AI to develop learning materials, exercises, and slides. Evaluate reliability.
Session 3 (Morning, Aug 23)

Big Data, Machine Learning & NLP: Hands-on

  • Overview of Big Data and analytical tools in teaching & research.
  • Analyzing text and social media data (Text Mining, Unsupervised Learning - ESG Case).
  • Machine Learning in forecasting problems (Supervised Learning - Learning Outcomes Forecasting Case).
  • Practice: Hands-on directly with Toolkits and sample data, reading and interpreting results.
Session 4 (Afternoon, Sep 05 - Hybrid)

From Use Cases to Classroom Application

  • Practical application scenarios at UEH (Lesson design, Student guidance).
  • Designing AI application projects for subjects (Defining objectives, planning).
  • Practice: Lecturers share case studies. Learner groups develop project proposals, Q&A with experts.
Session 5 (Morning, Sep 06)

Project Presentation & Course Wrap-up

  • Mentoring/Coaching: Support to finalize end-of-course projects.
  • Presenting, defending, and providing feedback on individual projects in parallel sessions.
  • Summary evaluation, sharing implementation experiences, and closing.
  • Outcome: Each learner completes a practical application product for their subject.

Teaching Methodology

A combination of instruction, practice, case study discussions, and project implementation. Learners directly use AI tools and Toolkits on specific teaching tasks. During the project implementation process, groups receive consultation and feedback from lecturers, experts, and teaching assistants.

Participant Requirements

  • Lecturers working at higher education institutions in the South Central Coast, Central Highlands, and Southern regions (Priority given to female lecturers/those outside Ho Chi Minh City).
  • Have basic computer skills and prepare a laptop for practice.
  • Commit to full participation and completion of the end-of-course project.
  • Take personal responsibility for software copyrights and installed data.
Team of Experts

Course Lecturers

MSc. Dang Thai Thinh

Deputy Head of Infrastructure Management Department, UEH

AI & Machine Learning expert with over 15 years of experience. Participated in training over 30,000 lecturers and staff. Combines deep technological thinking with a modern vision.

Dr. Nguyen Tri Tri

Program Director, Univ. of Roehampton (UK)

Senior Lecturer at the University of Roehampton, UEH Lecturer. Main focal point promoting UK-Vietnam/ASEAN academic connections, international research expert (ABDC A*/A, Scopus Q1).

Assoc. Prof. Dr. Phan Chung Thuy

Deputy Dean of the Faculty of Banking, UEH

PhD in Finance (Germany), AI and ESG research expert. Guest Editor of Discover Artificial Intelligence. In charge of general coordination and course program design.

Dr. Nguyen Hoang To Loan

Lecturer at the Faculty of Accounting, UEH

PhD from JAIST (Japan). Supports evaluating course effectiveness, accompanies learners in the process of applying AI to teaching and academic development.

MSc. Le Van Lam

Lecturer at the Faculty of Banking, UEH

Joint PhD Candidate (UEH & Erasmus Rotterdam, Netherlands). Supports AI training in teaching and research data analysis.

MSc. Mai Khanh Linh

Lecturer at University of Medicine and Pharmacy at Ho Chi Minh City

Expert in Medical Ethics, Sociology. Supports the development of content on the responsible and ethical use of AI in higher education.

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The course is 100% tuition-sponsored (10 million VND/learner) by the TNE Grant Award 2025.

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