Course Enrollment Link
https://www.ewant.org/admin/tool/mooccourse/mnetcourseinfo.php?hostid=13&id=14086
Certificate Application & Download Tutorial
Download Start Date: 2024/07/01
Summary
This course introduces generative AI, a powerful new technology that has the potential to revolutionize learning and education. The course will cover the theoretical foundations of generative AI and its practical applications in various fields, including text generation, audio generation, image generation, and video generation. Students will also explore the ethical considerations of using generative AI in education.
Course Objectives
- Understand the basic concepts, principles, and techniques of generative AI.
- Master commonly used models and tools for generative AI.
- Become familiar with the application areas and development trends of generative AI.
- Use generative AI models and tools to perform tasks such as text generation, image generation, and music generation.
Instructor
Hsueh-Ting Chu
Instructor Introduction
Prof. Chu is currently an associate professor in the Department of Information Engineering and holds a Ph.D. in Artificial Intelligence from Asia University. He has many years of experience in AI teaching and industry-university cooperation. His main research fields are Artificial Intelligence, Machine Learning, Deep Learning, Medical Informatics, and Genomics.
Course Schedule
- Unit 1: Introduction to Generative AI and Generative Deep Learning Models
- Unit 2: Text Generation / Audio Generation / Image Generation / Video Generation
- Unit 3: Generative AI Tools: OpenAI API / LangChain / LMStudio
- Unit 4: Applications of Generative AI in Education and Learning
- Unit 5: GenAI Stars Hackathon
- Unit 6: The Future of Generative AI
Course Content
This course introduces the latest developments and applications of generative AI in education. Generative AI is an artificial intelligence technology that can create realistic and original content such as text, images, audio, and video. In the field of education, generative AI can be used for personalized learning, automated assessment, simulation creation, and gamified learning. Topics include:
- Understanding the basic concepts and principles of generative AI
- Case studies of various generative AI applications
- Mastering examples of generative AI applications in education
- Evaluating the challenges and impacts of generative AI in education
Grading Criteria
- Regular Quizzes: 30% of the total grade
- Midterm Exam: 30% of the total grade
- Final Exam: 40% of the total grade
Passing Criteria
- Passing grade: 60
- Maximum grade: 100
Prerequisites or Required Skills
Basic knowledge of web browsing and image formats is sufficient. This course is suitable for all learners interested in AI.
