Generative AI for Beginners
in Artificial IntelligenceAbout this course
Course Title: Generative AI for Beginners: 6-Week Live Course
Course Overview:
The Generative AI for Beginners course is designed to introduce individuals with little or no prior knowledge to the exciting field of generative artificial intelligence. Through a combination of theoretical lectures, hands-on exercises, and real-world examples, participants will gain a strong foundation in generative AI concepts, techniques, and tools. By the end of the course, students will have the skills and knowledge required to develop their own generative AI applications.
Course Duration: 6 weeks (12 sessions)
Week 1: Introduction to Generative AI
- Understanding the basics of AI and its applications
- Overview of generative AI and its significance
- Key terminologies in generative AI
Week 2: Fundamental Concepts in Generative AI
- Differentiating between generative and discriminative models
- Introduction to neural networks and deep learning
- Probability theory and its role in generative models
Week 3: Generative Adversarial Networks (GANs)
- Conceptual explanation of GANs and their architecture
- Training GANs and overcoming common challenges
- Generating realistic images using GANs
Week 4: Variational Autoencoders (VAEs)
- Understanding autoencoders and their applications
- Introduction to variational inference
- Utilizing VAEs for image generation and data compression
Week 5: Recurrent Neural Networks (RNNs) for Generative Models
- Overview of RNNs and their significance in generative AI
- Introduction to sequence generation using RNNs
- Text generation using RNNs
Week 6: Advanced Topics in Generative AI
- Deep Reinforcement Learning for generative AI
- Conditional Generative Models
- Ethical considerations and challenges in generative AI
Course Requirements:
- Basic understanding of Python programming (recommended, but not mandatory)
- Familiarity with fundamental machine learning concepts (preferred, but not mandatory)
- Access to a computer with a stable internet connection for attending live sessions and completing exercises
Assessment and Grading:
- Weekly exercises and assignments: 60% of the final grade
- Course project: 40% of the final grade
- Active participation in live sessions and discussions
Course Materials:
- Lecture slides and notes provided before each session
- Additional resources and references for further reading
- Access to relevant software libraries and tools
Note: The course outline is subject to minor adjustments based on the instructor's discretion and the needs of the participants.
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Live - Generative AI for Beginners Kickoff with instructor, course and class introductions.