Advanced Generative AI (Synchronous E-learning)
About This Course
This course provides learners with the knowledge and practical skills to analyze, design, and apply advanced generative AI models for real-world use cases. It is structured around learning outcomes, ensuring that learners move beyond memorization to critically deconstruct models, compare architectures, and interpret outcomes. The course begins with foundational concepts of generative models and large language models (LLMs), then progresses through key architectures such as VAEs, GANs, and Transformers. Learners also gain expertise in LangChain for workflow design and application development, advanced prompt engineering strategies, and fine-tuning of LLMs for domain-specific needs.The sequence culminates in benchmarking and evaluation, where learners analyze model performance and translate cutting-edge research into practical applications. By the end of the course, learners will be able to critically analyze generative AI techniques, manage projects from conception to deployment, and apply innovative solutions that bridge research and industry practice.
What You'll Learn
Analyze generative models by differentiating their architectures and examining their applications.
Examine the architecture of LLMs to analyze how design choices determine processing capabilities.
Deconstruct the workflows of VAEs and GANs by comparing generative processes.
Analyze attention mechanisms and transformer architectures by examining their efficiency and research frontiers.
Examine LangChain workflows by analyzing integration of tools and evaluating best practices.
Analyze advanced prompting strategies by evaluating their impact on model behavior.
Deconstruct LangChain-based applications by analyzing how prompts, embeddings, and retrieval chains interact.
Examine fine-tuning strategies by analyzing customization processes and evaluating adaptability.
Analyze LLM capabilities by interpreting benchmarking results across multiple tasks.
Entry Requirements
• Age: 25 years and above
• Education: At least a GCE 'O' Level certificate/ GCE ‘N’ Level (Normal Academic stream), Nitec or Higher Nitec qualifications
o Applicants without formal academic qualifications may also be considered if they have relevant work experience and computer knowledge
• Digital Proficiency:
o Comfortable using digital tools and workplace software (e.g., Microsoft Excel, cloud-based platforms)
o Able to perform basic computer tasks such as internet search, creating folders, and copy-paste operations
• Technical Experience:
o No coding experience is required