Course Outline
Introduction to Generative AI
- Defining generative AI and exploring its significance.
- Overview of primary types and techniques within the generative AI landscape.
- Identifying key challenges and inherent limitations.
Transformer Architecture and LLMs
- Understanding what transformers are and their working principles.
- Examining the core components and characteristics of transformers.
- Utilizing transformers to construct Large Language Models.
Scaling Laws and Optimization
- Defining scaling laws and their relevance to LLMs.
- Analyzing the relationship between scaling laws and factors like model size, data volume, compute resources, and inference needs.
- Leveraging scaling laws to enhance LLM performance and efficiency.
Training and Fine-Tuning LLMs
- Reviewing the essential steps and hurdles in training LLMs from the ground up.
- Weighing the advantages and disadvantages of fine-tuning LLMs for specific objectives.
- Adopting best practices and recommended tools for training and fine-tuning.
Deploying and Utilizing LLMs
- Addressing the key considerations and challenges of production deployment.
- Exploring common use cases and applications across various industries.
- Integrating LLMs with other AI systems and platforms.
Ethics and the Future of Generative AI
- Discussing the ethical and social impact of generative AI and LLMs.
- Assessing potential risks and harms, such as bias, misinformation, and manipulation.
- Promoting the responsible and beneficial use of generative AI technologies.
Conclusion and Recommended Next Steps
Requirements
- A solid grasp of core machine learning concepts, including supervised and unsupervised learning, loss functions, and data partitioning.
- Proficiency in Python programming and data manipulation techniques.
- Foundational knowledge of neural networks and natural language processing.
Target Audience
- Software Developers
- Machine Learning Professionals
Testimonials (7)
Examples and links excel repository
Olga - GE HealthCare
Course - Generative AI with Large Language Models (LLMs)
a lot of examples and different tools to check
Bartosz - GE HealthCare
Course - Generative AI with Large Language Models (LLMs)
Custom GPTs, prompt engineering
Marcin Stezowski - GE HealthCare
Course - Generative AI with Large Language Models (LLMs)
Wide perspective
Artur - GE HealthCare
Course - Generative AI with Large Language Models (LLMs)
Technical examples in conjunction with theory.
Marcin - GE HealthCare
Course - Generative AI with Large Language Models (LLMs)
Mikołaj background outside IT enable presenting this topic from different angle - much needed for IT folks!
Grzegorz - GE HealthCare
Course - Generative AI with Large Language Models (LLMs)
Explanation form other than IT perspective. Adding value
