Course Outline
Introduction to Generative AI
- Understanding the definition and significance of generative AI.
- Overview of primary types and techniques within generative AI.
- Key challenges and limitations inherent to generative AI.
Transformer Architecture and LLMs
- Defining the transformer and explaining its operational mechanisms.
- Identifying the main components and features of a transformer.
- Leveraging transformers to construct Large Language Models.
Scaling Laws and Optimization
- Defining scaling laws and their critical role in the development of LLMs.
- Understanding the relationship between scaling laws, model size, data volume, compute budget, and inference requirements.
- Utilizing scaling laws to enhance the performance and efficiency of LLMs.
Training and Fine-Tuning LLMs
- Exploring the primary steps and challenges involved in training LLMs from scratch.
- Weighing the benefits and drawbacks of fine-tuning LLMs for specific applications.
- Adopting best practices and tools for training and fine-tuning LLMs.
Deploying and Using LLMs
- Examining key considerations and challenges associated with deploying LLMs in production environments.
- Identifying common use cases and applications of LLMs across various domains and industries.
- Integrating LLMs with other AI systems and platforms.
Ethics and Future of Generative AI
- Analyzing the ethical and social implications of generative AI and LLMs.
- Assessing potential risks and harms, such as bias, misinformation, and manipulation.
- Promoting responsible and beneficial utilization of generative AI and LLMs.
Summary and Next Steps
Requirements
- A foundational understanding of machine learning concepts, including supervised and unsupervised learning, loss functions, and data splitting.
- Practical experience with Python programming and data manipulation.
- Basic knowledge of neural networks and natural language processing.
Target Audience
- Software Developers
- Machine Learning Enthusiasts
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
