Course Outline
Fundamentals of Generative AI
- Defining generative AI and its significance.
- Exploring primary types and techniques within generative AI.
- Identifying key challenges and limitations inherent to generative AI.
Transformer Architectures and LLMs
- Understanding the transformer model and its functionality.
- Reviewing essential components and characteristics of transformers.
- Constructing LLMs utilizing transformer technologies.
Scaling Laws and Optimization Strategies
- The role and importance of scaling laws in LLM development.
- The relationship between scaling laws and model size, data volume, compute resources, and inference demands.
- Utilizing scaling laws to enhance LLM performance and efficiency.
Training and Fine-Tuning LLMs
- Key steps and obstacles involved in training LLMs from the ground up.
- Weighing the advantages and disadvantages of fine-tuning LLMs for specialized tasks.
- Best practices and recommended tools for effective training and fine-tuning.
Deployment and Utilization of LLMs
- Critical factors and challenges in deploying LLMs for production environments.
- Common use cases and applications of LLMs across different industries and sectors.
- Integrating LLMs with other AI systems and platforms.
Ethics and the Future of Generative AI
- Social and ethical considerations surrounding generative AI and LLMs.
- Potential risks and harms, such as bias, misinformation, and manipulation, associated with these technologies.
- Strategies for the responsible and beneficial application of generative AI and LLMs.
Recap and Future Directions
Requirements
- Familiarity with core machine learning principles, including supervised and unsupervised learning, loss functions, and data partitioning.
- Proficiency in Python programming and data manipulation.
- 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
