Course Outline
Foundations of Generative AI
- Defining generative AI and exploring its strategic importance.
- Overview of primary generative AI modalities and techniques.
- Identifying key challenges and inherent limitations.
Transformer Architecture and LLM Mechanics
- Understanding the transformer model and its operational logic.
- Examining the core components and distinctive features of transformers.
- Strategies for leveraging transformers to construct LLMs.
Scaling Laws and Performance Optimization
- The role of scaling laws in LLM development and their significance.
- Analyzing the relationship between scaling laws and model size, data volume, compute resources, and inference demands.
- Utilizing scaling laws to enhance both the performance and efficiency of LLMs.
Training and Fine-Tuning LLMs
- Key stages and obstacles involved in training LLMs from the ground up.
- Assessing the advantages and disadvantages of task-specific fine-tuning.
- Best practices and essential tools for effective training and fine-tuning.
LLM Deployment and Practical Application
- Critical factors and challenges associated with production deployment.
- Common use cases and LLM applications across different industries.
- Methods for integrating LLMs with existing AI systems and platforms.
Ethics and the Future Landscape of Generative AI
- Ethical and social considerations surrounding generative AI and LLMs.
- Potential risks, including bias, misinformation, and manipulation.
- Guidelines for responsible and beneficial utilization of generative AI.
Conclusions and Roadmap for Future Learning
Requirements
- Solid grasp of machine learning fundamentals, including supervised and unsupervised learning paradigms, loss functions, and data partitioning strategies.
- Proficiency in Python programming and data handling techniques.
- Foundational knowledge of neural networks and natural language processing (NLP).
Target Audience
- Software developers.
- Machine learning professionals and 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
