Large Language Models 10 week course by Aishwarya Naresh Reganti, ML Researcher!

Embark on a 10-week journey to master Large Language Models (LLMs). This course is your gateway to understanding the surge in LLM applications across various domains. From natural language processing to machine translation and automated content creation, grasp the transformative impact of LLMs. Designed for a broad audience, including business leaders, professionals, and students.

The course covers:
- Fundamentals of LLMs: Get started with the basics.
- Tools and Techniques: Dive into the tools that make LLMs work.
- Deployment and Evaluation: Learn how to bring LLM projects to life.
- Challenges and Future Trends: Explore what lies ahead for LLMs.
- Bonus Content: A special week on LLM architectural basics for those interested in research.

Format: Self-paced audit course with weekly content releases, featuring mind maps, quick overviews, comprehensive content, and the latest research papers.

Key Takeaways:
- Understand LLMs' practical fundamentals, capabilities, and limitations.
- Gain hands-on experience with LLM use cases.
- Learn best practices for evaluating LLMs in specific scenarios.
- Stay updated and integrate new LLM updates effectively.

Here are the topics week-wise:
🗓️Week 1: Practical Introduction to LLMs
⛳ Applied LLM Foundations
⛳Real World LLM Use Cases
⛳Domain and Task Adaptation Methods

🗓️Week 2: Prompting and Prompt Engineering
⛳Basic Prompting Principles
⛳Types of Prompting
⛳Applications, Risks and Advanced Prompting

🗓️Week 3: LLM Fine-Tuning
⛳Basics of Fine-Tuning
⛳Types of Fine-Tuning
⛳Fine-Tuning Challenges

🗓️Week 4: RAG (Retrieval-Augmented Generation)
⛳Understanding the concept of RAG in LLMs
⛳Key components of RAG
⛳Advanced RAG Methods

🗓️Week 5: Tools for Building LLM Apps
⛳Fine-tuning Tools
⛳RAG Tools
⛳Tools for observability, prompting, serving, vector search etc.

🗓️Week 6: Evaluation Techniques
⛳Types of LLM Evaluation (Behavior vs. Performance evaluation)
⛳Common Evaluation Benchmarks
⛳Common Metrics

🗓️Week 7: Building Your Own LLM Application
⛳Components of LLM application (from basic to advanced components)
⛳Build your own LLM App end to end with free resources

🗓️Week 8: Advanced Features and Deployment
⛳LLM lifecycle and LLMOps
⛳Advanced Features for LLM Deployment

🗓️Week 9: Challenges with LLMs
⛳Scaling Challenges
⛳Behavioral Challenges (Hallucinations, Alignment, Adversarial Attacks etc.)
⛳Deployment Challenges (Memory, Scalability, Security etc.)

🗓️Week 10: Emerging Research Trends
⛳Multimodal LLMs
⛳Open Source Models
⛳Agents
⛳Domain Specific Models
⛳New Architectures (MoE, Mamba etc.)

🗓️Week 11 *Bonus*: LLM Foundations
⛳Generative Models Foundations
⛳Neural Networks for Language (RNNs, LSTMs, S2S models etc.)
⛳Self-Attention and Transformers

Path to Notion content: https://shorturl.at/sFHM3
Downloadable markdown files on GitHub: https://shorturl.at/elFH3