Practical AI for Developers

This week provides an introduction to the ethics, key players in AI infrastructure and models, and hands-on experience with APIs like OpenAI.

• Ethics, pitfalls, and possibilities

• Overview of some providers
  Models: OpenAI, Anthropic, Cohere, Google, Huggingface
  Infrastructure: Azure, AWS, Google Cloud, HF Spaces, Runpod

• OpenAI API
  Temperature
  Function calling
  Building plugins
  Compatible APIs

• Developing against a local LLM

• OpenRouter to easily access many models

• Google Colab and Jupyter Notebooks.

This week focuses on mastering advanced prompting techniques and introduces you to academic research in the field of AI.

• Langchain framework overview

• Advanced prompting techniques

  • Zero shot, one shot, few shot

  • Step-by-step instruction

  • Chain of thought, tree of thought, graph of thought

  • Persona adoption

  • Mix of experts

• Huggingface Transformers introduction

• Strategies for engaging with academic research

• Researching and evaluating models.

This week is dedicated to exploring the wide range of AI applications in multimedia, from generating images and transcribing voice to creating avatars.

• Text to image generation

• Transcription with Whisper

• Text to speech

• Voice cloning

• Avatar generation.

This week lets you dive into the mechanics of knowledge retrieval, utilising vector databases and augmented generation, while learning how to monitor and analyse these processes.

• Retrieval augmented generation
  Vector databases
  Embedding functions
  Open vs closed providers
  Limitations

• Knowledge graphs

• Observability and analytics (Phoenix and Langfuse)

• Exploring GptCache for caching.

In this week you'll delve into the intricacies of fine-tuning models, managing training data, and deploying AI models effectively.

• Fine-tuning models

• Open (e.g., Llama 2) vs closed (OpenAI)

• Managing training data

• Synthetic training data

• Evaluation and metrics

• Deploying models.

This week guides you through the design and functioning of AI-powered agents, offering a comparative study of different frameworks and discussions on safety and alignment.

• Overview of some popular implementations
  Auto-GPT, AgentGPT, SuperAGI, Botpress, MetaGPT, DevOpsGPT, GPT-Researcher

• Comparison of agent frameworks
  Langchain, Haystack, Llama index

• Tools and monitoring

• Human supervision

• Recursive self-improvement, replication, and autonomous sourcing of compute. **

** (Not really; we will focus extensively on alignment and safety)

Also Week 6: Culminating Projects

In this final week you'll apply all the knowledge and skills you've gained in individual or group projects.Note: AI is moving fast, so our curriculum does too. Expect changes as we go.