Become an AI engineer

Building skills & expertise in AI is one of the best investments you can make in 2024.

With the AI revolution underway, there are many new jobs, startups, and opportunities for anyone with expertise in the field. From developers to marketers, understanding the foundations of AI is a must-have.

Gain foundational knowledge and skills working with LLMs, practical prompt engineering, fine tuning, vector databases, AI agents, building AI apps with Streamlit, and more.

This is designed to fast track your knowledge and skills in AI, while covering both key concepts & real-world projects using modern tools like the OpenAI API, Pinecone, Streamlit, and more.

What we'll cover

AI engineering covers a range of topics, from working with LLMs to building AI-enabled Streamlit apps. Specifically, we'll cover the following topics:

Module 1: Foundations of LLMS

• Intro to LLMs & the Transformer architecture
• Understanding tokens & context windowns

Module 2: Prompt Engineering

• What is prompt engineering?
• Improving LLM responses & reliability
• Prompt techniques

Module 3: Using LLM Tools

• Top LLM tools to know
• Open source LLMs to watch
• Getting started with ChatGPT
• Building a custom GPT
• LLM settings & the OpenAI Playground

Module 4: Getting Started with the OpenAI API

• Making your first Chat Completions request
• Getting started with the Assistants API
• Introduction to function calling

Module 5: Getting Started with the Claude API

• Making your first Claude API request
• Prompt engineering with the Claude metaprompt
• [Project] Function calling & tool use with Claude

Module 6: Fine Tuning LLMs

• Introduction to GPT fine tuning
• [Project] Fine tuning for brand tone of voice
• [Project] Fine tuning for structured output

Module 7: Vector Databases

• Intro to embeddings & vector databases
• Top vector databases to watch
• [Project] Website Q&A with GPT-4 & Pinecone

Module 8: AI Agents

• What are AI agents?
• Top AI agents to watch
• Getting started with AutoGen
• Data visualization agent with AutoGen

Module 9: AI Engineering Projects

• [Project] Building a text-to-speech app with OpenAI & Streamlit
• [Project] GPT-4 Vision for data analysis app
• [Project] Building a stock screener assistant with GPT function calling
• [Project] Building a financial statement assistant with GPT function calling

Tools covered

• OpenAI Chat Completions API
• OpenAI Assistants API
• OpenAI Function calling
• Text to speech
• GPT-4 Vision
• Pinecone
• Streamlit

Who is this for?

Whether you're a beginner, experienced developer, or a business executive, this track will help fast-track your AI learning curve.

• Developers looking to learn foundations of AI & LLMs
• Business professionals that want to incorporate LLMs into their work
• Creatives that want to learn how to work with AI and future proof their careers

Ideally you have some basic Python skills, but if not you can still follow along and learn from all the notebooks & code templates provided.

By the end of this AI Engineering track, you'll have hands-on experience with multiple AI tools, APIs, and a portfolio of projects that you can use to land a job in AI or launch an MVP for your own startup.

Enroll today