DeepLearning.AI Short Courses

Course Available

Building an AI-Powered Game

Learn to build with LLMs by creating a fun interactive game from scratch.

AI Safety AI in Software Development GenAI Applications Generative Models LLMOps Prompt Engineering

ChatGPT Prompt Engineering for Developers

Learn the fundamentals of prompt engineering for ChatGPT. Learn effective prompting, and how to use LLMs for summarizing, inferring, transforming, and expanding.

OpenAI

GenAI Applications Prompt Engineering Transformers

LangChain for LLM Application Development

Use the powerful and extensible LangChain framework, using prompts, parsing, memory, chains, question answering, and agents.

LangChain

AI Frameworks Agents Chatbots Generative Models Prompt Engineering RAG

How Diffusion Models Work

Learn and build diffusion models from the ground up, understanding each step. Learn about diffusion models in use today and implement algorithms to speed up sampling.

Deep Learning Diffusion Models GenAI Applications Generative Models

Building Systems with the ChatGPT API

Learn to break down complex tasks, automate workflows, chain LLM calls, and get better outputs from LLMs. Evaluate LLM inputs and outputs for safety and relevance.

OpenAI

AI Safety Chatbots GenAI Applications Generative Models Prompt Engineering

LangChain Chat with Your Data

Create a chatbot with LangChain to interface with your private data and documents. Learn from LangChain creator, Harrison Chase.

LangChain

Computer Vision Document Processing Embeddings RAG Vector Databases

Building Generative AI Applications with Gradio

Create and demo machine learning applications quickly. Share your app with teammates and beta testers on Hugging Face Spaces.

Hugging Face

Chatbots Diffusion Models GenAI Applications Generative Models

Evaluating and Debugging Generative AI

Learn MLOps tools for managing, versioning, debugging, and experimenting in your ML workflow.

Weights & Biases

Evaluation and Monitoring Fine-Tuning Generative Models LLMOps MLOps MultiModal Prompt Engineering

Large Language Models with Semantic Search

Learn to use LLMs to enhance search and summarize results, using Cohere Rerank and embeddings for dense retrieval.

Cohere

Embeddings NLP RAG Search and Retrieval Vector Databases

Finetuning Large Language Models

Discover when to use finetuning vs prompting for LLMs. Select suitable open-source models, prepare data, and train & evaluate for your specific domain.

Lamini

Deep Learning Fine-Tuning Transformers

How Business Thinkers Can Start Building AI Plugins With Semantic Kernel

Learn Microsoft's open source orchestrator, Semantic Kernel and use LLM building blocks such as memory, connectors, chains and planners in your apps.

Microsoft

AI Frameworks Chatbots GenAI Applications Prompt Engineering RAG

Understanding and Applying Text Embeddings

Learn how to accelerate the application development process with text embeddings for sentence and paragraph meaning.

Google Cloud

Embeddings GenAI Applications NLP RAG Search and Retrieval

Pair Programming with a Large Language Model

Learn how to prompt an LLM to help improve, debug, understand, and document your code. Use LLMs to simplify your code and enhance productivity.

Google

AI in Software Development GenAI Applications Prompt Engineering

Functions, Tools and Agents with LangChain

Learn about the latest advancements in LLM APIs and use LangChain Expression Language (LCEL) to compose and customize chains and agents.

LangChain

AI Frameworks Agents Chatbots Generative Models Prompt Engineering RAG

Vector Databases: from Embeddings to Applications

Design and execute real-world applications of vector databases. Build efficient, practical applications, including hybrid and multilingual searches.

Weaviate

Embeddings GenAI Applications RAG Search and Retrieval Vector Databases

Quality and Safety for LLM Applications

Learn how to evaluate the safety and security of your LLM applications and protect against risks. Monitor and enhance security measures to safeguard your apps.

WhyLabs

AI Safety Embeddings Evaluation and Monitoring GenAI Applications Vector Databases

Building and Evaluating Advanced RAG

Learn advanced RAG retrieval methods like sentence-window and auto-merging that outperform baselines, and evaluate and iterate on your pipeline's performance.

TruEra, LlamaIndex

AI Frameworks Evaluation and Monitoring GenAI Applications LLMOps RAG Search and Retrieval

Reinforcement Learning From Human Feedback

Get an introduction to tuning and evaluating LLMs using Reinforcement Learning from Human Feedback (RLHF) and fine-tune the Llama 2 model.

Google Cloud

Fine-Tuning Generative Models LLMOps Transformers

Advanced Retrieval for AI with Chroma

Learn advanced retrieval techniques to improve the relevancy of retrieved results. Learn to recognize poor query results and use LLMs to improve queries.

Chroma

Embeddings Fine-Tuning GenAI Applications RAG Search and Retrieval

Build LLM Apps with LangChain.js

Expand your toolkit with LangChain.js, a JavaScript framework for building with LLMs. Understand the fundamentals of using LangChain to orchestrate and chain modules.

LangChain

AI Frameworks Chatbots GenAI Applications Prompt Engineering RAG Search and Retrieval

LLMOps

Learn LLMOps best practices as you design and automate steps to fine-tune and deploy an LLM for a specific task.

Google Cloud

AI Safety Chatbots Data Processing Evaluation and Monitoring Fine-Tuning LLMOps

Automated Testing for LLMOps

Learn how to create an automated CI pipeline to evaluate your LLM applications on every change, for faster and safer development.

CircleCI

Evaluation and Monitoring LLMOps MLOps Prompt Engineering

Building Applications with Vector Databases

Learn to build six applications powered by vector databases, including semantic search, retrieval augmented generation (RAG), and anomaly detection.

Pinecone

Anomaly Detection Embeddings MultiModal Vector Databases

Serverless LLM Apps Amazon Bedrock

Learn how to deploy an LLM-based application into production using serverless technology. Learn to prompt and customize LLM responses with Amazon Bedrock.

AWS

Event-Driven AI GenAI Applications LLMOps

Prompt Engineering with Llama 2&3

Learn best practices for prompting and selecting among Meta Llama 2 & 3 models. Interact with Meta Llama 2 Chat, Code Llama, and Llama Guard models.

Open Source Models with Hugging Face

Learn how to easily build AI applications using open-source models and Hugging Face tools. Find and filter open-source models on Hugging Face Hub.

Hugging Face

Chatbots Generative Models MultiModal NLP Prompt Engineering Transformers

Knowledge Graphs for RAG

Learn how to build and use knowledge graph systems to improve your retrieval augmented generation applications. Use Neo4j's query language Cypher to manage and retrieve data.

Neo4j

Embeddings GenAI Applications RAG Search and Retrieval Vector Databases

Efficiently Serving LLMs

Understand how LLMs predict the next token and how techniques like KV caching can speed up text generation. Write code to serve LLM applications efficiently to multiple users.

Predibase

Fine-Tuning Generative Models LLMOps LLM Serving Transformers

JavaScript RAG Web Apps with LlamaIndex

Build a full-stack web application that uses RAG capabilities to chat with your data. Learn to build a RAG application in JavaScript, using an intelligent agent to answer queries.

LlamaIndex

AI Frameworks GenAI Applications Prompt Engineering RAG Search and Retrieval

Red Teaming LLM Applications

Learn how to make safer LLM apps through red teaming. Learn to identify and evaluate vulnerabilities in large language model (LLM) applications.

Giskard

AI Safety Chatbots Generative Models LLMOps Prompt Engineering

Preprocessing Unstructured Data for LLM Applications

Improve your RAG system to retrieve diverse data types. Learn to extract and normalize content from a wide variety of document types, such as PDFs, PowerPoints, and HTML files.

Unstructured

Computer Vision Document Processing GenAI Applications RAG Vector Databases

Quantization Fundamentals with Hugging Face

Learn how to quantize any open-source model. Learn to compress models with the Hugging Face Transformers library and the Quanto library.

Hugging Face

Generative Models Compression and Quantization MultiModal Transformers

Explore Mistral's open-source and commercial models, and leverage Mistral's JSON mode to generate structured LLM responses. Use Mistral's API to call user-defined functions for enhanced LLM capabilities.

Mistral AI

Embeddings Generative Models Prompt Engineering RAG

Prompt Engineering for Vision Models

Learn prompt engineering for vision models using Stable Diffusion, and advanced techniques like object detection and in-painting.

Comet

Computer Vision Diffusion Models Fine-Tuning Generative Models Prompt Engineering

Quantization in Depth

Customize model compression with advanced quantization techniques. Try out different variants of Linear Quantization, including symmetric vs. asymmetric mode, and different granularities.

Hugging Face

Compression and Quantization

Building Agentic RAG with Llamaindex

Build autonomous agents that intelligently navigate and analyze your data. Learn to develop agentic RAG systems using LlamaIndex, enabling powerful document Q&A and summarization. Gain valuable skills in guiding agent reasoning and debugging.

LlamaIndex

AI Frameworks Agents GenAI Applications Prompt Engineering RAG Search and Retrieval

Building Multimodal Search and RAG

Build smarter search and RAG applications for multimodal retrieval and generation.

Weaviate

Embeddings MultiModal RAG Search and Retrieval Vector Databases

Multi AI Agent Systems with crewAI

Automate business workflows with multi-AI agent systems. Exceed the performance of prompting a single LLM by designing and prompting a team of AI agents through natural language.

crewAI

AI Frameworks AI in Software Development Agents GenAI Applications RAG Task Automation

Introduction to on-device AI

Deploy AI for edge devices and smartphones. Learn model conversion, quantization, and how to modify for deployment on diverse devices.

Qualcomm

Data Processing Deep Learning Compression and Quantization On-Device AI

AI Agentic Design Patterns with AutoGen

Use the AutoGen framework to build multi-agent systems with diverse roles and capabilities for implementing complex AI applications.

Microsoft, Penn State University

AI Frameworks Agents GenAI Applications RAG Task Automation

AI Agents in LangGraph

Build agentic AI workflows using LangChain's LangGraph and Tavily's agentic search.

LangChain, Tavily

AI Frameworks Agents Chatbots Document Processing GenAI Applications Generative Models Search and Retrieval

Building Your Own Database Agent

Interact with tabular data and SQL databases using natural language, enabling more efficient and accessible data analysis.

Microsoft

Function-calling and data extraction with LLMs

Learn to apply function-calling to expand LLM and agent application capabilities.

Nexusflow

Agents Embeddings

Carbon Aware Computing for GenAI developers

Train your machine learning models using cleaner energy sources.

Google Cloud

GenAI Applications LLMOps LLM Serving

Prompt Compression and Query Optimization

Optimize the efficiency, security, query processing speed, and cost of your RAG applications.

MongoDB

Pretraining LLMs

Learn the essential steps to pretrain a large language model from scratch.

Upstage

Intro to Federated Learning

Build and fine-tune LLMs across distributed data using a federated learning framework for better privacy.

Flower Labs

AI Frameworks

AI Python for Beginners: Basics of AI Python Coding

Learn Python programming with AI assistance. Gain skills writing, testing, and debugging code efficiently, and create real-world AI applications.

DeepLearning.AI

Generative Models Prompt Engineering

Federated Fine-tuning of LLMs with Private Data

Learn how to securely fine-tune large language models (LLMs) with private data using federated methods, enhancing data privacy, minimizing risks of data leakage, and optimizing efficiency through Parameter-Efficient Fine-Tuning (PEFT) and Differential Privacy.