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39 coursesdeeplearning.ai
JetBrains
Learn to take control of your AI coding workflow. Starting from a Claude Code baseline, you'll structure work for smaller models, switch coding agents, connect to different models and providers, and progress from cloud to hybrid and fully local workflows. Along the way, you'll evaluate tradeoffs in…
Oracle
AI agents often repeat the same mistakes because they carry nothing forward between sessions. This course teaches three ways to fix that. Learners build a pipeline that turns agent traces into reusable, human-approved skills, build a code knowledge graph that improves retrieval in large codebases,…
University of Washington, NexusFlow
Adapt LLMs for specific tasks and behaviors using post-training techniques like SFT, DPO, and online RL.
Arize AI
Learn how to systematically evaluate, improve, and iterate on AI agents using structured assessments.
LangChain
Learn to build AI agents with long-term memory with LangGraph, using LangMem for memory management.
Qdrant
Build advanced retrieval systems that represent images with multiple vectors, enabling fine-grained matching between text queries and visual content for accurate multi-modal search.
AMD
Go beyond just using LLMs to actually understanding them. In this course taught by Sharon Zhou, you'll build the intuition to reason about model behavior, debug real problems, and make smarter decisions about deploying transformer-based models.
Predibase
Improve LLM reasoning with reinforcement fine-tuning and reward functions.
Box
Build an LLM app that uses tools from the Box MCP server to discover Box files and extract text from them. Transform it into a multi-agent system that communicates using A2A.
Neo4j
Build a multi-agent system that plans, designs, and constructs a knowledge graph.
Astronomer
Turn your GenAI prototype into an automated pipeline using Apache Airflow
LandingAI
Build agentic systems to parse documents and extract information grounded in visual components like charts, tables, and forms.
LlamaIndex
Build an event-driven agentic workflow to process documents and fill forms using RAG and human-in-the-loop feedback.
AMD
Learn how to apply fine-tuning and reinforcement learning techniques to shape model behavior, improve reasoning, and make LLMs safer and more reliable.
AGI Inc
Build agents that navigate and interact with websites, and learn how to make them more reliable.
Cerebras
This course, built in partnership with Cerebras and taught by Zhenwei Gao, Sebastian Duerr, and Sarah Chieng of Cerebras, shows you how to build LLM applications that respond in real time on Cerebras' Wafer-Scale Engine (WSE-3). It's a chip large enough to hold a model's weights on-chip, right next…
Qdrant
AI applications that depend on the cloud to remember things need a connection and send data to a remote server. This course teaches an on-device alternative: learners build a memory system that stores experiences as vectors across text, voice, and images, retrieves them by meaning, and teaches an a…
Qodo
AI can write more code than any team can review by hand. In this hands-on course with Qodo, you'll learn how to make AI code review effective, from running reviews early to giving the reviewer the right context. Then you'll build your own review agent and see why context is what makes a review reli…
Vocal Bridge
Add voice to your AI agents and applications using three integration patterns: embedded voice, voice layered on existing agents, and voice as a callable tool.
