All Courses
12 expert-designed courses spanning the full AI engineering stack. Start anywhere — finish everywhere.
Showing 12 courses
Prompt Engineering Mastery
Master the art and science of crafting prompts that get exceptional results from any AI model. From zero-shot to chain-of-thought — learn it all.
Python for AI
The Python crash course built specifically for AI engineers. Skip the boring stuff — learn lists, dicts, async, APIs, and data manipulation through AI projects.
Understanding Large Language Models
Go beyond the surface. Learn how transformers work, why models hallucinate, how context windows function, and what model architecture choices mean for your applications.
Building AI-Powered Applications with APIs
Build production-grade AI applications from scratch. Full-stack apps with Next.js, streaming responses, multi-turn conversations, tool calling, and real deployments.
RAG: Build Knowledge-Powered AI
Master Retrieval-Augmented Generation — the most impactful AI architecture for enterprise applications. Vector search, chunking, reranking, and production deployment.
AI Agents: Building Autonomous Systems
Build AI agents that plan, use tools, and complete multi-step tasks autonomously. ReAct, tool use, memory architectures, multi-agent systems, and production safety.
Fine-Tuning LLMs
Fine-tune Llama, Mistral, and GPT models for specialized tasks. LoRA, QLoRA, PEFT, dataset preparation, evaluation, and deployment on real hardware.
LangChain & LangGraph
Master the most widely-used AI orchestration frameworks. Build production chains, agents, RAG pipelines, and complex stateful workflows with LangGraph.
Vector Databases & Semantic Search
Master the infrastructure layer of modern AI: vector databases, ANN algorithms, embedding strategies, and production semantic search systems at scale.
MLOps: Shipping AI to Production
The complete MLOps playbook for AI engineers. CI/CD for ML, model serving, monitoring, drift detection, infrastructure as code, and scaling to millions of users.
AI for Computer Vision
Build production computer vision systems with modern foundation models. CLIP, SAM, object detection, video analysis, and real-world vision pipelines.
Building AI Products
Everything between idea and revenue for AI products. Product strategy, user research, AI UX design, GTM, pricing models, and lessons from 50+ AI product launches.