Fine-Tuning Large Language Models
DeepLearning.AI’s short course on fine-tuning LLMs — learn when and how to customize language models for your specific use case.
Deep Learning Specialization
Andrew Ng’s comprehensive 5-course specialization covering neural networks, CNNs, RNNs, and sequence models from the ground up.
System Prompts: Building Reliable AI Assistants
Learn to design system prompts that create consistent, reliable AI assistants for production applications.
Chain of Thought: Advanced Reasoning Techniques
Master chain of thought prompting, tree of thought, and other advanced reasoning techniques for complex AI tasks.
AI Operations: Automating Business Workflows
Automate complex business workflows with AI using Make.com, Zapier, n8n, and custom integrations.
Building RAG Systems from Scratch
Design and implement production-ready RAG systems with vector stores, embedding models, chunking strategies, and evaluation.
Fine-tuning Large Language Models
Learn to fine-tune open-source LLMs using LoRA, QLoRA, and RLHF with Hugging Face’s transformers library.
Building AI Agents with Tool Use
Build autonomous AI agents that can use tools, browse the web, write code, and complete complex multi-step tasks.
Model Deployment: From Notebook to Production
Deploy ML models to production using FastAPI, Docker, Kubernetes, and cloud platforms with monitoring and CI/CD.
MLOps: Production Machine Learning Systems
Build end-to-end MLOps pipelines with experiment tracking, model versioning, automated retraining, and production monitoring.