Build a complete machine learning project using YOLOv9, from dataset creation and annotation to training and deployment for object detection.
Master AI hygiene essentials, learning to manage risks, ensure data governance, and implement security and ethical practices for AI systems.
Master API, UI, and performance testing with the Karate framework, integrating AI and Gatling for a complete automation solution.
Build production-grade RAG systems with Spring AI, covering ingestion, retrieval, and prompt orchestration for reliable, data-driven AI applications.
Build AI-powered applications with Spring AI and Java, covering prompts, memory, function calling, RAG, and multimodal AI for real-world use cases.
Master the fundamentals of Machine Learning and Deep Learning with a comprehensive A-to-Z guide covering core algorithms, neural networks, and key concepts.
Master deep learning models explained for beginners, covering neural networks, CNNs, RNNs, and Transformers in clear, intuitive language.
Build real-world AI applications with Google AI Studio and Gemini, covering text, code, image, and voice generation with three production-ready projects.
Build a complete AI Governance Command Center with Python and Streamlit, covering AI inventory, risk scoring, model evaluation, compliance, and audit reporting.
Build, attack, and secure LLM applications with Python, covering prompt injection, RAG security, tool calling, and AI agents in a hands-on masterclass.
Build and deploy AI agents with Google Antigravity, covering agent design, workflow automation, and tool integrations for real-world AI projects.
Prepare for the Claude Certified Architect exam with 400 practice questions covering Agentic Architecture, Claude Code, MCP, and prompt engineering, with detailed explanations.