Certified Agentic and Robotic AI Engineer
Master Modern Python fundamentals, explore GenAI and Prompt Engineering, and gain essential skills in Linux, Docker, VSCode, Devcontainers, and GitHub for AI development.
Learn to develop Agentic AI systems with custom GPTs, prompt engineering, CrewAI framework, and knowledge graphs to integrate AI agents in real-world scenarios, including financial systems.
Advance your skills in Agentic AI with LangGraph and LangChain, and build dynamic AI agent frontends using Next.js, TypeScript, and Knowledge Graph integration.
Learn to build and deploy scalable AI-powered APIs with modern tools and frameworks, integrating design thinking and Behavior-Driven Development for user-centric AI solutions.
Explore Physical AI and humanoid robotics, mastering ROS 2, Gazebo, NVIDIA Isaac™, and OpenAI’s GPT models to design and deploy advanced humanoid robots.
Learn to build, deploy, and optimise distributed systems with Ray, the AI Compute Engine, for machine learning, data processing, and reinforcement learning.
Understand AI ethics and governance frameworks, exploring fairness, transparency, accountability, and privacy to lead responsible AI initiatives.
Learn to build and train AI models using PyTorch and Ray, exploring GANs, Transformers, LLMs, autoencoders, and diffusion models with hands-on experience.
Master the fine-tuning and deployment of open-source LLMs like Meta LLaMA 3 using PyTorch, with a focus on cloud-native training, optimization, and inference.
Master Kubernetes, Ray, Terraform, and GitHub Actions to design, deploy, and manage distributed AI systems and cloud-based AI pipelines with scalability and fault tolerance.