Certified Agentic and Robotic AI Engineer
Master Modern Python programming for AI development with a strong focus on static typing, OOP, and asynchronous programming. Enhance efficiency using AI-assisted coding tools like GitHub Copilot. Gain hands-on experience in Python web development with frameworks like Streamlit and version control with GitHub.
Delve into Agentic AI, focusing on autonomous intelligent systems. Build a strong foundation in Conversational and Generative AI, progressing to hands-on development using the OpenAI Agents SDK. Explore AgentOps, deployment strategies, and observability to prepare for real-world AI applications.
Deepen your expertise in Agentic AI with advanced frameworks and design strategies. Learn to build enterprise-grade multi-agent systems with sophisticated reasoning, agent-to-agent communication, and robust frontends using Next.js and TypeScript. Capstone project included.
Master the deployment of scalable, stateful AI agents using Kubernetes, Docker, and Dapr. Learn to build and observe Cloud Native MCP Servers and APIs with robust architecture, context storage, and design thinking for production-grade Agentic AI systems.
Explore Physical AI and humanoid robotics, mastering ROS 2, Gazebo, NVIDIA Isaac™, and OpenAI’s GPT models to design and deploy advanced humanoid robots.
Master Ray for distributed AI computing, optimizing scalable machine learning, data processing, and model serving in cloud-based AI pipelines.
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.