Harish Kashyap

This dynamic five-day Python-based course immerses participants in cutting-edge technologies through hands-on projects and real-world applications. Build modern AI foundations with Natural Language Processing and learn how these techniques are leveraged in generative AI. Then explore the world of generative AI, uncovering the power of transformer models, large language models, and tools like LangChain and Hugging Face. Build advanced generative systems with vector databases, RAG architectures, and fine-tuning techniques to create chatbots and knowledge management solutions. Unlock the potential of computer vision with CNNs, image preprocessing, and object detection. The journey concludes with advanced vision techniques, custom model creation, and powerful deployment strategies for AI-driven workflows.

AI agents are moving beyond copilots and chatbots into systems that perceive, reason, and act. This program gives business leaders practical frameworks and applied experience to evaluate opportunities, govern risks, and scale agentic AI—linking agent flows to enterprise value and measurable outcomes.

AI and data now shape every decision—from budgets to customer experience. This program builds practical literacy for managers and directors: plain-English concepts, governance fundamentals, and ROI framing. Through case-based exercises (no coding, no company data), leaders learn to ask better questions and guide responsible adoption.

Establish a durable AI foundation to enable your engineering teams to design and build state-of-the-art AI systems. Participants learn modern LLM concepts, prompting methods, and parameter-efficient fine-tuning, with options for closed-API or open-weight models in on-premises or air-gapped contexts. This course is part of Caltech’s Enterprise AI Engineering series (Foundations, Intermediate, Advanced), a sequence that organizations can target to different skill levels; learners may progress through all three over time. All three tiers belong to the same series and can be sequenced or spaced to cascade learning across roles—enabling cohorts to advance from foundational literacy to applied prototyping and, ultimately, governed multi-agent design.

Accelerate your engineering teams from literacy to applied prototyping. Participants will implement retrieval-augmented generation and agent patterns, then instrument behavior with tracing and metrics. We emphasize guardrails, evaluation, and deployment choices across closed APIs and open-weights—optionally in on-prem or air-gapped contexts. This course is part of Caltech’s Enterprise AI Engineering series (Foundations, Intermediate, Advanced), a sequence that organizations can target to different skill levels; learners may progress through all three over time. All three tiers belong to the same series and can be sequenced or spaced to cascade learning across roles—enabling cohorts to advance from foundational literacy to applied prototyping and, ultimately, governed multi-agent design.

Move beyond single agents to scalable, governed multi-agent systems. Teams design planner-executor architectures with memory and tool use, practice semantic routing, and explore Model Context Protocol for controlled, multi-endpoint execution—suitable for regulated, on-prem or air-gapped environments. This course is part of Caltech’s Enterprise AI Engineering series (Foundations, Intermediate, Advanced), a sequence that organizations can target to different skill levels; learners may progress through all three over time. All three tiers belong to the same series and can be sequenced or spaced to cascade learning across roles—enabling cohorts to advance from foundational literacy to applied prototyping and, ultimately, governed multi-agent design.