Enterprise AI Engineering Foundations

AI Engineering Foundations: Enterprise Training for Technical Teams

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.

Learners Foundational
Time Client definable
Duration 5 Days; Definable
Program Type Customizable Programs
Certificate Type Certificate
Format
Any Format/Location
CEUS Available
PDUS Available
Program Number AIEngF-Custom
Fees Group Rate
See full course info

Submit an Inquiry

Course Info

Benefits

Topics

Who Should Attend

Schedule

FAQ

Your team will learn to:

Explain core LLM components (embeddings, attention) and when to use them
Apply zero/few-shot, chain-of-thought, and ReAct/Reflexion prompting for reliable behavior
Execute PEFT/LoRA-style fine-tuning to adapt open-weight models to enterprise context
Stand up a private code assistant for internal evaluation (non-production)
Differentiate demo versus production requirements and define validation gates
Draft a 30/60/90-day internal action plan

LLM evolution; embeddings, attention; supervised/unsupervised/RL basics
Prompt engineering: zero-/few-shot, chain-of-thought, ReAct, Reflexion
Fine-tuning with LoRA/PEFT; working with APIs and open-source hubs
Private code-assistant setup with on-prem open-weight models
Capstone (education prototype): fine-tune an open-weight model; deploy a private code assistant for internal testing

Do participants build a production model in this course? No. All artifacts are produced for educational purposes during the course.

Can our teams use enterprise data during the labs? Yes, if the data is non-confidential or appropriately anonymized. No production integrations occur during class.

Can this course run behind our firewall and use our internal enterprise model endpoints? Yes. We can deliver the course on-premises, in a VPC, or in air-gapped environments and connect to your enterprise-approved model endpoints (for example, Azure OpenAI or other hosted foundation models, Bedrock in a private VPC, or self-hosted/open-weight deployments). In-class access is used for research and evaluation during the course; no production integrations or changes are performed in class. Any production access, promotion, or change management follows your enterprise policies and remains outside the scope of the course.

Which frameworks and tools are covered? We introduce open- and closed-weight LLMs, Hugging Face resources, and prompt-engineering methods; we also cover the basics of LangChain, LlamaIndex, and LangGraph/LangSmith.

How is governance addressed in the Foundations tier? We cover policy guardrails, role-based access, audit trails, evaluation basics, and reliability considerations appropriate to foundational work.

Who owns the materials and outputs created in class? Your organization owns the creations your participants produce during class; Caltech retains ownership of course materials and templates.

How does this course relate to the Enterprise AI Engineering series? Foundations is the first tier of a three-course series designed to help companies target content to different skill levels.

Can learners progress through all three tiers over time? Yes. The series is structured so learners can begin with Foundations and move into Intermediate and Advanced as their roles and responsibilities evolve.

Enterprise AI Engineering Foundations

AI Engineering Foundations: Enterprise Training for Technical Teams

Program Experience

Course Info

Meet the Educators

Harish Kashyap

Mike Frantz, PhD

Instructors

Mike Frantz, PhD

Harish Kashyap

Enterprise AI Engineering Foundations

AI Engineering Foundations: Enterprise Training for Technical Teams

Program Experience

Course Info

Meet the Educators

Harish Kashyap

Mike Frantz, PhD

Related Programs

Reinventing Work for the Age of AI

Enterprise AI Engineering Intermediate

AI-Assisted Development

Instructors

Mike Frantz, PhD

Harish Kashyap