August 2026

Machine Learning Engineer

Natalie Krzyzanowski

Engineers and engineering leaders who build, deploy, and scale software systems.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Building autonomous AI agent systems that take actions, use tools, and orchestrate multi-step workflows.

Designing and optimizing the context window for LLM applications — prompt structure, memory, and information retrieval.

Operating and deploying large language models in production — fine-tuning, inference, monitoring, and cost optimization.

Building retrieval-augmented generation and search systems — vector databases, embeddings, ranking, and retrieval pipelines.

Build and reason about enterprise agents grounded in your team's knowledge base

Agentic Search Expert

Shopify.com

Reddit

Wikipedia

LexisNexis

Apple

Doug Turnbull

Led teams at Shopify, Reddit, Wikipedia

AI Builder/Educator (6 Million Students)

Google

Instagram

OpenAI

Netflix

Yale

Hugo Bowne-Anderson

AI & data engineer, consultant, educator of 6+ million students (ex-Yale)

Build Production-Ready AI Agents for the Enterprise

Doug Turnbull (Maven)

<h3>Why I enrolled</h3>

<p></p>

<p></p>
<h3>What I’ll apply</h3>
<p class="p2-tall">Agent harness design and implementation, and experimenting with different guardrails </p>
<p></p>

Certificate

Learn more about this course