Agentic AI

Coding with AI

AI Evals

AI for PMs

AI for Engineers

AI for Designers

AI for Marketers

AI for Founders

Product

User Research

Prototyping

Growth

Strategy

Influence

Leadership

Career Growth

Engineering

Machine Learning

Security

System Design

Design

Figma

Design Systems

Design Strategy

Marketing

Content Marketing

Go-to-Market

Product Marketing

B2B Marketing

AI for Leaders

Communication

Management

Storytelling

Founders

More

Everyone

Operators

Data Scientists

User Researchers

Project Managers

Sales People

Lawyers

Finance

Investors

Real Estate

Leave with a working AI analyst system on your laptop (skills, agents, data connections) and a finished analysis ready for Monday.

Principal Data Scientist @ Ontra 

Shane Butler

Principal Data Scientist @ Ontra | Ex-Stripe, Nextdoor, PwC, Appfolio

Data Science Leader |Ex-Microsoft

Sravya Madipalli

Data Science Leader@Superhuman (Prev. Grammarly)| Ex-Microsoft, eBay, Nextdoor

Head of Data @ Ontra AI | Ex-LinkedIn

Hai Guan

Head of Data @ Ontra | Ex-Nextdoor, LinkedIn, Pinterest, Meta

Bootcamp 1

This is a hands-on weekend bootcamp (4 hours Saturday, 4 hours Sunday) where you build AI analysts powered by Claude Code. Not a lecture series. Not a demo you watch. You set up your own environment, build custom skills and agents, connect to real data, and leave with a working system that turns business questions into charts, narratives, and presentations in minutes.No Python. No SQL. No coding of any kind. Claude Code writes all the code. You direct the analysis.By Sunday evening, you will have a complete AI analyst repo on your computer: 45 skills, 27 agents, data connections, and a finished analysis you can share with your manager Monday morning. Everything runs locally. No vendor lock-in. No proprietary platform. Just a repo you own.AI is changing how teams make decisions with data. The bottleneck is no longer the analysis — it is knowing how to set up the tools. This bootcamp gives you that setup in a weekend. You will not learn about agentic systems. You will build one.

Build agentic data analysts for your company in one weekend. No code.

Set up Claude Code as your personal AI analyst environment

Build custom skills that encode analytics best practices as markdown

 Build agents that automate multi-step analysis workflows

Produce a complete analysis with charts, narrative, and slide deck

Connect your own company data and analyze it before you leave

Product managers who are tired of waiting in the data team's queue. Stop waiting. Analyze it yourself.

Data scientists who want to multiply their output. You know how to do the analysis manually. Now automate it.

Engineers who want to make data-driven decisions without hiring a data team.

Master end-to-end AI engineering - transform prototypes into production-ready apps with LLMs, RAG & agents in just 8 weeks.

Cohort 4

Founder @ SwirlAI • Ex CPO @ neptune.ai

neptune.ai

Aurimas Griciunas

LinkedIn Top Voice in AI • Founder & CEO @ SwirlAI

Cohort 3

Cohort 5

The End-to-End AI Engineering Bootcamp is an 8-week, cohort-based experience designed to turn technical professionals into full-stack AI engineers who can confidently design, build, and deploy production-grade AI systems.🛠️ What You’ll BuildYou’ll develop your own capstone project - a real-world AI application built sprint by sprint, applying each week’s concept to solve a business-relevant use case. By the end, you’ll present it live on Demo Day, with a working repo and deployed app you can showcase to hiring managers, CTOs, or investors. 🧑‍💻Technologies include:<ul><li>LLM APIs (Gemini, Claude, GPT, etc.).</li><li>Vector databases &amp; RAG.</li><li>AI agent libraries (LangChain, LangGraph, ADK, AutoGen).</li><li>Docker, FastAPI, Kubernetes, cloud deployment.</li><li>Observability, evaluation, and performance testing.</li><li>Modern communication protocols (A2A, MCP).</li></ul>🧠 How It WorksEach week follows a real engineering sprint:<ul><li>Sprint Lesson (Monday): Self-paced learning with videos, cheatsheets &amp; reference code.</li><li>Sprint Review (Tuesday): Live walkthrough with Aurimas + deep Q&amp;A.</li><li>Sprint Build Lab (Thursday): Live coding session to implement key sprint features.</li><li>Bonus QnA and Feedback sessions.</li></ul>🎬 Pre-course that will help you prepare <a target="_blank" rel="noopener noreferrer nofollow" href="https://youtube.com/playlist?list=PLeId95Z-0iyOATuFuHt3zP5enX3eCOsoq&amp;si=1xrntQdNOUkXwH6H">here</a>.

🚀 Build Real AI Products, Not Just Prototypes

Design and optimize RAG architectures

Engineer and orchestrate agentic systems

Design and deploy multi-agent systems for complex workflows

Implement structured prompt and context management

Apply LLMOps for observability and continuous evaluation

Build and deploy production-grade GenAI applications

Software Engineers &amp; DevelopersWho want to transition into AI Engineering and build, deploy and scale real-world AI systems end-to-end.

ML Engineers &amp; Data ScientistsWho want to architect, evaluate and scale production-grade agentic AI systems.

Technical Founders &amp; CTOsWho want to make AI a core product capability and confidently design and ship scalable AI systems.

Future-proof your finance career by mastering AI tools, predictive modeling, and autonomous agents that handle real finance workflows.

Professor & AI Expert (510K+ Students)

General Motors

Samsung

HSBC

Barclays

Stellantis

Dr. Ryan Ahmed

Professor, AI expert, & YouTuber who has taught 500,000+ learners worldwide.

Cohort 1

AI Agents are rapidly transforming how business and finance teams operate. 6 months ago, building a DCF financial model took a junior analyst ~1 day. Today, a team of autonomous AI agents builds, audits, reports, and presents it in 10 minutes.Organizations are moving beyond spreadsheets and manual workflows toward AI-native systems, where intelligent agents analyze data, generate reports, and automate complex tasks.The problem: Most professionals still use AI for basic Q&amp;A and drafting emails; they lack the skills to build AI agents that execute real business and finance tasks autonomously.The solution: This bootcamp teaches you to build intelligent agents that reason, use tools, access data, and complete multi-step workflows automatically using Claude Code, Claude Cowork, and Copilot agents.What makes this bootcamp unique?<ul><li>AI Agent Workflows: Automate research, reporting, and operational tasks</li><li>Build AI Agents: Connect agents to financial data and generate insights, no coding required to start</li><li>Predictive Analytics: Use ML agents for forecasting, classification, and risk scoring</li><li>Autonomous Agent Teams: Deploy teams of agents that collaborate and improve continuously</li></ul>

Build AI Agents That Automate Business & Finance Workflows & Get Certified

Automate Business & Finance Workflows with AI Agents

Build Predictive Financial Models with AI Agents

Connect Agents to Financial Data with MCP

Build & Deploy Autonomous Finance Agent Teams

Master Agent Architectures & Guardrails

Capstone: Deploy an End-to-End Agent System

Finance Professionals &amp; Analysts wanting to automate workflows, build predictive models, and deploy AI agents for reporting and forecasting.

CFOs, Controllers &amp; Finance Managers who want to lead AI adoption and deploy autonomous agents for reconciliation and decision support.

Data-Savvy Accountants &amp; FP&amp;A Teams who want to move from manual spreadsheets to AI-powered workflows that analyze and forecast at scale.

The best way to learn Python for Data Science and AI, with the help of AI.

16 yrs in AI & Data, 3xAuthor, Mentor

Mirza Rahim Baig

AI Leader, GenAI Startup Mentor, Educator, Author | Zalando, Flipkart, ZS

Cohort 202505

Cohort 2

Real skills for real data science jobs. No outdated tutorials. Think in logic and use GenAI wisely. One unique course. One capstone. Weekly 1:1 mentorship.Don't be a code monkey, be a data science doer. Each week features a hands-on case study. The course is unique - teaches techniques like pseudocode effectively for data science tasks and uses GenAI for assistance for maximum learning. No fluff, just practical skills for data science roles. Additionally, this course will fill a HUGE gap - teaching skills like API fundamentals, using OpenAI API, that are essential for modern data professionals. By the end of this course, students will be able to: -<ul><li>Apply Python programming concepts - specifically for data science tasks</li><li>Manipulate and analyze data using key Python libraries</li><li>Create effective data visualizations to communicate insights</li><li>Implement end-to-end data analysis projects</li><li>Create ML models using sklearn</li><li>Use APIs for real world data - foundational knowledge for modern data science/AI</li><li>Use OpenAI APIs to access GenAI models like GPT</li></ul>Note: This is not a regular course. You will learn ONLY through case studies, each week, to get extremely practical knowledge.

In weeks, not months. Logic first. Don't be a code monkey!

Learn Python by doing end-to-end analyses

For Data Science, not developer focused

Logic first approach for beginners

GenAI used wisely as validator, not a crutch 

Multiple projects for your portfolio

Modern data science foundations

Basic IT literacy is enough. If you can use technology to access this course, you're good!

No prerequisites!

Anyone seeking to make a career in Data Science/AI.

Graduates looking to get into Data science/ analytics / AI roles.

Professionals in adjacent roles who would like to move to data science roles.

Transform from consumer of analytics to independent operator - asking sharp questions, validating answers, shipping decisions.

Stripe

Nextdoor

PwC India

Ontra

AppFolio

Microsoft

eBay

Grammarly

Superhuman

LinkedIn

Pinterest

Ask Better Questions, Make Faster Decisions - with AI as Your Analyst

Frame Problems Like a Senior Data Scientist

Design Metrics That Actually Drive Decisions

Diagnose Root Causes Without Guessing

Design Experiments That Ship

Turn Analysis Into Action With AI as Your Copilot

Synthesize Insights and Prioritize for Impact

Product Managers, engineers, and operators who need analytical independence and frameworks to measure success and drive decisions.

Designers and researchers stepping into strategy roles who need to quantify impact, run experiments, and influence with data-driven insights

Data professionals who want to frame better questions, delegate technical execution to AI, and drive impact with agentic analytics tools.

Learn practical, hands-on methods to evaluate, measure, and improve AI products using data science to make better product decisions.

Principal Data Scientist, AI Evaluations

Principal Data Scientist, AI Evaluations at Ontra

With the recent leaps in model capabilities, it is becoming clear that much of the AI evaluation work previously requiring humans to build and run can be automated through agentic systems. This course teaches you how to build those systems, and where human judgment and input is still required.The foundational work of designing eval frameworks, defining quality signals, and structuring failure analysis remains critical. But the execution of that work, running evaluations, scoring results, iterating on improvements, and surfacing what matters, can now be handled by agentic workflows that operate continuously and at scale.This course equips you with the capability to build, test, and deploy automated evaluation systems using Claude Code. You will leave with working systems, not just conceptual understanding.The focus is on automation that is trustworthy. Systems that score their own output, flag uncertainty, and know when to surface decisions to a human rather than proceeding autonomously.The foundational content on AI evals for product development is available free at <a target="_blank" rel="noopener noreferrer nofollow" href="https://aianalystlab.ai">aianalystlab.ai</a>. If you are new to AI evals, start there.

Build the agentic systems that automate your AI evaluation workflow from end to 

Build agentic evaluation workflows in Claude Code

Automate scoring and quality assessment

Implement iterative improvement loops

Scale experiment execution

Integrate with production data and decision-making

You will get the most out of it if you are actively working on, or about to ship, AI features in a real product.

Real-World AI Product Experience

Product Managers: Want automated eval systems for your team? Learn what is possible, reliable, and where human oversight stays essential.<pre><code class="language-markdown"></code></pre>

Data Scientists &amp; Analysts: Spending more time running evals than learning? Build systems that handle execution so you focus on decisions.

Engineers and ML Engineers: val bottlenecks slowing your release cycle? Automate repetitive work and ship with speed and confidence.

Learn how to evaluate, ship, and monitor GenAI products that perform reliably in production.

Head of AI Applied Science

Shopify

Carvana

Harvard University

Stella Liu

Cofounder, AI Evals & Analytics

System1

Uptake

Seasalt.ai

UCLA

University of Washington

Amy Chen

Cofounder at AI Evals & Analytics

<blockquote>Building AI is easier than ever. Building AI that is reliable, safe, and trusted is not.AI evaluations help teams measure quality, detect failures, and build guardrails around your GenAI systems that will survive in the real world.</blockquote><blockquote>🔹</blockquote><h3>Who this course is for</h3>Data scientists, QA/QE professionals, and PMs who:<ul><li>have no prior background in AI evals, or</li><li>have tried LLM-as-a-judge but want a clearer framework.</li></ul><blockquote>🔹How the course works</blockquote><ul><li>Self-paced lectures you can watch anytime</li><li>Hands-on exercises using a pre-built GenAI product</li><li>Dedicated office hours for questions and guidance</li></ul><blockquote>🔹</blockquote><h3>What makes this course different</h3><ul><li>Playbook-driven approach</li><li>Evaluation-driven development</li><li>Product-focused</li><li>Hands-on experience</li><li>Flexible learning + expert support</li></ul>🔹Curious about the ideas behind this course? You can explore related topics in the <a target="_blank" rel="noopener noreferrer nofollow" href="https://datasciencexai.substack.com/">Data Science × AI Substack</a>, where we share perspectives on evaluating real GenAI products.

Learn How to Evaluate GenAI Products Confidently in 3 Weeks

Execution-ready Testing & Monitoring Playbook

GenAI Risk Management Strategy

Hands-On AI Evals Exercise

Product LeadersBuilding GenAI products and need a clear playbook for evaluation frameworks, success metrics, and shipping with confidence.

Data ScientistsLeveling up with AI product skills: learn AI evals, LLM-as-a-judge, and design metrics for GenAI systems.

QA and Test EngineerAdapting traditional testing practices to GenAI systems.

Stop being the “number explainer.” Build the stories, systems, and credibility to lead with clarity and confidence in the age of AI.

Data & AI leader,19yrs of scaling teams

Pier Martin

 Data & AI leader with 19+ years scaling global teams, Executive coach 

Cohort 7

As a data leader, do you catch yourself asking questions like…- How do I get execs to actually act on my insights instead of tuning out?- How do I influence peers in Product, Ops, and Marketing when they don’t report to me? - How can I build credibility around AI adoption without just demoing tools?- How do I stop my team from being seen as a “ticket shop” and instead as a trusted partner?If you’re not confident about these, this course is for you. This is a hands-on leadership course designed for emerging data leaders, analytics managers, data science managers, and heads of data who want to grow from technical doers into visible, trusted, AI-ready leaders.Before this course, you may feel:- Stuck explaining numbers that don’t lead to action.- Anxious that AI will outpace your team or make your work irrelevant.- Reactive to hype or resistance, rather than steering the narrative.After this course, you’ll:- Turn “data dumps” into compelling stories that executives repeat in the boardroom.- Translate AI pilots into credible business cases that prove ROI, reduce fear, and win support.- Lead your team confidently through change, balancing optimism with realism.

Lead with Data. Inspire with Story. Win with AI.

How to Master Strategic Communication

How to Lead AI Change with Confidence

  How to Build Your Leadership Operating System

Folks who are early in their career, focused only on technical execution, or looking to break into data/analytics should not enroll.

This course is NOT FOR everyone

It is designed for data managers, analytics leads, and heads of data already managing teams and facing leadership challenges.

This is NOT a beginner-level technical course

Overlooked Data Manager delivering dashboards but dismissed in strategy conversations, eager to be trusted for impact.

AI for Data Scientists

Cohort-based courses

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