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

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 No outdated tutorials.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.

Build robust LLM-powered apps, chatbots, and agents. Learn by writing real code, one line at a time.

CEO @ Actualize

Jay Wengrow

Software Engineer and Educator, Author of A Common-Sense Guide to AI Engineering

Cohort 1

Do you have a grasp of basic LLM principles but struggle to put it all into code? Tired of scattered documentation, outdated tutorials, and frameworks that impress in demos but collapse in production?You’re not alone. Building with large language models doesn’t have to be confusing - it can be clear, structured, and deeply rewarding.In this course, you’ll build real LLM-powered apps, one line of code at a time. You'll see how an app is built from scratch in real time, and follow along. Along the way, you'll discover not only how to implement these systems, but the why behind each line of code.From chatbots to agents and RAG to evals, you’ll learn the core concepts of building atop LLMs. More importantly, you’ll get how LLMs “think” - allowing you to guide them to do what you want despite their nondeterministic nature. Additionally, you’ll be able to balance quality, latency, and cost, making big-picture decisions about AI-powered app architecture.AI engineering isn’t just another branch of software development - it’s a different mindset altogether.

Gain hands-on AI Engineering proficiency by writing real code

Gain real-world intuition for working with LLMs

Reliably guide LLMs instead of getting unpredictable results.

Build retrieval-augmented assistants that can access proprietary knowledge

Use evals to systematically optimize your LLM app’s performance over time

Assemble agents that act upon the real world

This course is designed for current software engineers who will use Python  to build LLM-powered apps. We won't teach basic coding here.

Software Engineering

We'll be using Python, but we'll keep it simple in case you're more familiar with other coding languages.

Note about Python

If you want an inside look at what's involved with building AI apps but don't plan on coding yourself, you'll still follow what's going on.

Exception: Product Managers

Software engineers who want to build LLM-powered chatbots and agents, or break into AI engineering more generally

Data Scientists/Engineers who want to build their own LLM-powered apps

Product Managers who want to understand AI engineering from the coding perspective

Walk away with the core skills, tools, and support you need to operate like a modern PM

Cohort 23rd March 2026

20+ YoE | 8+ Yrs Teaching | 5K Students 

Linktree

Kajabi

Expedia Group

Harvard University

Melbourne Business School

David Wang (Product Dave)

Global Product Leader with 20+ Years of Experience from Hyper-Growth Companies

This cohort is designed for students who are based in Australia and the US West Coast timezones

Cohort 12PM AEST / 7PM PST 

Cohort 3 May 2026

Who’s this for?This course is for people trying to break into product management, unofficial PMs already doing the work without the title, and new PMs who want stronger foundations.Each cohort is capped at 12 motivated learners. Not a 500-person course where you're lost in the noise. Weekly live workshops and direct feedback. That's how you learn.- Why this course?AI has made building and execution easier. But speed is not judgement. Most courses teach prompts without teaching the PM foundations that matter in interviews and on the job. This course gives you both.You’ll learn how to think like a PM, break down customer and business problems, define personas and JTBD, connect ideas to metrics, structure AI-assisted PRDs, prioritise work, and influence without authority.-What you'll get:<ul><li>Certification from Product Academy</li><li>Weekly live workshops so you build real skills fast</li><li>1:1 coaching on insider knowledge on hiring PMs</li><li>A complete Miro board of PM tools — market dynamics, customer segmentation, feature maps, prioritisation, roadmapping, etc</li><li>AI prompt library to speed up every step of product work</li><li>Career Happiness Refund: If you're not happy, you'll get 100% refund anytime in your career.</li></ul>

Decide What To Build, Get Customers, and Drive Outcomes with AI PM Skills

Master the foundations of Product Thinking in the age of AI

Ground Product Decisions in Business and Customer Needs with AI Tools

Influence Executives with Data-Driven Prioritization and Planning

Build Working AI Product with Clear Product Requirements

Measure the Success of Your Product using Clear Metrics

Product thinking needs real workplace judgement. This course promotes learning from each other's real-life experiences. 

Must be a Mid-Career Professional | 4+ Years of WORKING experience

We use real examples from tech companies and tech products; otherwise, you'll get lost in the concepts.

Must work in tech or tech-related products

Unofficial PMs - Engineers, Designers, Program Managers, BAs, and SalesFolks who touches product work and wants to define WHAT to build

New or Aspiring PMsPeople moving into PM who want practical product thinking, AI workflows, and a real project to show their ability.

PMs who needs to stay relevant in the AI eraCurrent PMs who want to remove low-level work and use AI to operate with more impact.

Working with LLMs

Artificial Intelligence

For Product Managers

For Data Scientists

Working with LLMs

Cohort-based courses

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