Ai Product Manager Explorer Certificate

Launch your career in AI Product Management with essential skills in Machine Learning, AI Agents, and GPT-powered apps

What you'll learn

Understand Python fundamentals to collaborate effectively with AI and engineering teams.

Learn how machine learning models work and how to frame ML use cases for product strategy.

Evaluate model performance using practical metrics like accuracy, precision, and recall.

Explore the architecture, use cases, and ethics of AI agents across industries.

Gain hands-on experience with AI agent tools like AutoGPT, LangGraph, and CrewAI.

Build and publish your own GPT-powered applications to the ChatGPT Store.

Requirements

Curiosity about AI, product strategy, and emerging technologies

Basic familiarity with how digital products are built or managed

Comfort using a computer and navigating web tools

Willingness to experiment with Python code (we guide you step-by-step!)

A modern computer with internet access for running notebooks and trying out tools

Optional: Experience working on product teams or collaborating with developers (but not required)

Description

Are you ready to break into the future of product management? The AI Product Manager Explorer Certificate is a beginner-friendly, high-impact certification program designed to equip you with the core concepts, tools, and skills needed to manage AI-powered products. Whether you're a product manager, business analyst, or entrepreneur, this course will help you transition into the rapidly growing field of AI product management – with a focus on machine learning fundamentals, AI agents, and real-world GPT applications.In today’s landscape, AI isn't just a buzzword – it's a product strategy. The AI Product Manager Explorer Certificate course gives you hands-on, practical understanding of how AI models work, what makes machine learning successful, and how to evaluate and frame AI-driven features from a business lens. Through this program, you’ll gain fluency in essential AI topics while avoiding the need to become a full-time coder or data scientist.You’ll start by building foundational technical literacy through Python programming basics – understanding syntax, data structures, and the logic that powers machine learning workflows. Next, we introduce you to the core principles of machine learning: how models are trained, evaluated, and improved. This includes feature engineering, model selection, and evaluation metrics – all framed in a product development context.As the course progresses, we shift to the future of intelligent software: AI agents and autonomous systems. You’ll explore what AI agents are, how they interact with environments, and how they are built using frameworks like LangChain, AutoGPT, and CrewAI. This is your entry into the world of generative AI product management, where systems can reason, plan, and make decisions.Finally, you’ll learn to build and publish your own custom GPTs using ChatGPT Store. This hands-on experience brings together everything you’ve learned – from ideating AI use cases to deploying GPT-powered assistants for real-world scenarios.Whether your goal is to lead AI product teams, integrate GPTs into your product roadmap, or champion AI strategy in your organization, this certificate will provide the end-to-end blueprint for AI product innovation. No PhD or engineering degree required – just a curious mind and a passion for building intelligent, impactful products.Key Takeaways:Understand the AI product lifecycle from problem framing to deploymentGain fluency in machine learning fundamentals and feature engineeringLearn how to evaluate AI model performance with product-relevant metricsExplore the architecture and applications of AI agents and GPTsBuild and publish your own custom GPTs to the ChatGPT StoreDevelop a strong conceptual foundation to collaborate with AI engineers and data scientistsJoin a global community of product thinkers driving the future of technology. Become an AI Product Manager who not only understands AI—but builds with it.

Overview

Section 1: Introduction to Course and Instructor

Lecture 1 What You’ll Learn in the AI Product Manager Explorer Certificate Course

Section 2: Python Programming Basics

Lecture 2 Day 1: Introduction to Python and Development Setup

Lecture 3 Day 2: Control Flow in Python

Lecture 4 Day 3: Functions and Modules

Lecture 5 Day 4: Data Structures (Lists, Tuples, Dictionaries, Sets)

Lecture 6 Day 5: Working with Strings

Lecture 7 Day 6: File Handling

Lecture 8 Day 7: Pythonic Code and Project Work

Section 3: Introduction to Machine Learning

Lecture 9 Day 1: Machine Learning Basics and Terminology

Lecture 10 Day 2: Introduction to Supervised Learning and Regression Models

Lecture 11 Day 3: Advanced Regression Models – Polynomial Regression and Regularization

Lecture 12 Day 4: Introduction to Classification and Logistic Regression

Lecture 13 Day 5: Model Evaluation and Cross-Validation

Lecture 14 Day 6: k-Nearest Neighbors (k-NN) Algorithm

Lecture 15 Day 7: Supervised Learning Mini Project

Section 4: Feature Engineering and Model Evaluation

Lecture 16 Day 1: Introduction to Feature Engineering

Lecture 17 Day 2: Data Scaling and Normalization

Lecture 18 Day 3: Encoding Categorical Variables

Lecture 19 Day 4: Feature Selection Techniques

Lecture 20 Day 5: Creating and Transforming Features

Lecture 21 Day 6: Model Evaluation Techniques

Lecture 22 Day 7: Cross-Validation and Hyperparameter Tuning

Section 5: AI Agents for Dummies

Lecture 23 Understanding AI Agents - How AI Agents Function

Lecture 24 Introduction to AI Agents

Lecture 25 Types of AI Agents

Lecture 26 Technologies Behind AI Agents - Machine Learning and AI Agents

Lecture 27 Natural Language Processing in AI Agents

Lecture 28 AI Agents in Robotics

Lecture 29 AI Agent Frameworks & Architectures - AI Agent Development Frameworks

Lecture 30 Overview of AutoGPT for AI Agents

Lecture 31 IBM Bee Framework for AI Agents

Lecture 32 LangGraph for Stateful AI Agents

Lecture 33 CrewAI for Collaborative AI Agents

Lecture 34 Applications of AI Agents - AI Agents in Business Operations

Lecture 35 AI Agents in Healthcare

Lecture 36 AI Agents in Financial Systems

Lecture 37 AI Agents in Entertainment

Lecture 38 AI Agents in Smart Homes and IoT

Lecture 39 Future Trends and Ethical Implications - The Future of AI Agents

Lecture 40 Ethics in AI Agent Development

Lecture 41 Legal and Regulatory Challenges for AI Agents

Lecture 42 Broader Impact of AI Agents - Social and Economic Impacts of AI Agents

Lecture 43 AI Agents and Human Collaboration

Lecture 44 The Role of AI Agents in Scientific Research

Lecture 45 AI Agents in Public Safety and National Defense

Section 6: AI Agents: A Comprehensive Overview

Lecture 46 Hands-on AutoGen | IBM Bee | LangGraph | CrewAI | AutoGPT

Lecture 47 Hands-on AutoGen

Lecture 48 Hands-on IBM Bee Framework

Lecture 49 Hands-on LangGraph

Lecture 50 Hands-on CrewAI

Lecture 51 Hands-on AutoGPT

Section 7: Creating and Publishing GPTs to ChatGPT Store

Lecture 52 Creating and Publishing GPTs to ChatGPT Store Part 1

Lecture 53 Creating and Publishing GPTs to ChatGPT Store Part 2

Lecture 54 Creating and Publishing GPTs to ChatGPT Store Part 3

Section 8: Congratulations

Lecture 55 Congratulations and Best of Luck

Aspiring product managers looking to break into AI-focused roles,Current product managers seeking to upskill in AI and machine learning,Entrepreneurs and startup founders building AI-powered products,Business analysts and strategists wanting to understand AI capabilities,UX designers and marketers collaborating with AI product teams,Professionals transitioning into tech or AI product roles from non-technical backgrounds,Anyone curious about how AI agents, GPTs, and ML models are used in real products,Leaders and managers who need to evaluate or oversee AI-driven initiatives