PRODUCT MANAGEMENT FOR AI & ML

• Instructor introduction
• Course objectives & flow
• Q&A

AI is growing! So, it’s time to learn AI and machine learning fundamentals! How are they applied in real life? How do businesses derive value from AI? Learn the role, skills & responsibilities of an AI product manager in this class.

• AI industry growth
• AI product manager vs product manager
• AI & ML basics and use cases
• Case study 

AI is the future, but it can’t solve 100% of your issues. In this class, you’ll learn how and when to use AI to solve business problems and build successful AI products.

• Case study
• When to use AI in a product
• ML vs Heuristics
• Framework for evaluation

Assignment #1: Identify a problem that can be solved with AI in a student’s field of work using the framework described in the class.

Every successful AI product starts with great data management. Learn how to use the knowledge and skills to manage data effectively.

• Data analysis & acquisition strategies
• Creating a dataset
• Data features and correlations
• Data labeling, quality & augmentation
• Demo: Insights from data

Assignment #2: Explore the features of a public dataset using the Jupyter Notebook, Python, and Pandas.

Do words like “unsupervised learning” and “neural networks” ring any bells? Learn AI terms & techniques and their possible applications as you prepare for your next role.

• Basics of AI and Machine Learning
• Supervised learning algorithms
• Unsupervised learning algorithms
• Demo: Linear Regression and K means clustering

Acquire an in-depth understanding of AI and Machine Learning.

• What is Machine Learning
• How a neural network learns from training data
• Pre-trained models vs build from scratch
• Demo: Build a neural network to identify handwritten digits

Gain a comprehensive understanding of AI models and techniques used in speech, text, and audio processing, and learn to apply these concepts in various real-world scenarios and contribute to advancements in the field.

• NLP machine learning basics
• Demo: Spam email classification using Bag of Words
• Recurrent Neural Networks
• Transformers
• Demo: Calculate sentiment of Yelp reviews using BERT transformer

Assignment #3: Deep dive into one algorithm and describe its architecture, uses, applications, etc.

In this class, you’ll obtain the skills necessary to measure the impact of AI solutions accurately and make data-driven decisions.

• Business metrics vs. model metrics
• Regression and classification metrics
• Metrics for ranking systems
• Workshop: Expedia

Assignment #4: Group Capstone project: Idea pitch

AI has great power, and you have an even greater responsibility. Learn the tools used to address issues and implement AI solutions ethically.

• Responsible AI Framework
• Tools available to address RAI concerns
• Model development lifecycle and RAI

This lesson covers all of the hands-on skills you’ll need to succeed as a PM. Everything from tools to platforms to product development concepts.

• Case study: MidJourney product strategy
• ML frameworks
• Cloud providers
• AI tools

They’re responsible for the technical development and deployment of the product you’re managing. How can you work together with them? Learn how!

• AI solution teams: engineering & production
• Deployment management
• Build vs Buy
• Demo: Transfer learning

In this class you’ll be introduced to Gen AI and key AI strategies and their applications!

• Key AI strategies
• Generative models
• GenAI for product managers

Assignment #5: Research and Analyze a Generative AI product/ tool

• Advancing your skills as a PM
• Flywheel Growth Strategy
• Workshop: Product Strategy
• Demo: Final project – AI product proposal

Self Study: Update your resume to give it the attention it deserves.