project management

The Product Management for AI & Data Science Course is designed for aspiring Product Managers who want to learn AI and Data Science. The course is ideal for beginners as it begins with the fundamentals of Product Management for AI and data.

The instructor of the course, Danielle Thé, is a Senior Product Manager and has years of experience working in the digital sector as a Product Manager for companies like Google and Deloitte Digital. The courses are usually available at INR 3,499 on Udemy but you can click now to get 87% off and get The Product Management for AI & Data Science Course for INR 449.

Who all can opt for this course?

  • If you want to learn more about the topic of AI and Data Science, or if you want to become a Product Manager, you should enroll in this course.
  • If you desire a successful job, you should take this course.
  • The training is excellent for novices as well because it starts with the basics and gradually develops your skills.

Course Highlights

Key HighlightsDetails
Registration LinkApply Now!
PriceINR 449 (INR 3,49987 % off
Duration04 hours
Rating4.6/5
Student Enrollment13,408 students
Instructor365 Careers https://www.linkedin.com/in/365careers
Topics CoveredProduct Management for AI and Data, Business Strategy for AI and Data, User Experience, Data Management
Course LevelIntermediate
Total Student Reviews2,477

Learning Outcomes

  • This course offers comprehensive insight for a product manager interested in the fields of Data Science and AI.
  • Learn how to be the bridge between business needs and technically oriented Data Science and AI personnel.
  • Find out what a Product Manager does and what makes a Project Manager different from a Product Manager.
  • Understand the difference between Data Analysis and Data Science
  • Know the difference between an AI and an algorithm
  • Differentiate the various kinds of Machine Learning
  • Plan and execute a business strategy for AI and Data
  • Conduct a SWOT analysis
  • Study the creation and testing of hypotheses
  • Acquire user experience for AI and data science skills
  • Source data for your projects and be aware of the management requirements
  • Investigate an AI or data science project’s whole lifespan within a corporation
  • Learn how to manage teams in Data Science and AI
  • Address bias, privacy, and ethics

Course Content

S.No.Module (Duration)Topics
1.Intro to Product Management for AI & Data (22 minutes)Introduction
Course Overview
Growing Importance of an AI & Data PM
The Role of a Product Manager
Differentiation of a PM in AI & Data
Product Management vs. Project Management
2.Key Technological Concepts for AI & Data (34 minutes)A Product Manager as an Analytics Translator
Data Analysis vs. Data Science
A Traditional Algorithm vs. AI
AI vs Traditional Algorithm
Explaining Machine Learning
Explaining Deep Learning
When to use Machine Learning vs. Deep Learning
Machine Learning or Deep Learning
Supervised, Unsupervised, & Reinforcement Learning
Supervised Learning, Unsupervised Learning or Reinforcement Learning
3.Business Strategy for AI & Data (24 minutes)AI Business Model Innovations
When to Use AI
SWOT Analysis
Building a Hypothesis
Testing a Hypothesis
AI Business Canvas
Dr.DermaApp Case Study
4.User Experience for AI & Data (21 minutes)User Experience for Data & AI
Getting to the Core Problem
User Research Methods
Developing User Personas
Prototyping with AI
5.Data Management for AI & Data (30 minutes)Data Growth Strategy
Open Data
Company Data
Crowdsourcing Labeled Data
New Feature Data
Acquisition/Purchase Data Collection
Data Collection Needs Matching
Databases, Data Warehouses, & Data Lakes
6.Product Development for AI & Data (27 minutes)AI Flywheel Effect
Top & Bottom Problem Solving
Product Ideation Techniques
Complexity vs. Benefit Prioritization
MVPs & MVDs (Minimum Viable Data)
Agile & Data Kanban
7.Building The Model (26 minutes)Who Should Buid Your Model
Enterpise AI
Machine Learning as a Service (MLaaS)
In-House AI & The Machine Learning Lifecycle
Timelines & Diminishing Returns
Setting a Model Performance Metric
8.Evaluating Performance (21 minutes)Dividing Test Data
The Confusion Matrix
Precision, Recall & F1 Score
Optimizing for Experience
Error Recovery
AutoBikerz Case Study
9.Deployment & Continuous Improvement (20 minutes)Model Deployment Methods
Monitoring Models
Selecting a Feedback Metric
User Feedback Loops
Shadow Deployments
10.Managing Data Science & AI Teams (21 minutes)AI Hierarchy of Needs
AI Within an Organization
Roles in AI & Data Teams
Managing Team Workflow
Dual & Triple-Track Agile
11.Communication (23 minutes)Internal Stakeholder Management
Setting Data Expectations
Active Listening & Communication
Compelling Presentations with Storytelling
Running Effective Meetings
12.Ethics, Privacy, & Bias (18 minutes)AI User Concerns
Bad Actors & Security
AI Amplifying Human Bias
Data Laws & Regulations

Resources Required

No prior experience or knowledge is required. The instructor begins with the basics of Product Management.

Featured Review

Neethi Ganesh Palanisamy (5/5): The presenter is able to connect with the listener with broad industry knowledge. Jack of All Trades, Master of None is a very good analogy use to describe a Product Manager!!!

Pros

  • Madhusudhan Pamula (5/5): This was the best course I have taken for Product Management.
  • Dinesh Vuppalapu (5/5): Best course for someone who would like to build their career in the field of AI/ML Product Manager
  • Mohammed A Raheem (5/5): This best course foundation of data science and communication among team members
  • Harry Shea (5/5): The explanation of AI concepts in this course are the best that I’ve come across online.

Cons

  • Chandan Kumar G. (2.5/5): A more pictorial representation would be more efficient.
  • Scott C. (2.5/5): There are a lot of typos, and not that much material that go beyond just watching the instructor talk. As a data scientist, there are also a lot of statements that I disagree with and I worry could be confusing product managers in their work. That said, I do appreciate the distinctions that were made between typical product management and PM for data science.
  • Mal P. (1.5/5): on mobile every time I go from one lesson to the next (or sometimes in the middle of a lesson) it will say that there was an error. I have to back out of it, then click back into it. I’m at lesson 38 now. I’ve probably done this 20 times.
  • Bharghvi P. (1/5): It is very monotonous and unclear. Not interesting at all.

About the Author

The instructor of this course is 365 Careers who are creating opportunities for Data Science and Finance students. With a 4.6 instructor rating and 6,18,572 reviews on Udemy, they offer 91 courses and have taught 2,143,657 students so far.

  • On Udemy, 365 Careers is the top-selling provider of courses in Business, Finance, and Data Science.
  • In 210 different countries, more than 2,000,000 students have taken the company’s courses.
  • People who have finished 365 Careers training now work at renowned companies like Apple, PayPal, and Citibank.
  • On Udemy right now, 365 focuses on the following subjects: Finance, Data Science, Office Productivity, Business, and Blockchain.
  • The courses offered by 365 Careers are the ideal place to start whether you want to work as a Financial Analyst, Data Scientist, Business Analyst, Data Analyst, Business Intelligence Analyst, Business Executive, Finance Manager, FP&A Analyst, Investment Banker, or Entrepreneur.

Comparison Table

ParametersThe Product Management for AI & Data Science Course 2023Advanced Product Management: Vision, Strategy & MetricsAdvanced Product Management: Leadership & Communication
OffersINR 455 (INR 3,499) 87% offINR 455 (INR 3,499) 87% offINR 455 (INR 3,499) 87% off
Duration5 hours5.5 hours4.5 hours
Rating4.6 /54.5 /54.5 /5
Student Enrollments13,40541,33415,836
Instructors365 CareersCole MercerCole Mercer
Register HereApply Now!Apply Now!Apply Now!

Leave feedback about this

  • Rating