The Product Management for AI & Data Science Course

BY
Udemy

Begin the journey of becoming a successful product manager with The Product Management for AI & Data Science Course certification course.

Lavel

Beginner

Mode

Online

Fees

₹ 3999

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

The Product Management for AI & Data Science Course certification is a small online course that is both prepared and instructed by Udemy. This  Udemy Business collection course does not require any pre-enrolment criteria so anyone wanting to receive an overview regarding being a product manager in the data science and AI field is welcome to attend this certification course. 

The Product Management for AI & Data Science Course training on Udemy allows free access to the course once the candidates have attained the completion certificate. This 4.6 rated course is instructed by renowned 365 Careers and Danielle Thé who have been part of the data industry for years now. The course includes 67 lectures that are broken down into biteable video content of a total of 5 hours only. The course will be serving as a bridge between technologies like artificial intelligence, and data science, and business needs.

The highlights

  • 5 hours video sessions
  • Fully online programme
  • Full lifetime access
  • Accessible on mobile and tablet
  • Certificate of completion
  • 30-day guarantee of money back

Program offerings

  • 5 hours video
  • 12 sections
  • 6 downloadable
  • Lifetime course access
  • Content completion certificate
  • Assignments
  • 67 lectures

Course and certificate fees

Fees information
₹ 3,999

The Product Management for AI & Data Science Course certification fee is Rs. 3,999

The Product Management for AI & Data Science Course Fee Structure

Description

Amount in INR

Programme Fee

Rs. 3,999

certificate availability

Yes

certificate providing authority

Udemy

Who it is for

Here are people who can seriously attempt this course:

  • If people want to learn the fundamentals and build up their career by learning the skills then this course is for this group.
  • Candidates who are looking for an amped up career as product managers.
  • The motto of the candidates must be learning about the nitty gritties of AI and data science.

Eligibility criteria

Educational Qualification

  • No prerequisite educational qualification is required.

Certification Qualifying Details

  • The Product Management for AI & Data Science Course certification by Udemy can be attained when the entire course is watched, and assignments are completed.

What you will learn

Knowledge of product management Knowledge of artificial intelligence Machine learning Data science knowledge

With The Product Management for AI & Data Science Course certification syllabus, the candidates will learn:

  • Identify what role a project manager has, and the difference between a project manager, and a product.
  • Understand the difference between an AI, and its algorithm.
  • The students can differentiate between data science and data analysis.
  • Machine learning has different types that may be understood by the participants.
  • AI and data science need strategies that can be designed technically by the participants.
  • The SWOT analysis of products can be performed by the students.
  • Candidates will learn to prepare a test and its hypothesis.
  • Both data science and AI skills’ user experience may be acquired.
  • The aspirants may understand what is the right lifecycle of a project under AI or data science in a company.
  • The teams of data science and AI can be managed by the candidates.
  • Issues like privacy, ethics, and bias can be addressed by the participants.

The syllabus

Intro to Product Management for A1 & Data

Key Technological Concepts for AI & Data

  • A Product Manager as an Analytics Translator
  • Data Analysis vs. Data Science
  • A Traditional Algorithms 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

Business Strategy for AI & Data

  • AI Business Model Innovations
  • When to Use AI
  • SWOT Analysis
  • Building a Hypothesis
  • Testing a Hypothesis
  • AI Business Canvas
  • Dr. DermaApp Case Study

User Experience for AI & Data

  • User Experience for Data & AI
  • Getting to the Core Problem
  • User Research Methods
  • Developing User Personas
  • Prototyping with AI

Data Management for AI & Data

  • 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

Product Development for AI & Data

  • AI Flywheel Effect
  • Top & Bottom Problem Solving
  • Product Ideation Techniques
  • Complexity vs. Benefit Prioritization
  • MVPs & MVDs (Minimum Viable Data)
  • Agile & Data Kanban

Building The Model

  • Who Should Build Your Model
  • Enterprise AI
  • Machine Learning as a Service (MLaaS)
  • In-House AI & The Machine Learning Lifecycle
  • Timelines & Diminishing Returns
  • Setting a Model Performance Metric

Evaluating Performance

  • Dividing Test Data
  • The Confusion Matrix
  • Precision, Recall & F1 Score
  • Optimizing for Experience
  • Error Recovery
  • AutoBikerz Case Study

Deployment & Continuous Improvement

  • Model Deployment Methods
  • Monitoring Models
  • Selecting a Feedback Metric
  • User Feedback Loops
  • Shadow Deployments

Managing Data Science & AI Teams

  • AI Hierarchy of Needs
  • AI Within an Organization
  • Roles in AI & Data Teams
  • Managing Team Workflow
  • Dual & Triple-Track Agile

Communication

  • Internal Stakeholder Management
  • Setting Data Expectations
  • Active Listening & Communication
  • Compelling Presentations with Storytelling
  • Running Effective Meetings

Ethics, Privacy & Bias

  • AI User Concerns
  • Bad Actors & Security
  • AI Amplifying Human Bias
  • Data Laws & Regulations

Admission details

Here is The Product Management for AI & Data Science Course classes admission process:

Step 1: Visit the official site: https://www.udemy.com/course/the-product-management-for-data-science-ai-course/.

Step 2: The students must either click the ‘Buy Now’ button or the ‘Add to Cart’ button.

Step 3: After submitting the details, and the fee, the candidates can buy the course.

Step 4: As the course is bought, admission is given, and the students can learn.

How it helps

Here is The Product Management for AI & Data Science Course certification benefits:

  • The candidates can build their careers as product managers in the field of data science, and artificial intelligence.
  • In a very short time, this course certificate can be earned, and free lifetime access to the materials of study is also available.
  • This certificate course will be teaching everything from the basic level so this is beginner-friendly.
  • The course will aim towards the preparation of an interesting career path.

Instructors

Ms Danielle
Senior Product Manager
Freelancer

Other Masters

FAQs

Is there any gifting possibility for this course?

If required a person may gift this programme to their family or friends.

How many sections are there in The Product Management for AI & Data Science Course online certification?

There are 12 sections that one can find on the Udemy website.

Can this online certification be accessed both on the television, and mobile browser?

The course materials can be played both through mobile, and television screens.

Is this programme designed for the ‘Udemy Business’ collection?

Yes, this course is a part of the ‘Udemy Business’ collection.

Can The Product Management for AI & Data Science Course online course be previewed before enrolment?

Yes, this product management online course can be previewed.

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