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Kirsten Gokay,
Meeta Dash,
Alyssa Simpson-Rochwerger,
Andrea Butkovic,
and
Kiran Vajapey
Learn the foundations of AI and how these technologies can learn from data and improve or inform product development.
Register for this course and see more details by visiting:
OpenCourser.com/course/pr3qca/introduction
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What's inside
Syllabus
Welcome to this course on AI for Product Managers! Learn about the course structure and resources available to you.
Get an overview of AI and machine learning and where they are used in industry. This lesson covers terminology and applications of supervised learning, unsupervised learning, and neural networks.
How do you build a successful AI product? Learn which kinds of narrow business cases can stand to benefit the most from machine learning, and identify the components of an effective, AI product team.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores the foundations of AI, which is standard in industry
Taught by industry experts with proven experience
Develops product management skills within an AI context
Suitable for learners with a background in product management
Examples and case studies primarily focus on industry applications
Does not cover the full lifecycle of AI product development
Save this course
Save Introduction to AI in Business to your list so you can find it easily later:
Save
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introduction to AI in Business with these
activities:
Read 'Artificial Intelligence: A Modern Approach'
Show steps
Gain a comprehensive understanding of the foundations and applications of AI.
View
Melania
on Amazon
Show steps
-
Read the book thoroughly, taking notes and highlighting important concepts
-
Complete the exercises and practice problems in the book
-
Summarize key chapters and present them to peers or stakeholders
Review Introduction to AI
Show steps
Deepen understanding of core concepts like supervised and unsupervised learning.
Browse courses on
AI
Show steps
-
Reread relevant sections of your AI textbook
-
Take practice quizzes or complete practice problems on supervised learning
-
Review case studies of successful AI product implementations
Attend an AI Product Development Workshop
Show steps
Gain hands-on experience and learn from experts in the field of AI product development.
Show steps
-
Research and identify relevant AI product development workshops
-
Attend the workshop and actively participate in discussions and exercises
-
Follow up with workshop organizers or speakers to continue learning and networking
Three other activities
Expand to see all activities and additional details
Show all six activities
Explore Machine Learning Algorithms
Show steps
Strengthen understanding of how machine learning algorithms work and their applications.
Browse courses on
Machine Learning Algorithms
Show steps
-
Follow online tutorials on different machine learning algorithms
-
Implement a simple machine learning algorithm from scratch
-
Participate in online forums or discussion groups on machine learning algorithms
Participate in AI Product Development Discussions
Show steps
Engage with peers to exchange ideas and perspectives on AI product development.
Show steps
-
Join online or in-person discussion groups or forums focused on AI product development
-
Actively participate in discussions, share knowledge, and seek feedback from peers
-
Organize or lead discussions on specific AI product development topics
Develop an AI Product Roadmap
Show steps
Gain practical experience in planning and managing an AI product's lifecycle.
Show steps
-
Analyze market trends and customer needs to identify opportunities for AI products
-
Develop a roadmap that outlines the key milestones, timelines, and resources needed to bring an AI product to market
-
Present the roadmap to stakeholders and get feedback
Read 'Artificial Intelligence: A Modern Approach'
Show steps
Gain a comprehensive understanding of the foundations and applications of AI.
View
Melania
on Amazon
Show steps
Show steps
Show steps
- Read the book thoroughly, taking notes and highlighting important concepts
- Complete the exercises and practice problems in the book
- Summarize key chapters and present them to peers or stakeholders
Review Introduction to AI
Show steps
Deepen understanding of core concepts like supervised and unsupervised learning.
Browse courses on
AI
Show steps
Show steps
Show steps
- Reread relevant sections of your AI textbook
- Take practice quizzes or complete practice problems on supervised learning
- Review case studies of successful AI product implementations
Attend an AI Product Development Workshop
Show steps
Gain hands-on experience and learn from experts in the field of AI product development.
Show steps
Show steps
Show steps
- Research and identify relevant AI product development workshops
- Attend the workshop and actively participate in discussions and exercises
- Follow up with workshop organizers or speakers to continue learning and networking
Three other activities
Expand to see all activities and additional details
Show all six activities
Explore Machine Learning Algorithms
Show steps
Strengthen understanding of how machine learning algorithms work and their applications.
Browse courses on
Machine Learning Algorithms
Show steps
Show steps
Show steps
- Follow online tutorials on different machine learning algorithms
- Implement a simple machine learning algorithm from scratch
- Participate in online forums or discussion groups on machine learning algorithms
Participate in AI Product Development Discussions
Show steps
Engage with peers to exchange ideas and perspectives on AI product development.
Show steps
Show steps
Show steps
- Join online or in-person discussion groups or forums focused on AI product development
- Actively participate in discussions, share knowledge, and seek feedback from peers
- Organize or lead discussions on specific AI product development topics
Develop an AI Product Roadmap
Show steps
Gain practical experience in planning and managing an AI product's lifecycle.
Show steps
Show steps
Show steps
- Analyze market trends and customer needs to identify opportunities for AI products
- Develop a roadmap that outlines the key milestones, timelines, and resources needed to bring an AI product to market
- Present the roadmap to stakeholders and get feedback
Career center
Learners who complete Introduction to AI in Business will develop knowledge and skills
that may be useful to these careers:
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. They work with engineers, designers, and marketers to ensure that products meet customer needs and are successful in the marketplace. This course can help Product Managers build a foundation in AI and understand how these technologies can be used to improve product development. For example, the course covers how to identify the right business cases for AI, how to build and manage an AI product team, and how to measure the success of AI products.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. They work with large datasets to identify trends and patterns, and they develop models to predict future outcomes. This course can help Data Scientists build a foundation in AI and understand how these technologies can be used to improve their work. For example, the course covers how to use AI to automate data analysis tasks, how to build and train machine learning models, and how to interpret the results of AI models.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. They work with data scientists and product managers to ensure that models are accurate and efficient. This course can help Machine Learning Engineers build a foundation in AI and understand how these technologies can be used to improve their work. For example, the course covers how to choose the right machine learning algorithms, how to train and evaluate machine learning models, and how to deploy models to production.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with product managers and other engineers to ensure that applications are reliable, efficient, and meet customer needs. This course can help Software Engineers build a foundation in AI and understand how these technologies can be used to improve their work. For example, the course covers how to use AI to automate software development tasks, how to build and train machine learning models, and how to integrate AI into software applications.
Business Analyst
Business Analyst
Business Analysts help organizations understand their business needs and develop solutions to meet those needs. They work with stakeholders across the organization to gather requirements, analyze data, and develop recommendations. This course can help Business Analysts build a foundation in AI and understand how these technologies can be used to improve their work. For example, the course covers how to use AI to automate data analysis tasks, how to build and train machine learning models, and how to use AI to identify trends and patterns in data.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. They work with portfolio managers and other investment professionals to develop investment strategies and make investment decisions. This course can help Quantitative Analysts build a foundation in AI and understand how these technologies can be used to improve their work. For example, the course covers how to use AI to automate data analysis tasks, how to build and train machine learning models, and how to use AI to identify trends and patterns in data.
Market Research Analyst
Market Research Analyst
Market Research Analysts conduct research to understand consumer behavior and market trends. They work with marketing and product development teams to develop new products and services and to improve existing ones. This course can help Market Research Analysts build a foundation in AI and understand how these technologies can be used to improve their work. For example, the course covers how to use AI to automate data analysis tasks, how to build and train machine learning models, and how to use AI to identify trends and patterns in data.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. They work with operations managers and other decision-makers to develop strategies to improve efficiency and productivity. This course can help Operations Research Analysts build a foundation in AI and understand how these technologies can be used to improve their work. For example, the course covers how to use AI to automate data analysis tasks, how to build and train machine learning models, and how to use AI to identify trends and patterns in data.
Management Consultant
Management Consultant
Management Consultants help organizations improve their performance. They work with clients to identify problems, develop solutions, and implement change. This course can help Management Consultants build a foundation in AI and understand how these technologies can be used to improve their work. For example, the course covers how to use AI to automate data analysis tasks, how to build and train machine learning models, and how to use AI to identify trends and patterns in data.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make recommendations on investment and business decisions. They work with portfolio managers and other investment professionals to develop investment strategies and make investment decisions. This course may be useful for Financial Analysts who want to learn how to use AI to automate data analysis tasks, how to build and train machine learning models, and how to use AI to identify trends and patterns in data.
Actuary
Actuary
Actuaries use mathematical and statistical models to assess risk and uncertainty. They work with insurance companies and other financial institutions to develop products and services that protect against financial risks. This course may be useful for Actuaries who want to learn how to use AI to automate data analysis tasks, how to build and train machine learning models, and how to use AI to identify trends and patterns in data.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. They work with researchers, businesses, and governments to solve problems and make decisions. This course may be useful for Statisticians who want to learn how to use AI to automate data analysis tasks, how to build and train machine learning models, and how to use AI to identify trends and patterns in data.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. They work with businesses and organizations to improve decision-making and solve problems. This course may be useful for Data Analysts who want to learn how to use AI to automate data analysis tasks, how to build and train machine learning models, and how to use AI to identify trends and patterns in data.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to help businesses make better decisions. They work with data analysts and other business professionals to identify trends and patterns, and to develop strategies to improve business performance. This course may be useful for Business Intelligence Analysts who want to learn how to use AI to automate data analysis tasks, how to build and train machine learning models, and how to use AI to identify trends and patterns in data.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand consumer behavior and market trends. They work with marketing and product development teams to develop new products and services and to improve existing ones. This course may be useful for Marketing Analysts who want to learn how to use AI to automate data analysis tasks, how to build and train machine learning models, and how to use AI to identify trends and patterns in data.
For more career information including salaries, visit:
OpenCourser.com/course/pr3qca/introduction
Reading list
We've selected 13 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to AI in Business.
Save
Comprehensive guide to deep learning. It covers the latest research in the field and provides a detailed explanation of deep learning algorithms.
Provides a comprehensive overview of AI in practice. It good choice for those who want to learn more about the practical aspects of AI.
Provides a comprehensive overview of statistical learning methods. It good choice for those who want to learn more about the mathematical foundations of machine learning.
Provides a comprehensive overview of pattern recognition and machine learning. It good choice for those who want to learn more about the mathematical foundations of AI.
Provides a comprehensive overview of machine learning from a probabilistic perspective. It good choice for those who want to learn more about the mathematical foundations of AI.
Provides a comprehensive overview of AI for business. It good choice for those who want to learn more about the practical aspects of AI.
Provides a comprehensive overview of reinforcement learning. It good choice for those who want to learn more about the mathematical foundations of AI.
Save
Provides a comprehensive overview of computer vision algorithms and applications. It good choice for those who want to learn more about the practical aspects of AI.
Provides a comprehensive overview of speech and language processing. It good choice for those who want to learn more about the practical aspects of AI.
Save
Provides a comprehensive overview of data mining techniques. It good choice for those who want to learn more about the practical aspects of machine learning.
Provides a comprehensive overview of AI. It good starting point for those who want to learn more about the basics of AI.
Provides a comprehensive overview of AI. It good starting point for those who want to learn more about the basics of AI.
Provides a comprehensive overview of AI, machine learning, and deep learning. It good starting point for those who want to learn more about the basics of AI.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/pr3qca/introduction
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Time
150 hours
Level
Introductory
Via
Udacity
Instructors
Kirsten Gokay
Meeta Dash
Alyssa Simpson-Rochwerger
Andrea Butkovic
Kiran Vajapey
Language
English
Good to know
Explores the foundations of AI, which is standard in industry
Taught by industry experts with proven experience
Develops product management skills within an AI context
Suitable for learners with a background in product management
Examples and case studies primarily focus on industry applications
Does not cover the full lifecycle of AI product development
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