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Anne Rynearson,
JJ Miclat,
and
Vaishali Agarwal
Enhance your data product management skills with our in-depth online course. Learn to utilize data science, ML, and AI for effective decision-making. Enroll now
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- Tableau proficiency
- Basic SQL
You will also need to be able to communicate fluently and professionally in written and spoken English.
Register for this course and see more details by visiting:
OpenCourser.com/course/nkl8dy/applying
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What's inside
Syllabus
Find out about the rise of the data product manager with the explosion of information in recent years.
Learn about the granularity, distribution and modeling of data, key areas to utilize in your data PM skill set.
Read more
Syllabus
Find out about the rise of the data product manager with the explosion of information in recent years.
Learn about the granularity, distribution and modeling of data, key areas to utilize in your data PM skill set.
Read more
Establishing trends, enriching data, and visualizing that data are the next important areas in your data product manager journey.
You are responsible for bringing the first flying car taxi service to market by analyzing data and building a product proposal.
Learn how to set product objectives and strategy to drive your desired results.
Your product proposal is a crucial piece of getting a product to market - learn here how to synthesize and design your presentation.
Building on your previous research for a Flying Car Business Case, determine KPIs and an MVP en route to a fully fledged product proposal.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides a comprehensive introduction to data product management skills
Taught by industry experts who have extensive experience in data product management
Covers the latest trends and techniques in data product management
Includes hands-on exercises and real-world case studies to help you apply your learning
Provides a strong foundation for those who want to pursue a career in data product management
Save this course
Save Applying Data Science to Product Management to your list so you can find it easily later:
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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 Applying Data Science to Product Management with these
activities:
Attend a Data Science Meetup
Show steps
Connect with other professionals in the field and learn about industry trends and best practices.
Browse courses on
Data Science
Show steps
-
Find a data science meetup near you.
-
Attend the meetup and introduce yourself to other participants.
-
Listen to speakers and engage in discussions.
Gather Data Product Management Resources
Show steps
Organize and consolidate relevant resources to support your learning throughout the course.
Show steps
-
Identify and gather articles, books, and online resources on data product management.
-
Organize the resources into a structured folder system or bookmarking tool.
-
Review the resources regularly to reinforce your understanding.
Review Data Science for Business
Show steps
Review key concepts in data science and machine learning to reinforce your understanding of the course materials.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
-
Read the book and take notes on key concepts and definitions.
-
Summarize the main arguments and examples in the book.
-
Create a mind map or concept diagram to visualize the relationships between key ideas.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve Data Analysis Exercises
Show steps
Reinforce your data analysis skills by completing exercises and challenges.
Browse courses on
Data Analysis
Show steps
-
Find online resources or textbooks with data analysis exercises.
-
Solve the exercises using SQL, Tableau, or other data analysis tools.
-
Review your answers and identify areas for improvement.
Follow TensorFlow Tutorials
Show steps
Enhance your practical knowledge of machine learning and deep learning by working through guided tutorials.
Browse courses on
Machine Learning
Show steps
-
Choose a TensorFlow tutorial that aligns with your learning goals.
-
Follow the step-by-step instructions and build the model or functionality described in the tutorial.
-
Experiment with different parameters and hyperparameters to optimize the model's performance.
Build a Data Visualization Dashboard
Show steps
Gain practical experience in data visualization and dashboard design.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset and define the key metrics and insights to be displayed.
-
Design the dashboard layout and select appropriate chart types.
-
Build the dashboard using Tableau or other data visualization tools.
-
Test and refine the dashboard based on feedback from stakeholders.
Write a Blog Post on Data Product Management
Show steps
Develop your understanding of data product management and showcase your writing skills.
Show steps
-
Research and gather information on the topic.
-
Outline the key points and structure of your blog post.
-
Write the first draft.
-
Review and edit your work.
-
Publish your blog post on a relevant platform.
Develop a Data Product Proposal
Show steps
Demonstrate your ability to define a data product proposal and outline its value proposition.
Show steps
-
Identify a problem or opportunity that a data product could address.
-
Define the target audience and user needs.
-
Develop a solution concept and outline its key features and functionality.
-
Build a business case that quantifies the potential benefits and ROI of the product.
Attend a Data Science Meetup
Show steps
Connect with other professionals in the field and learn about industry trends and best practices.
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Find a data science meetup near you.
- Attend the meetup and introduce yourself to other participants.
- Listen to speakers and engage in discussions.
Gather Data Product Management Resources
Show steps
Organize and consolidate relevant resources to support your learning throughout the course.
Show steps
Show steps
Show steps
- Identify and gather articles, books, and online resources on data product management.
- Organize the resources into a structured folder system or bookmarking tool.
- Review the resources regularly to reinforce your understanding.
Review Data Science for Business
Show steps
Review key concepts in data science and machine learning to reinforce your understanding of the course materials.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
Show steps
Show steps
- Read the book and take notes on key concepts and definitions.
- Summarize the main arguments and examples in the book.
- Create a mind map or concept diagram to visualize the relationships between key ideas.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve Data Analysis Exercises
Show steps
Reinforce your data analysis skills by completing exercises and challenges.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Find online resources or textbooks with data analysis exercises.
- Solve the exercises using SQL, Tableau, or other data analysis tools.
- Review your answers and identify areas for improvement.
Follow TensorFlow Tutorials
Show steps
Enhance your practical knowledge of machine learning and deep learning by working through guided tutorials.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Choose a TensorFlow tutorial that aligns with your learning goals.
- Follow the step-by-step instructions and build the model or functionality described in the tutorial.
- Experiment with different parameters and hyperparameters to optimize the model's performance.
Build a Data Visualization Dashboard
Show steps
Gain practical experience in data visualization and dashboard design.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset and define the key metrics and insights to be displayed.
- Design the dashboard layout and select appropriate chart types.
- Build the dashboard using Tableau or other data visualization tools.
- Test and refine the dashboard based on feedback from stakeholders.
Write a Blog Post on Data Product Management
Show steps
Develop your understanding of data product management and showcase your writing skills.
Show steps
Show steps
Show steps
- Research and gather information on the topic.
- Outline the key points and structure of your blog post.
- Write the first draft.
- Review and edit your work.
- Publish your blog post on a relevant platform.
Develop a Data Product Proposal
Show steps
Demonstrate your ability to define a data product proposal and outline its value proposition.
Show steps
Show steps
Show steps
- Identify a problem or opportunity that a data product could address.
- Define the target audience and user needs.
- Develop a solution concept and outline its key features and functionality.
- Build a business case that quantifies the potential benefits and ROI of the product.
Career center
Learners who complete Applying Data Science to Product Management will develop knowledge and skills
that may be useful to these careers:
Data Product Manager
Data Product Manager
Data Product Managers are responsible for the development and management of data products, ensuring that they meet the needs of users and businesses. This course provides a foundation in data science, machine learning, and AI, which are essential skills for Data Product Managers. The course also covers topics such as data visualization, product management, and business strategy, which are all relevant to this role. By taking this course, you will gain the skills and knowledge necessary to succeed as a Data Product Manager.
Product Manager
Product Manager
Product Managers are responsible for the development and management of products, ensuring that they meet the needs of users and businesses. This course provides a foundation in data science, machine learning, and AI, which are increasingly important for Product Managers. The course also covers topics such as data visualization, product management, and business strategy, which are all relevant to this role. By taking this course, you will gain the skills and knowledge necessary to succeed as a Product Manager.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, analyzing, and interpreting data to help businesses make informed decisions. This course provides a foundation in data science, machine learning, and AI, which are essential skills for Data Analysts. The course also covers topics such as data visualization and data management, which are both relevant to this role. By taking this course, you will gain the skills and knowledge necessary to succeed as a Data Analyst.
Data Scientist
Data Scientist
Data Scientists are responsible for developing and implementing data-driven solutions to business problems. This course provides a foundation in data science, machine learning, and AI, which are essential skills for Data Scientists. The course also covers topics such as data analysis, data visualization, and data management, which are all relevant to this role. By taking this course, you will gain the skills and knowledge necessary to succeed as a Data Scientist.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for developing and deploying machine learning models. This course provides a foundation in data science, machine learning, and AI, which are essential skills for Machine Learning Engineers. The course also covers topics such as data engineering, model deployment, and model monitoring, which are all relevant to this role. By taking this course, you will gain the skills and knowledge necessary to succeed as a Machine Learning Engineer.
Business Analyst
Business Analyst
Business Analysts are responsible for analyzing business processes and identifying opportunities for improvement. This course provides a foundation in data science, machine learning, and AI, which can be helpful for Business Analysts in understanding data-driven insights. The course also covers topics such as data visualization and business strategy, which are both relevant to this role. By taking this course, you may gain the skills and knowledge necessary to succeed as a Business Analyst.
Software Engineer
Software Engineer
Software Engineers are responsible for developing and maintaining software applications. This course provides a foundation in data science, machine learning, and AI, which can be helpful for Software Engineers in understanding data-driven insights. The course also covers topics such as data visualization and data management, which are both relevant to this role. By taking this course, you may gain the skills and knowledge necessary to succeed as a Software Engineer.
Data Engineer
Data Engineer
Data Engineers are responsible for building and maintaining data pipelines. This course provides a foundation in data science, machine learning, and AI, which are increasingly important for Data Engineers. The course also covers topics such as data management, data quality, and data security, which are all relevant to this role. By taking this course, you may gain the skills and knowledge necessary to succeed as a Data Engineer.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts are responsible for developing and implementing mathematical models for financial analysis. This course provides a foundation in data science, machine learning, and AI, which can be helpful for Quantitative Analysts in understanding data-driven insights. The course also covers topics such as statistics and financial modeling, which are both relevant to this role. By taking this course, you may gain the skills and knowledge necessary to succeed as a Quantitative Analyst.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts are responsible for developing and implementing mathematical models for operational problems. This course provides a foundation in data science, machine learning, and AI, which can be helpful for Operations Research Analysts in understanding data-driven insights. The course also covers topics such as optimization and simulation, which are both relevant to this role. By taking this course, you may gain the skills and knowledge necessary to succeed as an Operations Research Analyst.
Actuary
Actuary
Actuaries are responsible for assessing and managing financial risks. This course provides a foundation in data science, machine learning, and AI, which can be helpful for Actuaries in understanding data-driven insights. The course also covers topics such as statistics and financial modeling, which are both relevant to this role. By taking this course, you may gain the skills and knowledge necessary to succeed as an Actuary.
Statistician
Statistician
Statisticians are responsible for collecting, analyzing, and interpreting data. This course provides a foundation in data science, machine learning, and AI, which can be helpful for Statisticians in understanding data-driven insights. The course also covers topics such as statistical modeling and data visualization, which are both relevant to this role. By taking this course, you may gain the skills and knowledge necessary to succeed as a Statistician.
Data Journalist
Data Journalist
Data Journalists are responsible for reporting on data-driven stories. This course provides a foundation in data science, machine learning, and AI, which can be helpful for Data Journalists in understanding data-driven insights. The course also covers topics such as data visualization and storytelling, which are both relevant to this role. By taking this course, you may gain the skills and knowledge necessary to succeed as a Data Journalist.
Market Researcher
Market Researcher
Market Researchers are responsible for collecting and analyzing data about consumer behavior. This course provides a foundation in data science, machine learning, and AI, which can be helpful for Market Researchers in understanding data-driven insights. The course also covers topics such as survey design and data analysis, which are both relevant to this role. By taking this course, you may gain the skills and knowledge necessary to succeed as a Market Researcher.
UX Researcher
UX Researcher
UX Researchers are responsible for studying user behavior and designing user interfaces. This course provides a foundation in data science, machine learning, and AI, which can be helpful for UX Researchers in understanding data-driven insights. The course also covers topics such as user research and data analysis, which are both relevant to this role. By taking this course, you may gain the skills and knowledge necessary to succeed as a UX Researcher.
For more career information including salaries, visit:
OpenCourser.com/course/nkl8dy/applying
Reading list
We've selected ten 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
Applying Data Science to Product Management.
Provides a comprehensive introduction to data science, covering the fundamental concepts, techniques, and tools used in the field. It valuable resource for anyone looking to gain a deeper understanding of data science and its applications in business.
Save
Provides a comprehensive introduction to data mining, covering the fundamental concepts, techniques, and applications of the field. It valuable resource for anyone looking to gain a deeper understanding of data mining and its potential impact on business and society.
Save
Provides a practical guide to big data, covering the fundamental concepts, techniques, and tools used in the field. It valuable resource for anyone looking to learn how to manage and analyze big data.
Provides a comprehensive introduction to Hadoop, covering the fundamental concepts, architecture, and applications of the platform. It valuable resource for anyone looking to learn how to use Hadoop to manage and analyze big data.
Provides a comprehensive introduction to Spark, covering the fundamental concepts, architecture, and applications of the platform. It valuable resource for anyone looking to learn how to use Spark to manage and analyze big data.
Save
Provides a practical introduction to data visualization, covering the fundamental concepts, techniques, and tools used in the field. It valuable resource for anyone looking to learn how to create effective data visualizations.
Provides a practical introduction to Python for data analysis, covering the fundamental concepts, libraries, and techniques used in the field. It valuable resource for anyone looking to learn how to use Python to analyze data.
Save
Provides a practical introduction to R for data science, covering the fundamental concepts, libraries, and techniques used in the field. It valuable resource for anyone looking to learn how to use R to analyze data.
Provides a practical introduction to machine learning with Python, covering the fundamental concepts, algorithms, and techniques used in the field. It valuable resource for anyone looking to learn how to use Python to build machine learning models.
Provides a practical introduction to deep learning with Python, covering the fundamental concepts, architectures, and applications of the field. It valuable resource for anyone looking to learn how to use Python to build deep learning models.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/nkl8dy/applying
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Effort
4 weeks
Level
Intermediate
Via
Udacity
Instructors
Anne Rynearson
JJ Miclat
Vaishali Agarwal
Language
English
Good to know
Provides a comprehensive introduction to data product management skills
Taught by industry experts who have extensive experience in data product management
Covers the latest trends and techniques in data product management
Includes hands-on exercises and real-world case studies to help you apply your learning
Provides a strong foundation for those who want to pursue a career in data product management
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