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Wendy Martin
As leaders in your chosen field, you need to not only know how to ask the right questions but also answer them using data-based methods. Through this class, you will be able to get to the bottom of what you really want to know, describe the associated data related to that question, and visualize the information from that data to understand and explain the results.
Read more
As leaders in your chosen field, you need to not only know how to ask the right questions but also answer them using data-based methods. Through this class, you will be able to get to the bottom of what you really want to know, describe the associated data related to that question, and visualize the information from that data to understand and explain the results.
Read more
As leaders in your chosen field, you need to not only know how to ask the right questions but also answer them using data-based methods. Through this class, you will be able to get to the bottom of what you really want to know, describe the associated data related to that question, and visualize the information from that data to understand and explain the results.
This course can be taken for academic credit as part of CU Boulder’s Master of Engineering in Engineering Management (ME-EM) degree offered on the Coursera platform. The ME-EM is designed to help engineers, scientists, and technical professionals move into leadership and management roles in the engineering and technical sectors. With performance-based admissions and no application process, the ME-EM is ideal for individuals with a broad range of undergraduate education and/or professional experience. Learn more about the ME-EM program at https://www.coursera.org/degrees/me-engineering-management-boulder.
Register for this course and see more details by visiting:
OpenCourser.com/course/zzw486/defining
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What's inside
Syllabus
Data and Measurement
Upon completion of this module, students will be able to classify types of data using measurement scales.
Working with Data in RStudio and ROIStat
Read more
Syllabus
Data and Measurement
Upon completion of this module, students will be able to classify types of data using measurement scales.
Working with Data in RStudio and ROIStat
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Covers foundational data science topics, from data acquisition to analysis, providing a well-rounded base
Utilizes industry-standard software and tools, such as RStudio and ROIStat, equipping learners with practical skills
Builds a strong foundation in probability and statistics, essential for data analysis and decision-making
Led by instructors with extensive experience in data science, ensuring up-to-date knowledge and industry insights
May require prior exposure to data science or proficiency in statistical software, suitable for learners with some background knowledge
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Reviews summary
Data fundamentals for engineering managers
According to learners, this course offers a clear and practical foundation in data definition, description, and visualization. Students gain hands-on experience with RStudio for statistical analysis and graphic representation, which is highly beneficial for applying concepts. It's especially valued for its relevance to leadership and management roles, helping professionals leverage data for better decision-making. The course also provides essential probability skills, rounding out a comprehensive introduction to data analytics for technical leaders.
Introduces ROIStat alongside RStudio for data manipulation.
"Learning to work with ROIStat provided an alternative perspective on data tools alongside RStudio."
"The course covers both RStudio and ROIStat, which gives options for different data analysis approaches."
"While RStudio was my preference, I gained exposure to ROIStat, which could be useful in some contexts."
Equips learners with foundational probability for problem-solving.
"The module on determining probabilities was crucial for understanding uncertainty in data-driven decisions."
"I now feel confident applying discrete and continuous distributions to analyze and solve problems."
"This section provided me with the necessary probabilistic thinking to better interpret complex data scenarios."
Provides strong, accessible explanations for core data principles.
"The course brilliantly demystified various data types and measurement scales, making complex ideas easy to grasp."
"I found the explanations on descriptive statistics very clear, which built a solid understanding for later modules."
"It's great for establishing a strong base in data definition and description, even without prior statistical background."
Directly applies data concepts to leadership and management decision-making.
"As a professional, I found the course's emphasis on asking the right questions and visualizing data incredibly relevant to my work."
"This course genuinely helped me understand how to leverage data for more informed strategic decisions in my role."
"It bridges the gap between raw data and actionable insights, which is crucial for engineers moving into management."
Offers valuable hands-on experience using RStudio for data tasks.
"The hands-on exercises in RStudio were invaluable; they truly helped me apply the concepts learned immediately."
"Working with real datasets in RStudio made the learning concrete and prepared me for practical data analysis."
"I really appreciated the practical demonstrations of how to use R for data visualization and descriptive analytics."
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 Defining, Describing, and Visualizing Data with these
activities:
Review the concepts of probability
Show steps
Reviewing the basic concepts of probability will make learning the more advanced topics easier.
Browse courses on
Probability
Show steps
-
Read through your old notes or textbooks on probability.
-
Work through some practice problems on probability.
Watch videos on probability and statistics
Show steps
There are many helpful videos available online that can explain probability concepts in a clear and concise way.
Show steps
-
Search for videos on probability and statistics on YouTube or other video-sharing websites.
-
Watch the videos and take notes on the key concepts.
Create a cheat sheet of probability formulas
Show steps
Creating a cheat sheet of probability formulas can help you to quickly and easily reference the formulas you need when working on problems.
Show steps
-
Gather together all of the probability formulas that you will need for the course.
-
Create a cheat sheet that includes the formulas, along with any relevant notes or examples.
Three other activities
Expand to see all activities and additional details
Show all six activities
Join a study group or online forum to discuss probability problems
Show steps
Discussing probability problems with other students can help you to better understand the concepts and to learn from others' perspectives.
Show steps
-
Find a study group or online forum dedicated to discussing probability problems.
-
Participate in the discussions and ask questions when you need help.
Solve practice problems on probability
Show steps
Practice is essential for mastering probability concepts. There are many practice problems available online and in textbooks.
Show steps
-
Find practice problems on probability.
-
Solve the problems and check your answers.
Create a blog post or video explaining a probability concept
Show steps
Explaining a probability concept to someone else can help you to solidify your understanding of the concept.
Show steps
-
Choose a probability concept that you want to explain.
-
Write a blog post or create a video explaining the concept in a clear and concise way.
Review the concepts of probability
Show steps
Reviewing the basic concepts of probability will make learning the more advanced topics easier.
Browse courses on
Probability
Show steps
Show steps
Show steps
- Read through your old notes or textbooks on probability.
- Work through some practice problems on probability.
Watch videos on probability and statistics
Show steps
There are many helpful videos available online that can explain probability concepts in a clear and concise way.
Show steps
Show steps
Show steps
- Search for videos on probability and statistics on YouTube or other video-sharing websites.
- Watch the videos and take notes on the key concepts.
Create a cheat sheet of probability formulas
Show steps
Creating a cheat sheet of probability formulas can help you to quickly and easily reference the formulas you need when working on problems.
Show steps
Show steps
Show steps
- Gather together all of the probability formulas that you will need for the course.
- Create a cheat sheet that includes the formulas, along with any relevant notes or examples.
Three other activities
Expand to see all activities and additional details
Show all six activities
Join a study group or online forum to discuss probability problems
Show steps
Discussing probability problems with other students can help you to better understand the concepts and to learn from others' perspectives.
Show steps
Show steps
Show steps
- Find a study group or online forum dedicated to discussing probability problems.
- Participate in the discussions and ask questions when you need help.
Solve practice problems on probability
Show steps
Practice is essential for mastering probability concepts. There are many practice problems available online and in textbooks.
Show steps
Show steps
Show steps
- Find practice problems on probability.
- Solve the problems and check your answers.
Create a blog post or video explaining a probability concept
Show steps
Explaining a probability concept to someone else can help you to solidify your understanding of the concept.
Show steps
Show steps
Show steps
- Choose a probability concept that you want to explain.
- Write a blog post or create a video explaining the concept in a clear and concise way.
Career center
Learners who complete Defining, Describing, and Visualizing Data will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Data Scientist
Data Scientist
Data Scientists use data to solve complex business problems. This course provides a strong foundation in data science techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to help businesses and organizations make informed decisions. This course provides a strong foundation in statistical methods and techniques, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Business Analyst
Business Analyst
Business Analysts use data to help businesses improve their performance. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Market Researcher
Market Researcher
Market Researchers collect and analyze data to help businesses understand their customers and make informed decisions. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Financial Analyst
Financial Analyst
Financial Analysts use data to help businesses make informed decisions about investments and financial planning. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to help businesses improve their operations and make informed decisions. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use data to help businesses make informed decisions about investments and financial planning. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Risk Analyst
Risk Analyst
Risk Analysts use data to help businesses identify and mitigate risks. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Data Engineer
Data Engineer
Data Engineers build and maintain the infrastructure that stores and processes data. This course provides a strong foundation in data engineering techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. This course provides a strong foundation in database administration techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course provides a strong foundation in software engineering principles and techniques, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Product Manager
Product Manager
Product Managers are responsible for the development and management of products. This course provides a strong foundation in product management principles and techniques, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Project Manager
Project Manager
Project Managers plan, execute, and control projects. This course provides a strong foundation in project management principles and techniques, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Consultant
Consultant
Consultants provide advice and guidance to businesses and organizations. This course provides a strong foundation in consulting principles and techniques, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
For more career information including salaries, visit:
OpenCourser.com/course/zzw486/defining
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
Defining, Describing, and Visualizing Data.
This influential book introduces Bayesian statistical methods, which are becoming increasingly important in data analysis and decision-making.
This renowned textbook provides a comprehensive overview of statistical learning methods, including supervised and unsupervised learning algorithms.
Save
Serves as a comprehensive guide to data visualization principles and techniques, offering practical advice on creating clear and effective visualizations.
Introduces Bayesian statistical methods using R and Stan, providing practical experience with Bayesian modeling and inference.
This practical guide offers step-by-step instructions and hands-on examples that demonstrate how to use R and RStudio for data visualization. It serves as a valuable complement to the course's focus on visualization techniques.
This classic textbook offers a comprehensive introduction to probability models, providing a solid foundation for understanding the probabilistic aspects of data analysis.
Save
This comprehensive resource covers the fundamental concepts and algorithms of deep learning, providing valuable insights into the latest advancements in data-driven decision-making.
This classic textbook introduces the principles of reinforcement learning, which is becoming increasingly important in artificial intelligence and data-driven decision-making.
Save
Provides a comprehensive overview of causal inference methods, which are essential for making reliable decisions based on observational data.
This textbook provides a solid foundation in discrete mathematics, covering topics such as set theory, logic, and probability, which are essential for understanding the underlying principles of data analysis.
This textbook provides an foundational overview of statistics and its foundational concepts. It could serve as additional reading for those in the course who may need to review or who want more context and background on statistical methods.
Explores the statistical methods and models used in financial engineering, providing valuable insights into the application of data-based decision-making in the financial sector.
Save
Provides a high level overview of data science and offers valuable insights into the ethical implications and limitations of data-based decision-making.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/zzw486/defining
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Effort
Approx. 9 hours
Level
Introductory
Via
Coursera
Institution
University of Colorado Boulder
Instructor
Wendy Martin
Language
English
This course belongs to a
collection
called
The Data Driven Manager. It's comprised of three courses:
- Defining, Describing, and Visualizing Data (viewing)
- Data Driven Decision Making
- Data Acquisition, Risk, and Estimation
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