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Sivarit Sultornsanee
The primary objective of this course is to offer students an opportunity to learn how to use visualization tools and techniques for data exploration, knowledge discovery, data storytelling, and decision making in engineering, healthcare operations, manufacturing, and related applications. This course covers basics of data mining and visualization, and Python. It also introduces students to static visualization charts and techniques that reveal information, patterns, interactions.
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What's inside
Syllabus
Introduction to Data - Part 1
In this module, we will delve into the fundamental aspects of data, exploring its definition, significance, and the transformative journey from raw information to actionable insights. Through a series of engaging videos, we will unravel the mysteries of structured and unstructured data, unveiling their unique characteristics and applications. As we progress, the module unfolds the intricate steps of the data workflow, guiding through the pivotal stages of framing objectives, preparing data, analysis, interpretation, and effective communication of findings. Additionally, our exploration extends to the vast landscape of Big Data, unraveling its complexities through the lens of the Five Vs: Volume, Velocity, Variety, Veracity, and Value. By the end of this module, We will not only have a comprehensive understanding of the foundational concepts of data but also possess the essential skills to navigate the data-driven landscapes of today's digital era. Get ready to unlock the power of data and discover its profound impact on our world!
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Syllabus
Introduction to Data - Part 1
In this module, we will delve into the fundamental aspects of data, exploring its definition, significance, and the transformative journey from raw information to actionable insights. Through a series of engaging videos, we will unravel the mysteries of structured and unstructured data, unveiling their unique characteristics and applications. As we progress, the module unfolds the intricate steps of the data workflow, guiding through the pivotal stages of framing objectives, preparing data, analysis, interpretation, and effective communication of findings. Additionally, our exploration extends to the vast landscape of Big Data, unraveling its complexities through the lens of the Five Vs: Volume, Velocity, Variety, Veracity, and Value. By the end of this module, We will not only have a comprehensive understanding of the foundational concepts of data but also possess the essential skills to navigate the data-driven landscapes of today's digital era. Get ready to unlock the power of data and discover its profound impact on our world!
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Develops data mining, visualization techniques, Python; applicable to engineering, healthcare, and manufacturing
Taught by Sivarit Sultornsanee, who has expertise in data analytics and visualization
Suitable for beginners with no prior knowledge in data visualization
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Reviews summary
Practical data visualization for engineers
According to learners, this course offers a solid foundation in data visualization, particularly for those new to the field or looking to enhance their skills with Python. Students frequently praise the instructor's clear explanations and the practical, hands-on Python exercises that facilitate deep understanding and immediate application of concepts like Matplotlib and Seaborn. While earlier feedback often highlighted a minimal presence of R content despite the course title, recent reviews indicate that some basic R examples have been integrated, addressing this previous concern. However, some experienced professionals found the initial modules to be too basic, suggesting it's best suited for beginners or those seeking a refresher.
Ideal for new learners, but can be too basic for experienced users.
"The instructor explains concepts so clearly, especially for a beginner like me. Highly recommend for those starting out in data visualization!"
"It's a decent course for beginners, but for someone already familiar with Python, much of the initial content felt too basic for my needs."
"This course was not for experienced professionals; I already knew Python, and the data visualization parts were not deep enough for me."
Praised for clear, engaging, and easy-to-follow explanations.
"The instructor explains concepts so clearly, especially for a beginner like me, making complex topics easy to grasp."
"The Python part was exceptionally well-taught. The lectures were clear and well-structured, which kept me engaged throughout."
"I found the instructor to be very knowledgeable and excellent at breaking down complex ideas into understandable segments."
Delivers a solid foundation in Python for data visualization.
"The hands-on Python exercises were very helpful in understanding data visualization. I appreciated how practical the examples were for engineering applications."
"I can now apply these skills directly to my work, thanks to the practical visualizations demonstrated using Matplotlib and Seaborn."
"This course provided me with a solid foundation for data visualization in an engineering context, which was exactly what I needed."
Course title implies R, but content is heavily Python-centric.
"It felt heavily focused on Python, almost completely ignoring R despite the course title. I was quite disappointed by the lack of R content."
"I was looking for more advanced techniques or specific engineering case studies, and the R content was barely touched upon."
"Initially, I was worried about the R content, but the course has recently added some basic R examples, which is a welcome improvement."
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 Data Visualization with Python & R for Engineers with these
activities:
Brush up on data visualization basics
Show steps
Review fundamental data visualization principles to strengthen your understanding of the course concepts.
Browse courses on
Data Analytics
Show steps
-
Revisit key concepts of data visualization
-
Explore different types of data visualizations and their applications
-
Practice creating basic visualizations using a tool of your choice
Follow Online Python Tutorials
Show steps
Enhance your Python skills and explore specific concepts through guided tutorials.
Browse courses on
Python
Show steps
-
Identify reputable online platforms or resources offering Python tutorials.
-
Choose tutorials that align with your learning goals and skill level.
-
Follow the tutorials step-by-step and complete the exercises.
Connect with a Data Visualization Expert
Show steps
Seek guidance and mentorship from experienced professionals to enhance your learning journey.
Browse courses on
Data Visualization
Show steps
-
Identify potential mentors through professional networks or online platforms.
-
Reach out to selected mentors and express your interest in mentorship.
-
Establish regular communication and seek guidance on specific topics.
Eight other activities
Expand to see all activities and additional details
Show all 11 activities
Participate in a Study Group
Show steps
Collaborate with peers to reinforce concepts, share insights, and improve your understanding.
Browse courses on
Data Visualization
Show steps
-
Form or join a study group with other course participants.
-
Meet regularly to discuss course materials, solve problems, and share knowledge.
-
Share resources and support each other's learning.
-
Organize a group project if desired.
Solve Python Coding Challenges
Show steps
Strengthen your Python coding skills and enhance your ability to write clear and efficient code.
Browse courses on
Python
Show steps
-
Find coding challenges online or in books.
-
Attempt to solve the challenges using Python.
-
Review the solutions and identify areas for improvement.
Work through data visualization exercises
Show steps
Reinforce your understanding of data visualization techniques by solving practical exercises.
Browse courses on
Python
Show steps
-
Find online or textbook exercises on data visualization
-
Solve the exercises, focusing on interpreting data and choosing appropriate visualizations
-
Review your solutions and identify areas for improvement
Read 'The Data Visualization Handbook'
Show steps
Improve your understanding of the basics of data visualization and enhance your ability to create compelling data visualizations.
View
Data Visualisation: A Handbook for Data Driven...
on Amazon
Show steps
-
Read the book thoroughly.
-
Take notes on the key concepts and techniques.
-
Apply the concepts to a real-world dataset.
Attend a Data Visualization Workshop
Show steps
Gain practical experience in data visualization and learn from industry experts.
Browse courses on
Data Visualization
Show steps
-
Research and identify relevant workshops.
-
Register for a workshop that aligns with your goals.
-
Attend the workshop and actively participate.
Create a data visualization storyboard
Show steps
Develop your ability to communicate data insights effectively by creating a storyboard that tells a compelling data-driven story.
Browse courses on
Data Storytelling
Show steps
-
Choose a dataset and identify the key insights you want to convey
-
Sketch out a storyboard that outlines the flow of your story
-
Create visualizations to illustrate each key insight
Build a Data Visualization Dashboard
Show steps
Develop a practical understanding of data visualization by creating an interactive dashboard.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset and define the goals of the dashboard.
-
Design the dashboard layout and select the appropriate visualizations.
-
Implement the dashboard using Python and relevant libraries.
Develop a data visualization dashboard
Show steps
Apply your data visualization skills to create a practical tool that provides insights from real-world data.
Browse courses on
Python
Show steps
-
Identify a problem or opportunity that can be addressed with a data visualization dashboard
-
Gather and prepare the necessary data
-
Design and develop the dashboard using Python and relevant visualization libraries
-
Test and refine the dashboard to ensure it meets user needs
Brush up on data visualization basics
Show steps
Review fundamental data visualization principles to strengthen your understanding of the course concepts.
Browse courses on
Data Analytics
Show steps
Show steps
Show steps
- Revisit key concepts of data visualization
- Explore different types of data visualizations and their applications
- Practice creating basic visualizations using a tool of your choice
Follow Online Python Tutorials
Show steps
Enhance your Python skills and explore specific concepts through guided tutorials.
Browse courses on
Python
Show steps
Show steps
Show steps
- Identify reputable online platforms or resources offering Python tutorials.
- Choose tutorials that align with your learning goals and skill level.
- Follow the tutorials step-by-step and complete the exercises.
Connect with a Data Visualization Expert
Show steps
Seek guidance and mentorship from experienced professionals to enhance your learning journey.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify potential mentors through professional networks or online platforms.
- Reach out to selected mentors and express your interest in mentorship.
- Establish regular communication and seek guidance on specific topics.
Eight other activities
Expand to see all activities and additional details
Show all 11 activities
Participate in a Study Group
Show steps
Collaborate with peers to reinforce concepts, share insights, and improve your understanding.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Form or join a study group with other course participants.
- Meet regularly to discuss course materials, solve problems, and share knowledge.
- Share resources and support each other's learning.
- Organize a group project if desired.
Solve Python Coding Challenges
Show steps
Strengthen your Python coding skills and enhance your ability to write clear and efficient code.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find coding challenges online or in books.
- Attempt to solve the challenges using Python.
- Review the solutions and identify areas for improvement.
Work through data visualization exercises
Show steps
Reinforce your understanding of data visualization techniques by solving practical exercises.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find online or textbook exercises on data visualization
- Solve the exercises, focusing on interpreting data and choosing appropriate visualizations
- Review your solutions and identify areas for improvement
Read 'The Data Visualization Handbook'
Show steps
Improve your understanding of the basics of data visualization and enhance your ability to create compelling data visualizations.
View
Data Visualisation: A Handbook for Data Driven...
on Amazon
Show steps
Show steps
Show steps
- Read the book thoroughly.
- Take notes on the key concepts and techniques.
- Apply the concepts to a real-world dataset.
Attend a Data Visualization Workshop
Show steps
Gain practical experience in data visualization and learn from industry experts.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Research and identify relevant workshops.
- Register for a workshop that aligns with your goals.
- Attend the workshop and actively participate.
Create a data visualization storyboard
Show steps
Develop your ability to communicate data insights effectively by creating a storyboard that tells a compelling data-driven story.
Browse courses on
Data Storytelling
Show steps
Show steps
Show steps
- Choose a dataset and identify the key insights you want to convey
- Sketch out a storyboard that outlines the flow of your story
- Create visualizations to illustrate each key insight
Build a Data Visualization Dashboard
Show steps
Develop a practical understanding of data visualization by creating an interactive dashboard.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset and define the goals of the dashboard.
- Design the dashboard layout and select the appropriate visualizations.
- Implement the dashboard using Python and relevant libraries.
Develop a data visualization dashboard
Show steps
Apply your data visualization skills to create a practical tool that provides insights from real-world data.
Browse courses on
Python
Show steps
Show steps
Show steps
- Identify a problem or opportunity that can be addressed with a data visualization dashboard
- Gather and prepare the necessary data
- Design and develop the dashboard using Python and relevant visualization libraries
- Test and refine the dashboard to ensure it meets user needs
Career center
Learners who complete Data Visualization with Python & R for Engineers will develop knowledge and skills
that may be useful to these careers:
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists translate raw data into visually appealing and informative charts, graphs, and dashboards. They use their expertise in design, data visualization, and storytelling to create data visualizations that are both beautiful and effective. This course provides a strong foundation in data visualization and Python, two essential skills for Data Visualization Specialists.
Data Analyst
Data Analyst
Data Analysts translate raw data into digestible, actionable insights. They use their expertise in statistical analysis, data visualization, and programming to create powerful dashboards and reports that help businesses make informed decisions. This course provides a solid foundation in these key skills, making it an excellent choice for aspiring Data Analysts.
Data Scientist
Data Scientist
Data Scientists use their knowledge of machine learning, statistics, and programming to build predictive models and solve complex problems. This course provides a strong foundation in data visualization and Python, two essential skills for Data Scientists. Additionally, the course's focus on data exploration and storytelling can help Data Scientists communicate their findings more effectively.
Data Engineer
Data Engineer
Data Engineers build and maintain the infrastructure that supports data-driven organizations. They use their expertise in database management, cloud computing, and programming to ensure that data is accessible, reliable, and secure. This course provides a solid foundation in data visualization and Python, two skills that are essential for Data Engineers.
Business Analyst
Business Analyst
Business Analysts use data to understand and improve business processes. They use their expertise in data analysis, data visualization, and business acumen to identify opportunities for growth and efficiency. This course provides a solid foundation in data visualization and Python, two skills that are essential for Business Analysts.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. They use their expertise in market research, data analysis, and design to create products that meet the needs of customers. This course provides a solid foundation in data visualization and Python, two skills that are increasingly important for Product Managers.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to understand and improve marketing campaigns. They use their expertise in data analysis, data visualization, and marketing to create campaigns that are both effective and efficient. This course provides a solid foundation in data visualization and Python, two skills that are essential for Marketing Analysts.
Healthcare Data Analyst
Healthcare Data Analyst
Healthcare Data Analysts use their expertise in data analysis, data visualization, and healthcare to improve patient care and outcomes. This course may be useful for aspiring Healthcare Data Analysts, as it provides a solid foundation in data visualization and Python, two skills that are essential for this role.
Financial Analyst
Financial Analyst
Financial Analysts use data to understand and predict financial trends. They use their expertise in data analysis, data visualization, and finance to make investment recommendations and develop financial plans. This course may be useful for aspiring Financial Analysts, as it provides a solid foundation in data visualization and Python, two skills that are increasingly important for this role.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency and effectiveness of organizations. They use their expertise in data analysis, data visualization, and operations research to develop solutions to complex problems. This course may be useful for aspiring Operations Research Analysts, as it provides a solid foundation in data visualization and Python, two skills that are essential for this role.
Actuary
Actuary
Actuaries use data to assess and manage risk. They use their expertise in data analysis, data visualization, and actuarial science to develop insurance plans and financial products. This course may be useful for aspiring Actuaries, as it provides a solid foundation in data visualization and Python, two skills that are increasingly important for this role.
Statistician
Statistician
Statisticians use data to understand and interpret the world around us. They use their expertise in data analysis, data visualization, and statistics to develop new knowledge and solve problems. This course may be useful for aspiring Statisticians, as it provides a solid foundation in data visualization and Python, two skills that are increasingly important for this role.
Data Architect
Data Architect
Data Architects design and manage the data infrastructure that supports data-driven organizations. They use their expertise in database management, cloud computing, and data modeling to ensure that data is accessible, reliable, and secure. This course may be useful for aspiring Data Architects, as it provides a solid foundation in data visualization and Python, two skills that are increasingly important for this role.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They use their expertise in programming, data structures, and algorithms to create software that meets the needs of users. This course may be useful for aspiring Software Engineers, as it provides a solid foundation in Python, a popular programming language for data visualization.
Computer Scientist
Computer Scientist
Computer Scientists use their expertise in computer science to solve problems and create new technologies. They use their knowledge of programming, data structures, and algorithms to develop software, hardware, and other computing systems. This course may be useful for aspiring Computer Scientists, as it provides a solid foundation in Python, a popular programming language for data visualization.
For more career information including salaries, visit:
OpenCourser.com/course/6p2hb2/data
Featured in The Course Notes
This course is mentioned in our blog,
The Course Notes. Read
one article that features
Data Visualization with Python & R for Engineers:
To read more articles from OpenCourser, visit:
OpenCourser.com/notes
Reading list
We've selected nine 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
Data Visualization with Python & R for Engineers.
Provides a comprehensive overview of data visualization techniques, from basic charts to advanced interactive visualizations. It valuable resource for anyone looking to learn more about data visualization and how to use it effectively.
Comprehensive guide to data analysis using Python. It covers a wide range of topics, including data cleaning, data exploration, and data visualization. It valuable resource for anyone who wants to learn more about data analysis using Python.
Save
Comprehensive guide to data science using R. It covers a wide range of topics, including data cleaning, data exploration, and data visualization. It valuable resource for anyone who wants to learn more about data science using R.
Collection of dashboards that have been used to solve real-world problems. It valuable resource for anyone who wants to learn more about how to design and use dashboards.
Save
Comprehensive guide to data visualization for business. It covers a wide range of topics, including data collection, data analysis, and data visualization. It valuable resource for anyone who wants to learn more about data visualization for business.
Save
Comprehensive guide to storytelling with data. It covers a wide range of topics, including data visualization, data analysis, and data storytelling. It valuable resource for anyone who wants to learn more about storytelling with data.
Comprehensive guide to ggplot2, a popular R package for creating graphics. It covers a wide range of topics, including data cleaning, data exploration, and data visualization. It valuable resource for anyone who wants to learn more about ggplot2.
Save
Comprehensive guide to the art of data visualization. It covers a wide range of topics, including data cleaning, data exploration, and data visualization. It valuable resource for anyone who wants to learn more about the art of data visualization.
Comprehensive guide to visualization analysis and design. It covers a wide range of topics, including data cleaning, data exploration, and data visualization. It valuable resource for anyone who wants to learn more about visualization analysis and design.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/6p2hb2/data
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Via
Coursera
Institution
Northeastern University
Instructor
Sivarit Sultornsanee
Language
English
Featured in The Course Notes
Read
one article that features
this course,
Data Visualization with Python & R for Engineers
from our blog, The Course Notes:
To read more articles from OpenCourser, visit:
OpenCourser.com/notes
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