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Data analysis and visualization is one of the highest-impact, most in-demand skills. In this lesson, we'll introduce you to the fundamental concepts and terms that you'll need to step into this world.

What's inside

Syllabus

Data analysis and visualization is one of the highest-impact, most in-demand skills. In this lesson, we'll introduce you to the fundamental concepts and terms that you'll need to step into this world.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Beginners will get a strong foundational introduction to the fundamental terms they need to step into data analysis and visualization
Examines how to analyze data and effectively visualize it, which are in high demand skill sets across many industries
Taught by Udacity, who are recognized for their work in providing online educational resources and training

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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 Discovering Data Analysis and Visualization with these activities:
Watch video tutorials on data analysis
Supplement your course materials with video tutorials tailored to your learning style.
Show steps
  • Search for video tutorials on YouTube or other online platforms.
  • Watch the tutorials and take notes on key concepts.
Solve practice problems
Practice makes perfect! Work on practice problems to develop fluency in skills taught in this course.
Show steps
  • Find practice problems online or in textbooks.
  • Work through the problems step-by-step.
  • Check your answers against the provided solutions.
Create a data visualization dashboard
Put your data visualization skills into practice by creating your own dashboard. It's a fun and practical way to apply what you're learning in the course.
Show steps
  • Choose a dataset that interests you.
  • Use data visualization tools to create interactive charts and graphs.
  • Present your dashboard to others and get feedback.
One other activity
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Show all four activities
Work on a data analysis project
Challenge yourself by applying your knowledge to a real-world data analysis project. This will give you valuable hands-on experience and help you build your portfolio.
Show steps
  • Identify a problem or opportunity that can be addressed with data.
  • Collect and analyze relevant data.
  • Develop insights and recommendations based on your analysis.
  • Present your findings to stakeholders.

Career center

Learners who complete Discovering Data Analysis and Visualization will develop knowledge and skills that may be useful to these careers:

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 Discovering Data Analysis and Visualization.
Provides a comprehensive overview of deep learning concepts and algorithms, covering topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for learners looking to gain a deeper understanding of the theoretical foundations of deep learning.
Provides a practical guide to deep learning using Python, covering topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for learners looking to develop their practical skills in deep learning.
Provides a practical and accessible introduction to data visualization, covering the fundamental concepts and techniques used to create effective visuals. It useful resource for beginners looking to gain a solid foundation in data visualization.
Provides a comprehensive guide to machine learning using Python, covering topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for learners looking to develop their practical skills in machine learning.
Provides a comprehensive guide to data analysis using R, covering topics such as data cleaning, manipulation, and visualization. It valuable resource for learners looking to develop their practical skills in data analysis.
Provides a practical guide to machine learning, covering topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for learners looking to develop their practical skills in machine learning.
Provides a comprehensive guide to data analysis using Python, covering data cleaning, manipulation, and visualization. It valuable resource for learners looking to develop their practical skills in data analysis.
Provides a practical guide to data science for business professionals, covering topics such as data mining, data analysis, and data visualization. It valuable resource for learners looking to gain a practical understanding of how data science can be used to solve business problems.
Provides a practical guide to big data analytics using Java, covering topics such as data mining, data visualization, and distributed computing. It valuable resource for learners looking to develop their practical skills in big data analytics.
Provides a comprehensive guide to data science, covering topics such as data cleaning, manipulation, and visualization. It valuable resource for learners looking to gain a foundational understanding of the field.

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