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The Complete Data Visualization Course with Python, R, Tableau, and Excel

with Elitsa Kaloyanova

Master the art of creating compelling data visualizations: learn how to create professional charts in Python, R, Tableau, and Excel

4.9

808 reviews on
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30108 students already have enrolled
  • Institute of Analytics
  • The Association of Data Scientists
  • E-Learning Quality Network
  • European Agency for Higher Education and Accreditation
  • Global Association of Online Trainers and Examiners

Skill level:

Basic

Duration:

10 hours
  • Lessons (9 hours)
  • Practice exams (38 minutes)
  • Projects (5 hours)

CPE credits:

12.5
CPE stands for Continuing Professional Education and represents the mandatory credits a wide range of professionals must earn to maintain their licenses and stay current with regulations and best practices. One CPE credit typically equals 50 minutes of learning. For more details, visit NASBA's official website: www.nasbaregistry.org

Accredited:

certificate

What You Learn

  • Gain a solid understanding of data visualization fundamentals and theory
  • Learn how to create professional and aesthetically pleasing charts in Python, R, Tableau, and Excel
  • Understand how to select the right type of chart depending on the problem at hand
  • Develop expertise in interpreting data and communicating your findings through data visualizations
  • Boost your resume and career prospects with highly sought-after data visualization skills
  • Enhance your project portfolio with compelling data visualizations and impress recruiters and hiring managers

Topics & tools

data visualizationdashboardpythontableaurexceltheory

Your instructor

Elitsa Kaloyanova

Elitsa Kaloyanova

Senior Data Scientist at 365 Data Science | Computational Biologist | Data Visualization Expert

Track record

Bringing real-world expertise from leading global companies

Company logo 1

Academic background

Master's degree, Bioinformatics

University of Saarland
Ask Elitsa a question
  • Course Overview
  • Accredited certificates
  • Career paths
  • How it works
  • Student reviews
  • Recommended courses

    • Course OVERVIEW

    Description

    CPE Credits: 12.5 Field of Study: Specialized Knowledge
    Delivery Method: QAS Self Study
    The Data Visualization course is designed for everyone looking to deepen their understanding of creating meaningful and compelling visualizations. Whether you’re coming from a business or data science-related field, knowledge in data visualization is both important and advantageous. That’s precisely why this course is centered not in just one, but four different environments: Excel, Tableau, Python, and R. Each section is dedicated to a specific type of chart – bar charts, pie charts, area charts, line charts and many more. In addition, there are lectures that specifically explore what to avoid when creating a certain graphic. You can stick with your preferred environment and follow each section. Or you could master all four environments and add indispensable skills to your data visualization toolset.

    Prerequisites

    • Python (any recent version, such as Python 3.8 or later) and a code editor or IDE (e.g., Spyder, VS Code, or Jupyter Notebook)
    • Tableau Desktop or Tableau Public
    • Completion of an introductory Python course is recommended. Completion of an introductory Tableau course is recommended.

    Advanced preparation

    See more

    Curriculum

    108 lessons 6 exercises 1 project 5 exams

    Free preview

    What does the Course Cover

    1.1 What does the Course Cover

    5 min

    Why Learn Data Visualization

    1.2 Why Learn Data Visualization

    6 min

    How to Choose the Right Visualization - Popular Approaches and Frameworks

    1.4 How to Choose the Right Visualization - Popular Approaches and Frameworks

    7 min

    Color Theory and Colors

    1.6 Color Theory and Colors

    9 min

    Setting Up The Environments - Do Not Skip, Please!

    2.1 Setting Up The Environments - Do Not Skip, Please!

    1 min

    Tableau - Downloading Tableau

    2.2 Tableau - Downloading Tableau

    2 min

    Start for free

    I was kinda lost with all the data stuff, but 365 Data Science really made it click. The structured learning path, clear explanations, and especially the hands-on projects were game-changers. I didn’t just learn theory—I actually applied it and built a portfolio that helped me land a data analyst job. Now I use Python, SQL, Excel, and data viz skills every day. I’m way more confident. Before I was guessing—now I know what I’m doing.

    Siriwat N.

    Siriwat N.

    Before 365: Engineering student
    After 365: Data Analyst & Process Improvement | CJ MORE

    See all reviews

    96%

    of our students recommend

    365 Data Science.

    365 Data Science has been an invaluable resource for refreshing my skills and expanding my expertise. The well-structured courses in Python, Machine Learning, and SQL helped me brush up on fundamentals while learning advanced ETL and data visualization techniques. This hands-on approach has directly benefited my work—improving pipelines and creating more insightful analyses. For busy professionals, 365 offers a solid foundation and a practical refresher to stay ahead in the evolving world of data analytics.

    Shruti P.

    Shruti P.

    After 365: Sr. Business Intelligence Engineer | Child Care Resource Center (USA)

    See all reviews

    4.9

    Based on 808 reviews

    #1 most reviewed

    AI and data learning platform on Trustpilot.

    I’ve been using 365 Data Science for a while now, and it’s genuinely helped me grow in so many areas. The platform is really well-designed—everything from learning and practicing to exams and reviewing material feels smooth and intuitive. One thing I truly appreciate is how talented, knowledgeable, and supportive the instructors are. Whenever I had a question, they responded quickly and were always thoughtful and helpful in their answers. I’ve been able to apply what I’ve learned in my day-to-day work—across engineering, management, and financial analysis. It’s not just theory—it’s practical, and it’s made a real difference in how I work.

    Mani A.

    Mani A.

    After 365: Research Engineer | SadrabSanat

    See all reviews

    94%

    of AI and data science graduates

    successfully change

    or advance their careers.

    ACCREDITED certificates

    Craft a resume and LinkedIn profile you’re proud of—featuring certificates recognized by leading global institutions.

    Earn CPE-accredited credentials that showcase your dedication, growth, and essential skills—the qualities employers value most.

    Learn More
    • Institute of Analytics
    • The Association of Data Scientists
    • E-Learning Quality Network
    • European Agency for Higher Education and Accreditation
    • Global Association of Online Trainers and Examiners
    Learn More
    A LinkedIn profile mockup on a mobile screen showing Parker Maxwell, a Certified Data Analyst, with credentials from 365 Data Science listed under Licenses & Certification. A 365 Data Science Certificate of Achievement awarded to Parker Maxwell for completing the Data Analyst career track, featuring accreditation badges and a gold “Verified Certificate” seal.

    How it WORKS

    • Lessons
    • Exercises
    • Projects
    • Practice Exams
    • AI Mock Interviews

    Lessons

    Learn through short, simple lessons—no prior experience in AI or data science needed.

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    Exercises

    Reinforce your learning with mini recaps, hands-on coding, flashcards, fill-in-the-blank activities, and other engaging exercises.

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    Projects

    Tackle real-world AI and data science projects—just like those faced by industry professionals every day.

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    Practice Exams

    Track your progress and solidify your knowledge with regular practice exams.

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    AI Mock Interviews

    Prep for interviews with real-world tasks, popular questions, and real-time feedback.

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    Student REVIEWS

    A collage of student testimonials from 365 Data Science learners, featuring profile photos, names, job titles, and quotes or video play icons, showcasing diverse backgrounds and successful career transitions into AI and data science roles.
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