Interactive Data Visualization with Tableau
This course will teach you how to estimate descriptive quantities and sampling variances from complex surveys, and also how to fit linear and logistic regression models to complex sample survey data.
Overview
In this course you will learn about the interactive exploration of data, and how it is achieved using state-of-the-art data visualization software. You will learn to explore a range of different data types and structures, and about various interactive techniques for manipulating and examining data to produce effective visualizations. The learning process is hands-on as students are guided through an analysis of quantitative business data to discern meaningful patterns, trends, relationships, and exceptions that reveal business performance, potential problems and opportunities.
- Introductory, Intermediate
- 4 Weeks
- Expert Instructor
- Tuiton-Back Guarantee
- 100% Online
- TA Support
Learning Outcomes
Students who complete this course will be able to:
- Apply principles of perception to data visualization
- Use software tools to interactively visualize relationships among variables
- Analyze distributions of data visually
- Use a range of displays to explore data
- Use parallel coordinate plots, scatterplots, and trellising to analyze multivariate data
- Visualize hierarchical data with treemap
Who Should Take This Course
Statistical analysts and data miners who need to explore and graph multivariate data, either to form impressions of the data or as a preliminary step to performing statistical tests or building models.
Our Instructors
Ms. Madhuri Maddipatla
Madhuri Maddipatla is an analytics specialist and problem solver with 10+ years of experience in analytics consulting across multiple domains, including Retail, Consumer Packaged Goods, Healthcare, Finance, Manufacturing, and E-commerce. Currently a Specialist with McKinsey and Company, she has been an instructor and mentor in the data analytics, data visualization and business consulting space for 6+ years now. She completed her M.S. in Data Science and Business Analytics at the University of North Carolina at Charlotte and worked on several analytics efforts with the industry and in the academic setup. She won several online crowd sourcing analytics contests and is a passionate problem solver and data science mentor.
Course Syllabus
Week 1
- Information visualization characterization and history
- Elements of visual perception
- Software introduction and data preparation (merging data, getting started, export)
Week 2
- Interaction techniques
- Distribution analysis
- Hands-on visual exploration of business data
Week 3
- Time Series
- Multivariate views (scatterplots, parallel coordinate plots, trellising)
- Treemaps for hierarchical data
Week 4
- Specialized visualizations
- Video demonstrations of novel techniques
- From visualization to visual analytics
Class Dates
2025
Instructors: Ms. Madhuri Maddipatla
Instructors: Ms. Madhuri Maddipatla
Instructors: Ms. Madhuri Maddipatla
Prerequisites
The Statistics.com courses have helped me a lot, pushing me to the limit and making me learn much more than I expected I could. The knowledge I gained I could immediately leverage in my job … then eventually led to landing a job in my dream company – Amazon.
Karolis Urbonas
This program has been a life and work game changer for me. Within 2 weeks of taking this class, I was able to produce far more than I ever had before.
Susan Kamp
The material covered in the Analytics for Data Science Certificate will be indispensable in my work. I can’t wait to take other courses. Great work!
Stephen McAllister
I learned more in the past 6 weeks than I did taking a full semester of statistics in college, and 10 weeks of statistics in graduate school. Seriously.
Amir Aminimanizani
This is the best online course I have ever taken. Very well prepared. Covers a lot of real-life problems. Good job, thank you very much!
Elena Rose
The more courses I take at Statistics.com, the more appreciation I have for the smart approach, quality of instructors, assistants, admin and program. Well done!
Leonardo Nagata
This course greatly benefited me because I am interested in working in AI. It has given me solid foundational knowledge…After completing this last course, I feel I have gained valuable skills that will enhance my employability in Data Science, opening up diverse career opportunities.
Richard Jackson
Frequently Asked Questions
-
What is your satisfaction guarantee and how does it work?
-
Can I transfer or withdraw from a course?
-
Who are the instructors at Statistics.com?
Visit our knowledge base and learn more.
Additional Information
Organization of Course
This course takes place online at The Institute for 4 weeks. During each course week, you participate at times of your own choosing – there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.
At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.
Time Requirements
This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.
Homework
Homework in this course consists of guided exercises using state of the art software.
In addition to assigned readings, this course also has an end of course data modeling project, and example software files.
Course Text
A recommended text for this course is Now You See It: Simple Visualization Techniques for Quantitative Analysis by Stephen Few. Note: This text is not available in digital format. For those residing outside the US and not able to purchase this text, you may use The Truthful Art by Albert Cairo instead.
Software
The use of Tableau software is illustrated and access to this program will be provided in the first lesson. Prior experience with Tableau is not expected or required.
Some students also use Spotfire, but it is not available as part of the course. Want to use R? Please see our course: Visualization in R with ggplot2.
Course Fee & Information
Enrollment
Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date unless you specify otherwise.
Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.
Group Rates
Contact us to get information on group rates.
Discounts
Academic affiliation? In most courses you are eligible for a discount at checkout.
New to Statistics.com? Click here for a special introductory discount code.
Invoice or Purchase Order
Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment.
Options for Credit and Recognition
This course is eligible for the following credit and recognition options:
No Credit
You may take this course without pursuing credit or a record of completion.
Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.
CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.
INFORMS-CAP
This course is recognized by the Institute for Operations Research and the Management Sciences (INFORMS) as helpful preparation for the Certified Analytics Professional (CAP®) exam and can help CAP® analysts accrue Professional Development Units to maintain their certification.
This course has been evaluated by the American Council on Education (ACE) and is recommended for the upper-division baccalaureate degree, 2 semester hours in computer science, computer science systems, or information technology. Please note that the decision to accept specific credit recommendations is up to the academic institution accepting the credit.
Supplemental Information
Literacy, Accessibility, and Dyslexia
At Statistics.com, we aim to provide a learning environment suitable for everyone. To help you get the most out of your learning experience, we have researched and tested several assistance tools. For students with dyslexia, colorblindness, or reading difficulties, we recommend the following web browser add-ons and extensions:
Chrome
- Color Enhancer (for colorblindness)
- HelperBird (for colorblindness, dyslexia, and reading difficulties)
Firefox
- Mobile Dyslexic
- Color Vision Simulation (native accessibility feature)
- Other native accessibility features instructions
Safari
- Navidys (for colorblindness, dyslexia, and reading difficulties)
- HelperBird for Safari (for colorblindness, dyslexia, and reading difficulties)