Visual Analytics with Tableau (Coursera)

Visual Analytics with Tableau (Coursera)

In this third course of the specialization, we’ll drill deeper into the tools Tableau offers in the areas of charting, dates, table calculations and mapping. We’ll explore the best choices for charts, based on the type of data you are using. We’ll look at specific types of charts including scatter plots, Gantt charts, histograms, bullet charts and several others, and we’ll address charting guidelines.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

We’ll define discrete and continuous dates, and examine when to use each one to explain your data. You’ll learn how to create custom and quick table calculations and how to create parameters. We’ll also introduce mapping and explore how Tableau can use different types of geographic data, how to connect to multiple data sources and how to create custom maps.
What You Will Learn

  • Create a chart using Tableau
  • Create dates using calculated fields
  • Customize table calculations
  • Customize and create dual layer maps

Course 3 of 5 in the Data Visualization with Tableau Specialization.

Syllabus

WEEK 1
Getting Started and Charting
In this module, you will explore the topic of charting in Tableau. By now you should already be well versed in how to change colors, shapes, and sizes of charts, so we are going to practice and demonstrate that skill more. You will be able to explain what the Tableau Tooltip does and when to use it. You will be able to discuss the various guidelines for choosing the right chart for your data. You will also create a chart using Tableau.

WEEK 2
Dates
This module highlights the important topic of dates within Tableau. You will be able to differentiate between discrete and continuous dates and when to use each. You will be able to use date hierarchies and use the date field to better customize your charts. You will be able to convert between discrete and continuous dates and know when and why you want to switch from one to the other. You will create dates using calculated fields.

WEEK 3
Table Calculations
In this module, you will focus on table calculations. You will be able to create new calculated fields to allow you to compare fields, apply aggregations, and more. You will be able use quick table calculations and create new calculated fields. You will be able to customize them and apply filters and parameters to your table calculations.

WEEK 4
Mapping
In this final module, we will go more in depths about maps within Tableau. You will be able to connect to a different data sources and customize your maps by changing colors, shapes, and sizes. You will be able to custom geocode a map and create Tableau maps with geographic data that is not recognized by Tableau. You will also be able to create dual layer maps and showcase how to overlay maps on top of one another.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Combining and Analyzing Complex Data (Coursera) Coursera
University of Maryland, College Park

Combining and Analyzing Complex Data (Coursera)

In this course you will learn how to use survey weights to estimate descriptive statistics, like means and totals, and more complicated quantities like model parameters for linear and logistic regressions. Software capabilities will be covered with R® receiving particular emphasis. The course will also cover the basics of record linkage and statistical matching—both of which are becoming more important as ways of combining data from different sources. Combining of datasets raises ethical issues which the course reviews. Informed consent may have to be obtained from persons to allow their data to be linked. You will learn about differences in the legal requirements in different countries.

Nov 16th 2026
4 Weeks
Principles of fMRI 2 (Coursera) Coursera
Johns Hopkins University,University of Colorado Boulder

Principles of fMRI 2 (Coursera)

Functional Magnetic Resonance Imaging (fMRI) is the most widely used technique for investigating the living, functioning human brain as people perform tasks and experience mental states. It is a convergence point for multidisciplinary work from many disciplines. Psychologists, statisticians, physicists, computer scientists, neuroscientists, medical researchers, behavioral scientists, engineers, public health researchers, biologists, and others are coming together to advance our understanding of the human mind and brain. This course covers the analysis of Functional Magnetic Resonance Imaging (fMRI) data.

Nov 16th 2026
4 Weeks
Bioinformatic Methods I (Coursera) Coursera
University of Toronto

Bioinformatic Methods I (Coursera)

Large-scale biology projects such as the sequencing of the human genome and gene expression surveys using RNA-seq, microarrays and other technologies have created a wealth of data for biologists. However, the challenge facing scientists is analyzing and even accessing these data to extract useful information pertaining to the system being studied. This course focuses on employing existing bioinformatic resources – mainly web-based programs and databases – to access the wealth of data to answer questions relevant to the average biologist, and is highly hands-on.

Nov 16th 2026
5-12 Weeks
Business intelligence and data analytics: Generate insights (Coursera) Coursera
Macquarie University

Business intelligence and data analytics: Generate insights (Coursera)

‘Megatrends’ heavily influence today’s organisations, industries and societies, and your ability to generate insights in this area is crucial to your organisation’s success into the future. This course will introduce you to analytical tools and skills you can use to understand, analyse and evaluate the challenges and opportunities ‘megatrends’ will inevitably bring to your organisation.

Nov 16th 2026
5-12 Weeks
Data Science for Business Innovation (Coursera) Coursera
Politecnico di Milano,EIT Digital

Data Science for Business Innovation (Coursera)

The course is a compendium of the must-have expertise in data science for executive and middle-management to foster data-driven innovation. It consists of introductory lectures spanning big data, machine learning, data valorization and communication. Topics cover the essential concepts and intuitions on data needs, data analysis, machine learning methods, respective pros and cons, and practical applicability issues.

Nov 16th 2026
4 Weeks
Google Sheets - Advanced Topics (Coursera) Coursera
Google Cloud

Google Sheets - Advanced Topics (Coursera)

This course builds on some of the concepts covered in the earlier Google Sheets course. In this course, you will learn how to apply and customize themes In Google Sheets, and explore conditional formatting options. You will learn about some of Google Sheets’ advanced formulas and functions. You will explore how to create formulas using functions, and you will also learn how to reference and validate your data in a Google Sheet.

Nov 16th 2026
1 Week
Assessing Health Program Delivery (Coursera) Coursera
Johns Hopkins University

Assessing Health Program Delivery (Coursera)

This course provides in-depth knowledge about implementation strength, quality of care, and service utilization, which are essential components of health program delivery. This course is primarily aimed at implementers, managers, funders, and evaluators of health programs in low- and middle-income settings (LMISs) targeting women and children, and undergraduate and graduate students in health-related fields.

Nov 16th 2026
5-12 Weeks
Analysis and Interpretation of Large-Scale Programs (Coursera) Coursera
Johns Hopkins University

Analysis and Interpretation of Large-Scale Programs (Coursera)

This course is for implementers, managers, funders, and evaluators of health programs targeting women and children in low- and middle-income countries as well as undergraduate and graduate students in health-related fields. Course participants will learn how to 1) transform quantitative components of an evaluation measurement plan into a sound analysis plan to address the evaluation questions, 2) conduct quantitative analyses of primary or secondary surveys or other available data, 3) interpret the meaning of the analysis results and their implications, and 4) disseminate the evaluation findings to program implementers, local and global stakeholders.

Nov 16th 2026
5-12 Weeks
Bayesian Statistics: Mixture Models (Coursera) Coursera
University of California, Santa Cruz

Bayesian Statistics: Mixture Models (Coursera)

Bayesian Statistics: Mixture Models introduces you to an important class of statistical models. The course is organized in five modules, each of which contains lecture videos, short quizzes, background reading, discussion prompts, and one or more peer-reviewed assignments. Statistics is best learned by doing it, not just watching a video, so the course is structured to help you learn through application.

Nov 16th 2026
5-12 Weeks
Football: More than a Game (Coursera) Coursera
University of Edinburgh

Football: More than a Game (Coursera)

Explore the world of football (soccer), the money, the rivalries, the trends, the past, the present, the men’s game, the women's game and the real issues. Whether you love it, hate it or try to ignore it – join us as we go behind the scenes to examine why football is more than just a game.

Nov 16th 2026
5-12 Weeks
Case studies in business analytics with ACCENTURE (Coursera) Coursera
ESSEC Business School

Case studies in business analytics with ACCENTURE (Coursera)

This course is RESTRICTED TO LEARNERS ENROLLED IN Strategic Business Analytics SPECIALIZATION as a preparation to the capstone project. During the first two MOOCs, we focused on specific techniques for specific applications. Instead, with this third MOOC, we provide you with different examples to open your mind to different applications from different industries and sectors. The objective is to give you an helicopter overview on what's happening in this field. You will see how the tools presented in the two previous courses of the Specialization are used in real life projects.

Nov 16th 2026
3 Weeks