Data Visualization Classes New Haven, CT

In this comprehensive 2-day course, participants can become an advanced Tableau user able to work with data to create visualizations and use the various tools Tableau Public has to offer. They will learn to identify datasets to create desired visualizations and then master the Tableau tools on a deeper level to customize their visualizations. By the end of this course, participants will have learned to create maps to represent geographical data, and build actions to control visualizations within sheets and dashboards. Tuition includes hands-on training, a free retake, and a course manual. The course offers flexible scheduling and is available online or in NYC.

In this course, participants will be introduced to the field of data visualization and the various tools Tableau Public offers. They will learn to identify datasets to connect to, explore, analyze, filter and structure data to create desired visualizations. Beginners will learn to understand and manipulate data in Tableau, create their first visualization, distribute and publish their visualization and cover topics such as formatting visualizations, Tableau calculations and creating dashboards and stories. Tuition includes hands-on training, a free retake, and a course manual. The course offers flexible scheduling and is available online or in NYC.

This 2-day comprehensive Tableau course is designed to provide beginners the skills they need to start working in Tableau and creating powerful data visualizations. In the beginner part of the program, students will begin learning the tool's essentials, including data connecting, manipulation, and calculation. Then students will begin to create visualizations from their data with charts, graphs, and dashboards. In the advanced section of the course, participants will learn advanced visualization techniques creating data maps, visualization maps, and custom charts.

This beginner Tableau course teaches participants the fundamentals of data visualization with Tableau. Students will get going in Tableau with hands-on exercises in tools working with data. This course covers data connection, calculations, data manipulation, data visualization, dashboard creation, and more. Participants will walk away with comfort working with data and creating visualizations in Tableau to start driving insights from data.

In this intermediate-level Tableau course, participants will take their Tableau skills to the next level with advanced visualization techniques. Participants will learn to create data maps, visualization maps, custom charts, and more. This 1-day course builds off beginner Tableau skills and teaches students more advanced visualization techniques in Tableau through hands-on exercises.

Designed for professionals already using data-management tools, this 2-day course introduces basic functions in Tableau. After exploring the fundamentals, students will learn how to connect to, prepare, and explore data, manage and sort data in fields, and apply advanced worksheet filters. Completion of this course will prepare students to create advanced visualizations, maps, and stories.

This intermediate course in Tableau Desktop teaches advanced skills with this data visualization software. This course teaches students how to blend data in order to visualize relationships, clean and organize PDF data, and troubleshoot joins. Students will learn how to manipulate data and use advanced calculations to create data visualizations.

This course on data wrangling with Python offers a 3-day comprehensive introduction. The purpose of this course is to give an immersive foundation that equips students with the most critical data analysis tools. Students will learn how to work with NumPy, Pandas, and MatPlotLib to calculate descriptive statistics, work with alternative data sources, and scrape web pages. The course culminates with a real-life data wrangling project.

This 2-day course on Python with data science is intended for software developers, IT architects, and data scientists. This course will build on their knowledge of statistics and programming, teaching them the theoretical and technical aspects of the use for Python. Students will learn about the history and purpose of data science, life-cycle phases of data analytics, methods for repairing and normalizing data, and how to aggregate and group data. Students will also complete 10 lab exercises.