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Data Analytics and Visualization Certificate is a Program

Data Analytics and Visualization Certificate

Self-paced

$1,650 Enroll

Full program description

Start:

Anytime

Duration:

40 hours

Location:

Online

Price:

$1650


 

What you'll learn:

In this four-course certificate program, students will obtain the skills needed to analyze data in a business environment. Each course focuses on a different aspect of analytics:

  1. Business Intelligence and Data Analytics - learn the basics of business analytics using Excel. First by learning all about business analytics, including the importance of the role of obtaining crucial information for the organization. Then, learners begin working on a dataset in Excel, and learn essential tasks such as sorting and filtering the data to learn more about the business. Finally, learn how to analyze both categorical and numeric data: for categorical data, learn how to aggregate data using Excel's Pivot Table feature; for numeric data, learn the basics of analyzing distributions using statistics and common visualizations such as histograms and boxplots. By the end of the course, learners will have hands-on practice in preparing data for analysis and thoroughly analyzing a dataset using descriptive analytic techniques.
  2. Data Engineering - learn how to interact with databases using SQL. By first learning how important databases are to acquiring and storing data. Learners can then become familiar with the common database structure, the star schema, and learn the techniques of joining data from multiple tables. Finally, learn how to write reporting queries and to build complex scripts for processing data. By the end of the course, learners will have enough practice in writing SQL to evaluate and analyze a database that they will be ready to use their skills in a business setting.
  3. Data Analytics Methods - learn all about predictive modeling for a business setting. The types of algorithms covered are used for uncovering more complex business insights than possible using descriptive statistics (of the type covered in Courses 1 and 2). By learning how to build a predictive model in Python, learners will gain the capability to better describe the relationships between multiple variables in a dataset. While typically this content depends on an advanced understanding of statistics, this course teaches how to build and interpret models without needing a statistics prerequisite by focusing on the most essential aspects of predictive modeling.
  4. Data Visualization and Representation - learn how to visualize data using Tableau. First by learning the Tableau interface and becoming familiar with the importance of data visualization in a business setting. Then, learners will gain practice building many types of visualizations using different datasets. Finally, learn how to combine multiple visualizations into a single dashboard, adding interactive features and instructive text so that business stakeholders can access the information needed to make decisions.

 

What you'll do:

Each course features interactive videos to help learners understand both the analytical concepts and the software. Each course contains a capstone project, in which learners will apply the concepts taught using a separate data source; this realistic project gives learners the practice and confidence necessary to connect, explore, and analyze data sources into the future.

 

What you'll receive:

After successfully completing this certificate program, you will receive a certificate of completion along with a digital badge you can place on your LinkedIn profile.