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Updated in [May 25th, 2023]

This course, Data Science: Visualization, is part of the Professional Certificate Program in Data Science. It covers the basics of data visualization and exploratory data analysis. Students will learn to use the ggplot2 package for the statistical programming language R, and will be introduced to three motivating examples. These examples will cover topics such as world health, economics, and infectious disease trends in the United States.

The course will also discuss how mistakes, biases, systematic errors, and other unexpected problems can lead to data that should be handled with care. Data visualization is an important tool for communicating data-driven findings, motivating analyses, and detecting flaws. By the end of the course, students will have the skills to leverage data to reveal valuable insights and advance their careers.

[Applications]
After completing this course, students will be able to apply the concepts of data visualization and exploratory data analysis to their own datasets. They will be able to use ggplot2 to create informative visualizations and identify potential problems in their data. Students will also be able to use data visualizations to communicate their findings to others and motivate further analyses.

[Career Paths]
1. Data Scientist: Data Scientists are responsible for analyzing large datasets to uncover patterns and trends, and then using those insights to develop predictive models and algorithms. They must be able to interpret and communicate their findings to stakeholders, and use their knowledge of data science and analytics to inform business decisions. Data Scientists are in high demand, and the demand is only expected to increase as more organizations rely on data-driven insights.

2. Business Intelligence Analyst: Business Intelligence Analysts are responsible for collecting, analyzing, and interpreting data to inform business decisions. They must be able to identify trends and patterns in data, and use their findings to develop strategies and solutions. Business Intelligence Analysts must also be able to communicate their findings to stakeholders, and use their knowledge of data science and analytics to inform business decisions.

3. Data Visualization Specialist: Data Visualization Specialists are responsible for creating visual representations of data to help stakeholders understand and interpret data. They must be able to identify trends and patterns in data, and use their findings to create visualizations that are both informative and aesthetically pleasing. Data Visualization Specialists must also be able to communicate their findings to stakeholders, and use their knowledge of data science and analytics to inform business decisions.

4. Data Engineer: Data Engineers are responsible for designing, building, and maintaining data systems. They must be able to design and implement data pipelines, databases, and data warehouses, and use their knowledge of data science and analytics to inform business decisions. Data Engineers are in high demand, and the demand is only expected to increase as more organizations rely on data-driven insights.

[Education Paths]
1. Bachelor of Science in Data Science: This degree program focuses on the fundamentals of data science, including data analysis, data visualization, machine learning, and artificial intelligence. Students will learn how to use data to solve real-world problems and gain an understanding of the ethical implications of data science. This degree is becoming increasingly popular as businesses and organizations recognize the value of data-driven decision-making.

2. Master of Science in Business Analytics: This degree program focuses on the application of data science to business problems. Students will learn how to use data to make informed decisions, develop strategies, and optimize operations. This degree is becoming increasingly popular as businesses and organizations recognize the value of data-driven decision-making.

3. Master of Science in Data Science: This degree program focuses on the fundamentals of data science, including data analysis, data visualization, machine learning, and artificial intelligence. Students will learn how to use data to solve real-world problems and gain an understanding of the ethical implications of data science. This degree is becoming increasingly popular as businesses and organizations recognize the value of data-driven decision-making.

4. Doctor of Philosophy in Data Science: This degree program focuses on the fundamentals of data science, including data analysis, data visualization, machine learning, and artificial intelligence. Students will learn how to use data to solve real-world problems and gain an understanding of the ethical implications of data science. This degree is becoming increasingly popular as businesses and organizations recognize the value of data-driven decision-making.