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Updated in [March 06th, 2023]

This course, Exploratory Data Analysis with MATLAB, provides students with the opportunity to learn how to think like a data scientist and ask questions of their data. Students will use interactive features in MATLAB to extract subsets of data and to compute statistics on groups of related data. They will also use MATLAB to automatically generate code and learn syntax as they explore. Additionally, students will use interactive documents, called live scripts, to capture the steps of their analysis, communicate the results, and provide interactive controls allowing others to experiment by selecting groups of data.

No programming background is required to be successful in this course, but some knowledge of basic statistics (e.g., histograms, averages, standard deviation, curve fitting, interpolation) is recommended. By the end of the course, students will be able to load data into MATLAB, prepare it for analysis, visualize it, perform basic computations, and communicate their results to others. The final assignment will combine these skills to assess damages following a severe weather event and communicate a polished recommendation based on the analysis of the data. Students will be able to visualize the location of these events on a geographic map and create sliding controls allowing them to quickly visualize how a phenomenon changes over time.

[Applications]
Upon completion of this course, participants will be able to apply the skills they have learned to explore data sets, visualize data, and communicate their results. They will be able to use MATLAB to automatically generate code and create interactive documents to capture the steps of their analysis. They will also be able to use MATLAB to create interactive controls to allow others to experiment with data sets.

[Career Paths]
1. Data Scientist: Data Scientists use MATLAB to analyze data and develop predictive models. They use the interactive features of MATLAB to explore data, identify patterns, and develop insights. They also use MATLAB to generate code to automate their analysis and to communicate their results. The demand for Data Scientists is growing rapidly as organizations increasingly rely on data-driven decision making.

2. Data Analyst: Data Analysts use MATLAB to explore data, identify trends, and develop insights. They use the interactive features of MATLAB to extract subsets of data and to compute statistics on groups of related data. They also use MATLAB to generate code to automate their analysis and to communicate their results. Data Analysts are in high demand as organizations increasingly rely on data-driven decision making.

3. Business Intelligence Developer: Business Intelligence Developers use MATLAB to develop interactive documents, called live scripts, to capture the steps of their analysis, communicate the results, and provide interactive controls allowing others to experiment by selecting groups of data. They use the interactive features of MATLAB to explore data, identify patterns, and develop insights. Business Intelligence Developers are in high demand as organizations increasingly rely on data-driven decision making.

4. Data Visualization Specialist: Data Visualization Specialists use MATLAB to visualize data and communicate their results. They use the interactive features of MATLAB to explore data, identify patterns, and develop insights. They also use MATLAB to generate code to automate their analysis and to communicate their results. Data Visualization Specialists are in high demand as organizations increasingly rely on data-driven decision making.

[Education Paths]
1. Bachelor of Science in Data Science: This degree program focuses on the fundamentals of data science, including data analysis, machine learning, and data visualization. Students will learn to use various tools and techniques to extract insights from data and develop predictive models. This degree is becoming increasingly popular as businesses and organizations recognize the value of data-driven decision-making.

2. Master of Science in Artificial Intelligence: This degree program focuses on the development of intelligent systems that can learn from data and make decisions. Students will learn to use various algorithms and techniques to develop autonomous systems that can interact with their environment and make decisions. This degree is becoming increasingly popular as businesses and organizations recognize the value of AI-driven decision-making.

3. Doctor of Philosophy in Machine Learning: This degree program focuses on the development of advanced machine learning algorithms and techniques. Students will learn to use various tools and techniques to develop models that can learn from data and make predictions. This degree is becoming increasingly popular as businesses and organizations recognize the value of machine learning-driven decision-making.

4. Master of Science in Data Science and Analytics: This degree program focuses on the fundamentals of data science and analytics, including data analysis, machine learning, and data visualization. Students will learn to use various tools and techniques to extract insights from data and develop predictive models. This degree is becoming increasingly popular as businesses and organizations recognize the value of data-driven decision-making.