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Updated in [March 06th, 2023]

MATLAB Essentials is a course designed to expand data analysis and modeling skills in MATLAB, a programming and numeric computing platform used to analyze data, develop algorithms, and create models. Learners will use MATLAB to examine real-world problems and answer questions such as how far does a blue whale swim each day, what is the favorite topping in a pizza shop, and what is the ride quality of a car suspension. MATLAB makes it easy to see results quickly, so there are no pre-requisites for the course. Learners will learn how to process, analyze, and visualize data collected nearly everywhere in today's digital workplace. They will use powerful templates and auto-generated code to start experimenting immediately and quickly process similar data sets. Additionally, this course will give learners the skills they need to prepare for the MathWorks Certified MATLAB Associate exam. By the end of the course, learners will be ready to analyze their own data sets and impress colleagues with word clouds, geographic plots, animations, and more.

[Applications]
Upon completion of this course, learners will be able to apply their MATLAB skills to analyze data, develop algorithms, and create models. They will be able to use MATLAB to process, analyze, and visualize data collected from various sources. Learners will also be able to use powerful templates and auto-generated code to quickly process similar data sets. Furthermore, they will have the essential programming skills needed to perform these tasks and be prepared to take the MathWorks Certified MATLAB Associate exam.

[Career Paths]
1. Data Scientist: Data Scientists use MATLAB to analyze data, develop algorithms, and create models. They are responsible for extracting insights from large datasets and using them to inform decisions and strategies. As the demand for data-driven decision-making increases, the demand for Data Scientists is expected to grow.

2. Machine Learning Engineer: Machine Learning Engineers use MATLAB to develop and deploy machine learning models. They are responsible for building and optimizing machine learning algorithms, as well as deploying them in production. With the increasing demand for automation and AI-driven solutions, the demand for Machine Learning Engineers is expected to grow.

3. Signal Processing Engineer: Signal Processing Engineers use MATLAB to analyze signals and develop algorithms for signal processing applications. They are responsible for designing and implementing signal processing systems, as well as optimizing them for performance. With the increasing demand for signal processing applications, the demand for Signal Processing Engineers is expected to grow.

4. Control Systems Engineer: Control Systems Engineers use MATLAB to design and develop control systems. They are responsible for designing and implementing control systems, as well as optimizing them for performance. With the increasing demand for automation and AI-driven solutions, the demand for Control Systems Engineers is expected to grow.

[Education Paths]
Recommended Degree Paths:
1. Bachelor of Science in Computer Science: This degree path provides students with a comprehensive understanding of computer science fundamentals, including programming, data structures, algorithms, and software engineering. Students will also learn about the latest trends in computer science, such as artificial intelligence, machine learning, and data science.

2. Master of Science in Data Science: This degree path focuses on the application of data science techniques to solve real-world problems. Students will learn how to use data to make decisions, develop predictive models, and create visualizations. They will also gain an understanding of the latest technologies and tools used in data science, such as MATLAB, Python, and R.

3. Master of Science in Artificial Intelligence: This degree path provides students with an in-depth understanding of artificial intelligence and its applications. Students will learn about the fundamentals of AI, including machine learning, deep learning, and natural language processing. They will also gain experience in using MATLAB to develop AI-based applications.

4. Doctor of Philosophy in Machine Learning: This degree path focuses on the development of advanced machine learning algorithms and their applications. Students will learn about the latest techniques in machine learning, such as deep learning, reinforcement learning, and unsupervised learning. They will also gain experience in using MATLAB to develop machine learning models.