MATLAB Foundations for Data Science and AI

In the era of artificial intelligence and big data, the ability to process complex datasets and build predictive models is a critical skill for engineers, scientists, and analysts. MATLAB provides a robust, high-level environment to transition from raw data to actionable AI-driven insights. This written course guides you through the fundamental concepts of MATLAB programming, specifically tailored for data analysis and artificial intelligence workflows. You will start with the basics of the MATLAB environment and progress to preprocessing data, training machine learning models, and evaluating their performance. What you'll learn: - Understand MATLAB syntax, core data structures, and the interactive desktop environment. - Import, clean, and preprocess diverse datasets using modern table and timetable data types. - Apply statistical methods to analyze and interpret data trends through structured written exercises. - Build and evaluate foundational machine learning models using classification and regression techniques. - Integrate AI workflows into your data analysis pipelines to automate decision-making. - Practice writing clean, efficient, and well-documented MATLAB scripts for reproducible results. The course begins with foundational MATLAB terminology, syntax, and basic programming concepts. You will then transition to data manipulation, visualization techniques, and statistical analysis, culminating in the application of machine learning algorithms to real-world scenarios. Designed for beginners, students, and professionals new to programming, this course requires no prior technical background. Start reading today to build the computational skills needed for the data-driven future.