I : Fundamentals of Data Analytics
Every analysis, from a simple average to a machine learning model, starts with data that has been understood, organized, and summarized correctly. This opening module builds that foundation. You will learn what data is and how it is classified, how raw observations are organized through classification and tabulation, how continuous data is grouped into class intervals, and how a frequency distribution turns a long list of numbers into a table that tells a story at a glance.
These are the same building blocks found at the start of any basic statistics textbook, and for good reason: every technique that follows in this book, from measures of central tendency to inferential tests to machine learning pipelines, assumes you can already organize and describe data correctly. Get this module right, and everything after it will make more sense.