A staggering amount of data is created everyday; analyzing and organizing this enormous amount of data can be quite a complex task. Haskell is a powerful and well-designed functional programming language that is designed to work with complex data. It is trending in the field of data science as it provides a powerful platform for robust data science practices. This course will introduce the basic concepts of Haskell and move on to discuss how Haskell can be used to solve the issues by using the real-world data. The course will guide you through the installation procedure, after you have all the tools that you require in place, you will explore the basic concepts of Haskell including the functions, and the data structures. It will also discuss the various formats of raw data and the procedures for cleaning the data and plotting them. With a good hold on the basics of Haskell and data analysis, you will then be introduced to advanced concepts of data analysis such as Kernel Density Estimation, Hypothesis testing, Regression analysis, text analysis, clustering, Naïve Bayes Classification, and Principal Component Analysis. After completing this course, you will be equipped to analyze data and organize them using advanced algorithms.