Master the art of data analysis by unleashing the power of Haskell
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.
Why go for this course?
We’ve spent the last decade working to help developers stay relevant. The structure of this course is a result of deep and intensive research into what real-world developers need to know in order to be job-ready. We don’t spend too long on theory, and focus on practical results so that you can see for yourself how things work in action.
This course follows an example-based approach that will take you through the most basic games toward the more complex ones, gradually building your skill level. It’s a blend of text, videos, code examples, and assessments, which together makes your learning journey all the more exciting and truly rewarding. It includes sections that form a sequential flow of concepts covering a focused learning path presented in a modular manner. This helps you learn a range of topics at your own speed and also move towards your goal of learning Unity.
After completing this course, you will be equipped to analyze data and organize them using advanced algorithms.
This course is authored by some of the best in the field.
James Church is an assistant professor of computer science at Austin Peay State University. He has consulted for various companies and a chemical laboratory for the purpose of performing data analysis work.
Hakim Cassimally has written, spoken, and evangelised about learning and writing Haskell since 2006.
What are the requirements?
- A computer with internet connection
- Enthusiasm to learn
What am I going to get from this course?
- Understand the basic concepts of data analysis
- Create Haskell functions for the common descriptive statistics functions
- Learn to apply regular expressions in large-scale datasets
- Plot data with the gnuplot tool and the EasyPlot library
- Reduce the size of data without affecting the data’s effectiveness using Principal Component Analysis
- Master the techniques necessary to perform multivariate regression using Haskell code
Who is the target audience?
- If you are new to the field of data analysis and wish to polish your data analysis skills by using Haskell, this course is all that you need.
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