Last Updated on June 6, 2019

Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.

As a data mining specialist you will need to tighten your grips on the combination of technological, business, and interpersonal skills.

A data mining specialist finds the hidden information in vast stores of data, decides the value and meaning of this information, and understands how it relates to the organization.

According to Glassdoor.com “a Data Mining Specialist earns an average salary of $67377 per year.” And it is also reported that the high-paid data mining specialists have strong skills in SAS and SQL for Data Science.

In this piece, i don’t assume intermediate comfortability with programming but if you do, you will definitely get ahead with the following courses.

First off, If you don’t have any experience in programming or background in Statistics and Maths, i’ve got you covered with few practical reads. Learn R For Data Science

Math for Data Science

Probability and Statistics for Data Science

In this piece, my goal is to simply suggest the resources that will equip and edify you to master the techniques and art to be more successful in your career.

Also, this compilation will be updated at least once every quarter. Go ahead & save this one in your pocket/ bookmarks.☆

The 5 Best Courses to Learn Data Mining

Below, I’ve curated a list of best online courses/ specialization to learn Data Mining.

These classes will give you a sense of the Data Science education and help you cultivate Analytical thinking, you’ll need to be effective in your Data Mining work, whatever that may be!

Intro to Text Mining: Bag of Words Highly Recommended ]

This course is created by Ted Kwartler, who is Senior Data Scientist at Liberty Mutual, DataCamp Instructor and Author of “Text Mining in Practice with R”.

This course is designed to introduce the learners to the basics of text mining using the bag of words model, a simple algorithm used in Natural Language Processing and Information Retrieval.

In first three chapters, you will learn the essential topics for analyzing and visualizing text data.

Finally, the last chapter will help you to apply everything you’ve learned in a real-world case study to extract insights from employee reviews of two major tech companies.

Is it right for you?

If you have a basic understanding of R programming, this course will be a great addition to get a solid point of entry to all the tactical thinking behind text mining.

Upon the successful completion of this course, you will be highly prepared for the more advanced topics involved in Data Mining and also ready for taking these Data Science Courses or Machine Learning Courses.

Data Mining Specialization Highly Recommended ]

This Data Mining Specialization is offered by University of Illinois Urbana–Champaign on Coursera. This is an intermediate Specialization designed to help learners understand data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. You are also required to complete the Capstone project task to solve real-world data mining challenges using a restaurant review dataset from Yelp.

Is it right for you? This Data Mining Specialization is designed for people who are eager to learn the general concepts of data mining along with basic methodologies and applications. You must be comfortable with computer programming and at least have the basic knowledge of maths and statistics since the course topics include; pattern discovery, clustering, text retrieval, text mining, analytics, and data visualization. GO TO SPECIALIZATION

This course “Data Mining with R” is created by Geoffrey Hubona — Phd, Author and Associate professor of MIS at Texas A&M International University.

This course will help you to learn R Studio, the open source software for data analysis, data visualization, and help you understand the techniques to perform dozens of popular data mining techniques.

Is it right for you?

This course is suitable for learners to acquire critical data analysis, data mining, and predictive analytics skills, including data exploration and data visualization.

If you have a basic knowledge of R programming, this course will help you equip you with employable data analytics skills to expand you repertoire of data analysis and data mining knowledge and capabilities.

This course is created by Barton Poulson, a professor at Utah Valley University, designer, and data analytics expert.

This course, Data Science Foundations: Data Mining, aims to provide a solid point of entry to all the techniques, tools and tactical thinking behind data mining.

Is it right for you?

This course is suitable for learners with some experience in R and Python, who wish to obtain more experience in data mining.

This course is one of the highly rated courses on the internet and upon the completion you will have necessary skills of joining the data science workforce.

This course, Data Science Foundations: Data Mining, aims to provide a solid point of entry to all the techniques, tools and tactical thinking behind data mining.

Is it right for you?

This course is suitable for learners with some experience in R and Python, who wish to obtain more experience in data mining.

This course is one of the highly rated courses on the internet and upon the completion you will have necessary skills of joining the data science workforce.

This course is created by Dejan Sarka, MCT and SQL Server MVP, is an independent consultant, trainer, and developer focusing on database & business intelligence applications.

In this “Data Mining Algorithms” course, you will learn how the most popular data mining algorithms work, when to use which algorithm, and advantages and drawbacks of each algorithm as well.

Is it right for you?

The knowledge you will acquire from this course is not only theoretical but aimed at helping you develop better models in production.

This course is for learners with good understanding of R programming and will be helpful to learn about implementing algorithms.

Thanks for making it to the end : -)

If you liked this article, i’ve got a few practical reads for you. One about How to Become a Data Scientist (Learn Python, Math and Statistics) and one about Learning R for Data Science.