As data mining is one of the utmost important steps of data science, it is crucial for all data science experts & statisticians to have apt knowledge of data mining. It majorly focuses on extracting information from a large dataset.

This may sound simple, but it can be complicated even for the experienced individual. However, with the right knowledge of tools, it becomes comparatively simple. Considering this, we have curated this course that will help you in understanding the fundamentals of data mining with some simple yet important GUI tools. None of these requires any coding or any programming languages like R or Python.

Why You Should Learn Data Mining?

• A crucial step in data science.

• Important from extracting information from a large dataset.

• Helps in transforming data into an easily interpretable structure for further use.

• Useful for developing smart market decisions, run accurate campaigns & so on.

• Lets you analyze customer behaviors and their insights.

Why You Should Take This Course?

• Covers basics of data mining

• Gives you insights into a process and frameworks used in data mining

• You will learn about various stages of data mining

• Work with some of the most heavily used tools & technologies.

How This Course Unfolds?

It is a perfect course created for any enthusiast looking to understand the process of data mining in the simplest way possible. If you are someone, who is eyeing a data science career, then learning data mining will be the perfect topic to kickstart your journey.

This course is created in such a way that it will cover all the theoretical aspects of data mining along with real-time implementation. It begins with the basic introduction of data mining & all the essential software or tools required. Later on, you will get insights into standard processes, models, data reduction, clustering, classification, anomaly detection, text mining, regression analysis & so much more. You will work with some of the most widely used tools & technologies to have complete learning.

What You Will Learn?

• Data mining

• Data mining tools & technologies

• Data mining standard process & models

• Data reduction, classification, clustering, anomaly detection

• Association analysis, regression analysis, text mining, Sequence

• Data reduction

• Projects for real-time implementation