Accelerate your career with courses from world class universities

Top Free Data Mining Courses

Data mining is the process of extracting and discovering structure in huge datasets. It employs methods of machine learning, statistics and database systems to achieve the same. In the free data mining courses by Great Learning, you will learn what it is and the various methods used to extract useful information. You will earn a free certificate for a Data Mining tutorial after the successful completion of the course.

 

Access Time
Free life time access
Auto Graph
1000+ free courses
Local Fire Department
In-demand skills & tools

How our courses help you upskill

Auto Graph
1000+ free courses
Access Time
Free life time access
Local Fire Department
In-demand skills & tools

Premium programs from top universities

Make the right decision for your career growth today!

KNOW MORE
Filter Results
Data Mining Domains
Level
Time to complete

Paid Degree & Certificate Programs

Education is one of the easy keys to be industry fit. But picking up the domain that suits you best from the pool of options? That’s a bit confusing. Great Learning offers you a plethora of choices in the fields of your interests. You can walk through the courses, understand what pleases your specifications and choose the best that suits you. Each of these courses will help you be ready by offering you the best of content. You will gain degree and PG certificates from recognized universities on successful completion of the registered course. We wish you happy learning!

 

10 Million+ learners

Success stories

Can Great Learning Academy courses help your career? Our learners tell us how.

And thousands more such success stories..

Data Mining students also learn

Take Free Data Mining Courses and Get Free Certificates

Data mining is the process of extracting and discovering structure in huge datasets. It employs methods of machine learning, statistics and database systems to achieve the same. It is the science that turns raw data into useful information. Useful data is extracted employing intelligent methods from a huge dataset. It transforms the data into a comprehensible form for future use.  Knowledge discovery in databases or KKD is the analysis step of data mining. Database and data management, data pre-processing, model and interference considerations, interestingness metrics, complexity analysis, post-processing of the structures, visualizations and online updation are other aspects besides raw analysis. 

Data mining is the process of inferring the data from raw information, it is derived from huge amounts of data and not the extraction of the data itself. It is applied to any form of huge amounts of data and information processing like collection, extraction, warehousing, analysis and statistics. It sees the application of computer decision support systems, artificial intelligence like machine learning and business intelligence. 

The data mining process is actually a semi-automated or automatic analysis of huge amounts of data to derive previously unknown, interesting structures like groups of data records or cluster analysis, unusual records like anomaly detection and dependencies that are association rule mining and sequential pattern mining. This employs database techniques like spatial indices. These structures can then be visualized as a summary of input data. It can be further used in analysis, for example, in predictive analysis. The data mining will identify many groups in the raw data. This is used to gain precise results by the decision support system. Data collection, data preparation, result interpretation and reporting does not belong to the data mining process. They fall under the overall KDD process as additional processes. 

Data mining techniques use machine learning and statistics to reveal hidden patterns in large data, while data analysis is used to test models like analysis of the effectiveness of the data despite its volume. Data dredging, data fishing and data snooping makes use of data mining techniques to sample parts of a large volume of dataset that may be very small for realistic statistical inferences to validate any patterns discovered. All these techniques can be used to create new hypotheses to test large volumes of datasets. 

Information discovery in KDD process involves:

  • Pre-processing. Targets must be made before using data mining algorithms. The targets set should be large so that it can contain the patterns while remaining aware enough to accomplish in stipulated time. This is because data mining can only uncover patterns that are already present in the dataset. Data warehouses or data mart are the sources for the data. Pre-processing is a very important step in data mining to analyze the multivariate datasets prior to data mining. The target set is then cleared. Data cleaning filters out the observations with noise and the component with missing data. 
  • Data mining. Data mining comprises of 6 classes of tasks:
  1. Anomaly detection. It is also called outlier and deviation detection. Unusual data records, data errors that need further studying are identified in anomaly detection. 
  2. Association rule learning. It is also called dependency modeling. It usually searches for relationships between variables. Market basket analysis can be an example to this. A supermarket holds the information of its customers' purchase history. It analyses what items are usually bought together. This information is further used for marketing purposes. 
  3. Clustering. It identifies the groups and structures in the data that are more or less similar without using known structures in the data. 
  4. Classification. It generalizes the known structures to apply them on the other data. For example, the e-mail application attempts to segregate the mails as legitimate and spam and place them in separate folders. 
  5. Regression. It finds the function to model the data with least error possible to estimate the relationship between the data or the dataset. 
  6. Summarization. It gives a better compact representation of the dataset that includes visualization and report generation. 
  • Result validation. It is possible to misuse data mining techniques unintentionally, but can still produce significant results. This cannot predict future behavior and cannot be applied on other samples of data. It is of very little use. This is the result of investing too many hypotheses and poor statistical hypothesis testing. This is called overfitting in machine learning terms. All the patterns that are found by data mining algorithms need not be necessarily valid. 

Test sets of data are used in evaluation for untrained data mining algorithms. Known patterns are applied to the test set. The resulting output is then compared to the expected output. If the known patterns do not match with the expected results, it must be re-evaluated. Also is it necessary to change pre-processing and data mining algorithms or to alter a few values. The final process has to be interpreted and turned into useful information.

Industry works with six phases of data mining:

  • Business understanding
  • Data understanding
  • Data preparation
  • Modeling 
  • Evaluation
  • Deployment

These processes are simplified into three simple processes: Pre-processes, Data mining and Result validation.

The free Data Mining course offered by Great Learning will help subscribers learn the subject for free online. The course will take you through various processes and phases involved in data mining. It takes you through various algorithms, selection, pre-processing, data-mining techniques and result validation processes in detail. You will also be taken through examples and applications of data mining. You can also learn free data mining tutorials in your free time. You will also earn a free certificate after the successful completion of the course. Happy learning!

Career Path

Frequently Asked Questions

What is data mining with an example?

Data mining is the process of extracting and discovering structure in huge datasets. It employs methods of machine learning, statistics and database systems to achieve the same. It is the science that turns raw data into useful information. Useful data is extracted employing intelligent methods from a huge dataset. Collecting the phone numbers from a huge set of applications is one of the examples of a data mining process.

How does data mining work?

Data mining is the process of extracting useful information from a huge collection of raw data. It follows a few steps in the process:

  • Business understanding
  • Data understanding
  • Data preparation
  • Modeling 
  • Evaluation
  • Deployment
Where is data mining used?

Data mining is a technique used to extract information from the pool of raw data. It is applied in various fields such as:

  • Healthcare
  • Market basket analysis
  • Manufacture engineering
  • CRM
  • Fraud detection
  • Intrusion detection
  • Customer segmentation
  • Financial banking
Why is data mining needed?

Data mining reduces the risk of manual extraction by automating the process of collecting the useful information from the pool of raw data. It reduces human involvement, reduces the risk of errors, saves time and also works efficiently. The same model can be applied to several other applications with similar data. 

 

How can I learn data mining?

Data mining is the process of extracting useful data. It is a tedious process and involves risks of errors. One can learn Data Mining courses online for free with a certificate by enrolling in Great Learning Academy.

What is a data mining course?

Data mining course will enlighten you with the definition, working, various processes and techniques, steps involved in extracting the useful data from the pool of raw information. It will help the learners be able to extract information efficiently and be an able professional.

Is data mining a good career?

Yes! Data mining makes an awesome career. Extracting the right data in an organization without leaking the secured data is the most important in any organization. Having the right skillset to work with data is hence important, making it a good career choice. You can enroll in a Great Learning Academy to avail Data Mining course for free

 

Will I get a certificate after completing these free Data Mining courses?

Yes, you will get a certificate of completion for Data Mining courses after completing all the modules and cracking the assessment. The assessment tests your knowledge of the subject and badges your skills.

How much do these Data Mining courses cost?

It is the entirely free courses list from Great Learning Academy. Anyone interested in learning the basics of Data Mining can get started with these courses.

Is there any limit on how many times I can take these free courses?

Once you enroll in the Data Mining courses, you have lifetime access to it. So, you can log in anytime and learn it for free online.

Can I sign up for multiple courses from Great Learning Academy at the same time?

Yes, you can enroll in as many courses as you want from Great Learning Academy. There is no limit to the number of courses you can enroll in at once, but since the courses offered by Great Learning Academy are free, we suggest you learn one by one to get the best out of the subject.

Why choose Great Learning Academy for these Data Mining courses?

Great Learning Academy provides these Data Mining courses for free online. The courses are self-paced and help you understand various topics that fall under the subject with solved problems and demonstrated examples. The courses are carefully designed, keeping in mind to cater to both beginners and professionals, and are delivered by subject experts. Great Learning is a global ed-tech platform dedicated to developing competent professionals. Great Learning Academy is an initiative by Great Learning that offers in-demand free online courses to help people advance in their jobs. More than 5 million learners from 140 countries have benefited from Great Learning Academy's free online courses with certificates. It is a one-stop place for all of a learner's goals.

What are the steps to enroll in these Data Mining courses?

Enrolling in any of the Great Learning Academy’s courses is just a one-step process. Sign-up for the courses, you are interested in learning through your E-mail ID and start learning them for free online.

Will I have lifetime access to these free Data Mining courses?

Yes, once you enroll in the courses, you will have lifetime access, where you can log in and learn whenever you want to.