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  • IBM® & IABAC® Certification
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  • 5 Capstone & 1 Client Project
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Data Mining is the process of mining useful insights from a large set of data by connecting statistics, artificial intelligence methods with database management. It becomes essential for the professionals to leverage and apply the important concepts of AI to make more profitable decisions for your company.

DataMites™ is the global institute for Data Science accredited by International Association of Business Analytics Certifications (IABAC). DataMites™ Data Mining Pune training program covers the fundamentals of Data mining along with the most popular language R, Machine learning and Text mining which is very much in demand today. With only few training providers venturing into AI, DataMites™ understood the need and have designed many professional courses to help candidates upskill themselves and to make them sought-after employees.




The entire training includes real-world projects and highly valuable case studies.

IABAC® certification provides global recognition of the relevant skills, thereby opening opportunities across the world.

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Why Datamites

Why DataMites Infographic


Become an expert in this lucrative "Data Mining" field with DataMites's training program. This Data Mining program provides requisite knowledge on concepts of Data analysis using R language and also the techniques of Machine learning and Text Mining. These are the most premier and demanding concepts needed to analyse the huge volume of data from different perspectives to gain better business insights. By choosing this DataMite's "Data Mining" course, it allows you to set your complete focus on these specified topics, R language, Machine learning and Text Mining to gain a specialisation.

Your big career move is all set now, as this Data mining course focuses on specialisation of skill set involving the techniques of Machine learning, Text Mining using the R programming language. Opting this course would be a perfect idea to explore, analyse and leverage data in order to arrive at valuable information for your company.

After successful completion of this "Data Mining" course, you should have acquired following skills

  • A complete knowledge about the R tool starting from the scratch of installing the tool. Acquire a thorough knowledge of the tool, also gain a better insight of Data manipulation as well as Data visualisation using the tool.
  • Gained an in-depth knowledge on this artificial intelligence Machine learning, which is a much demanded one in all the companies for an effective and powerful analysing of their business data. Both the foundation and Expert level are covered in this program.
  • Have attained the knowledge of Text mining and the major techniques used for mining and analysing the text data to derive at useful knowledge for the company. Also would have learned the statistical approach handled on text data with no or minimum human effort.

Data Mining is a powerful tool that many companies want to adapt in order to increase the accuracy of results they arrive from their raw data. Since the companies are readily interested in applying these new technologies for their data analysis, there is already a steep growth of opportunities in this field. Though the data mining concept is not pretty new and has been there for decades, it is becoming popular because of increased amount of data, fast processing and reduced cost in storage. As a Data Analytics professional, after completing this course you would see an increased growth in your career.

  • Any professionals who are aspiring to make a career in Business analytics using R language in Text Mining and Machine learning can choose this course.
  • Even as a beginner, if you want to take a specialisation by learning R language along with text mining and machine learning then start right away with this course.
  • Even as a beginner, if you want to take a specialisation by learning R language along with text mining and machine learning then start right away with this course.

"Our search for world class career ended at DataMites" is what, quoted by all of our candidates. Only experts with real time experience and better understanding of concepts can teach the candidates well. True, we have world class faculties who can make you understand even the toughest concepts at ease. DataMite's certification that you acquire after completing this course has industry recognition and adds weightage to your resume.


Introduction to R:

  • Installing R
  • Installing R Studio
  • Creating Objects in R
  • Creating Arrays
  • Creating Data frames
  • Use of Structure
  • Dimensions
  • Loading CSv files, Foreign packages into R

Data Manipulation with R:

  • Loading vectors in R
  • Combining to vectors in R
  • Cleaning Data with R, Swapping Data, Sorting Data, Converting unstructured to structured data, usage of sub, gsub, regexpr, gregexpr, apply, lapply, sapply

Data Visualization with R:

  • Usage of Plot, lines, boxplot, stars, barplot, pie, hist, rug, sunflowerplot, various color of histograms, tabplot, ggplot2, maptools and extracting data from URLs

The following topics are covered in "Machine Leaning"


Machine Learning Introduction: Supervised and Unsupervised Learning

  • Linear Regression Theory
  • Linear Regression Programming with R
  • Working on Case Study

Multiple Linear Regression

  • Theory behind multiple linear regression
  • Multiple Linear Regression with R
  • Working on Case Study

Decision Tree:

  • Theory Behind Decision Tree
  • Decision Tree with R
  • Working on Case Study

Naive Bayes:

  • Theory behind Naïve Bayes classifiers
  • Naive Bayes Classifiers with R
  • Working on Case Study

Support Vector Machines:

  • Theory behind Support Vector Machines
  • Support vector machines with R
  • Improving the performance with Kernals
  • Working on Case Study

Association Rule:

  • Theory behind Association Rule
  • Working on Case Studies


Neural Net:

  • Artificial Neural Network
  • Connection Weights in Neural Network
  • Generating Neural Network with R
  • Improving Neural Network Accuracy with Hidden Layers
  • Working on Case

Random Forest:

  • Theory behind Random Forest
  • Random Forest with R
  • Improving performance of Random Forest
  • Working on Case Study

Recommendation Engine:

  • Theory behind Recommendation Engines
  • Working on Case Study with R

Dimension Reduction:

  • Theory behind Recommendation Engine
  • Working on Case Studies

The topic covered in "Text Mining" are

Text Mining:

  • Introduction to Text Mining concepts
  • Sentiment Analysis with R/li>
  • Positive and Negative Word Cloud
  • Case study on Sentiment analysis

Advanced Regression

  • Theory Behind Advanced Regression
  • Advanced Regression with R
  • Working on Case Study

Web Analytics:

  • Theory behind Web Analytics
  • Working on Case Study


This online Data Mining course starts on the first day of your enrolment.

We are not supporting classroom sessions as of now and would definitely come up with it soon.

You can access the course materials and videos only during the course. Due to copyright issues, it is not available after the course.

The DataMites Placement Assistance Team(PAT) facilitates the aspirants in taking all the necessary steps in starting their career in Data Science. Some of the services provided by PAT are: -

  • 1. Job connect
  • 2. Resume Building
  • 3. Mock interview with industry experts
  • 4. Interview questions

The DataMites Placement Assistance Team(PAT) conducts sessions on career mentoring for the aspirants with a view of helping them realize the purpose they have to serve when they step into the corporate world. The students are guided by industry experts about the various possibilities in the Data Science career, this will help the aspirants to draw a clear picture of the career options available. Also, they will be made knowledgeable about the various obstacles they are likely to face as a fresher in the field, and how they can tackle.

No, PAT does not promise a job, but it helps the aspirants to build the required potential needed in landing a career. The aspirants can capitalize on the acquired skills, in the long run, to a successful career in Data Science.

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