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Machine Learning for Data Science using R Introductory Course


Machine Learning offers clever alternatives in analysing huge volumes of data. It’s a hybrid of computer science and statistics and is being aggressively adopted in multifarious industry applications. Machine learning involves developing efficient and fast algorithms and data driven models for data processing. R-Programming is one of the preferred tools for Machine learning. We will develop a keen understanding and appreciation of Machine Learning Algorithms by doing in on R. Check out the learning objectives below .

Career Guidance
Sandeep Soni

Mr. Sandeep Soni

CEO & Founder of Deccansoft Software Services
9849001840  /  9849001840


Course Overview

Machine learning is one of the fastest growing areas of computer science with far reaching business applications. The aim of this course is to introduce you to machine learning, and the most widely used algorithms in business applications.

  • We would spend time learning how to apply different ML algorithms in practice datasets from various business situations
  • However, an important learning objective will be to develop an appreciation for the fundamental ideas of machine learning and the mathematical derivations that transform these ideas into practical algorithm.

R (Programming language) is free programming language and software environment for statistical computing, graphics and Machine Learning. The R language is widely used among data scientist, statisticians and data miners for developing data models and data analytics. R has become one the most sought-after skills in 2018.

Why Our USP…

  • Get an idea of the quality and quantity of the subjects by watching demo videos provided.
  • For any technical issues/queries relating to the online training videos, we provide technical support by Subject Matter Experts (SMEs)
  • The course material is simple and organized and can be used for learning and as a reference material.
  • Includes job interview related training to help participants face an interview confidently.
  • Microsoft Certification Guidance and any subject related questions will be answered by Mr Sandeep Soni (MCT).
  • Every course is accompanied by a Real-time project along with a step-by- step guide and complete source code.


  1. Introduction:
    1. What is learning?
    2. When you we need machine learning?
    3. Types of Machine learning?
  2. Foundations:
    1. The statistical learning framework.
    2. Risk – Problem of overfitting.
    3. Error decomposition.
  3. Theory to Algorithm
    1. Linear Regression
    2. Logistic Regression
    3. Multiclass ranking & complex prediction problems.
    4. Decision tree Algorithms (CART & Random Forest)
      1. Measures of Gain
      2. Pruning
      3. Splitting rules.
      4. Neural Networks.
      5. Nearest Neighbour.


The course assumes that the student has no prior statistical or programming skills. However, comfort with college level math is must. Student need not know the math but should be comfortable with it.


Mithun Radhakrishnan, is a Freelance Data Enthusiast and Analyst.

He Primarily consults in the area of Digital Marketing. Mithun has consulted for multiple data projects as a Freelancer. Prior to this he was heading a team of stock analyst with a leading Bank in India.

In terms of Qualification, he has PG in Business Analytics and Business Intelligence from Illinois Institute of Technology. He is also a Chartered Market Technician (CMT) which is the highest certification in the field of Technical Analysis of stock market data. He also has ......



Course Completion Certificate

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