Data Science Course

Data Science is a process of extracting knowledge from data. Data science is emerging to meet the challenges of processing large data sets which require versatile skill set and specialized in specific domain.

Data Science

Data Science Training Course Introduction

Data Science is a process of extracting knowledge from data. Data science is emerging to meet the challenges of processing large data sets which require versatile skill set and specialized in specific domain.

Data scientist analyse the complex problems and ensure rich consistency of data sets with creating visualizations to aid in understanding data.

Data science training is designed to teach the techniques of data mining and gain knowledge on insight of visualization and optimization of data to become a successful Data Scientist.

Data Science Training drops an insight on data visualization and techniques of Data Mining.This course gives an overview of the data, and gives answers to all questions, and tools that data analysts and data scientists work

Data Science Training Curriculum
Introduction to Data Science

This module will introduce you to Data Science throwing light on Why data science?, Analysing Big Data, Architecture and methods to solve Big Data issues, Data visualization etc…

• Introduction to Big Data
• Roles played by a Data Scientist
• Analysing Big Data using Hadoop and R
• Different Methodologies used for analysis in Data Science
• The Architecture and Methodologies used to solve the Big Data problems
• For example, Data Acquisition from various sources
• Data preparation
• Data transformation using Map Reduce (RMR)
• Application of Machine Learning Techniques
• Data Visualization etc.,
• problem statement of few data science problems which we shall solve during the course

Basic Data Manipulation using R in Data Science.

This module teaches how to manipulate data and use R for all kinds of data conversion and restructuring processes that are frequently encountered in the initial stages of data analysis in Data Science Training.

• Understanding vectors in R
• Reading Data
• Combining Data
• sub-setting data
• sorting data and some basic data generation functions

Machine Learning Techniques Using R Part-1

The goal of machine learning is to create a predictive model, that is indistinguishable from a correct model. This module, starts off giving you an overview about machine learning in Data science Training.

• Machine Learning Overview
• ML Common Use Cases and techniques
• Clustering and Similarity Metrics
• Distance Measure Types: Euclidean, Cosine Measures, Creating predictive models

Machine Learning Techniques Using R Part-2

The module is designed to teach you ‘k’ means clustering, association rule mining and much more..

• Understanding K-Means Clustering in Data Science
• Understanding TF-IDF and Cosine Similarity and their application to Vector Space Model
• Implementing Association rule mining in R.

Data Science Machine Learning Techniques Using R Part-3

The last part of machine learning module of Data Science course, trains on Decision Tree’s , Random forests concept in Data Science.

• Understanding Process flow of Supervised Learning Techniques
• Decision Tree Classifier
• How to build Decision trees
• Random Forest Classifier
• What is Random Forests concept in data science
• Features of Random Forest
• Out of Box Error Estimate and Variable Importance
• Naive Bayes Classifier

Integrating R with Hadoop

This module of Data science course, will give good knowledge on how R is integrated with R, the integrated programming environment and writing MapReduce jobs.

• Integrating R with Hadoop using R
• Hadoop and RMR package
• Exploring RHIPE (R Hadoop Integrated Programming Environment)
• Writing MapReduce Jobs in R and executing them on Hadoop

Introduction to Hadoop Architecture

Understand the Hadoop architecture, its commands, SQOOP and other data loading techniques in this module.

• Hadoop Architecture
• Common Hadoop commands
• MapReduce and Data loading techniques (Directly in R and in Hadoop using SQOOP, FLUME, and other data Loading Techniques)
• Removing anomalies from the data

Data Science Mahout Introduction and Algorithm Implementation

By the end of this module , you will be able to implement machine learning algorithms with Mahout

Implementing Machine Learning Algorithms on larger Data Sets with Apache Mahout
Additional Mahout Algorithms and Parallel Processing using R

In this module of Data Science Training you will learn how to implement Random Forest Classifier with Parallel Processing Library using R in this module of Data Science Training.

• Implementation of different Mahout algorithms
• Random Forest Classifier with parallel processing Library in R

Want to have a course urgently or on Fast track. We can arrange you for a specialised training aimed only for you. Please get in touch with us with your requirements by mail or just fill in the Batch Enquiry form. We will get in touch with you with the slot times and other details with in 24 hours

For Priority Training contact below
  • eITCafe: trainings@eitcafe.com
  • India: 040 6678 6677
  • US: 630-636-0198

Support services

We know how hard it can be to find and keep a job when there are so many other things to worry about. Our support team is here to help break down the barriers which are blocking your road to employment.
If you are a Working Chance candidate, please don’t hesitate to ask for advice or support on any issues which are affecting your chances of finding a job.
For further information, please email jobsupport@eitcafe.com our Support and Training Manager.

Job Preparation

• Assistance with learning job seeking skills
• Resume creation
• Master application completion
• Dressing for success
• Job interview preparation

Job Development

• Assistance with completing applications online or in person
• Job development online, on foot, networking events, job fairs and established employer relationships to locate available positions in your job goal
• Job leads and information on attending hiring events
• Follow-ups on applications placed to request interviews.

Explain what is Citrix?

It is an application deployment system. With Citrix, one can access the customized application and can also delivered to remote systems. It also allows file transfer from home computer to office computer and e-mail accessing.

Explain what is Data Store?

Data store is a database which consists of all the configuration information needed by the Citrix farm. Changes can be made at any time to the Meta Frame Server. The changes are persisted in the data store. It will data store following information like

  • Server configuration
  • User configuration
  • Print Environment
  • Published Application

Mention what is the query command in Citrix?

Query command in Citrix includes

  • qfarm
  • querydc
  • queryds
  • queryhr

Mention what is web interface or Nfuse?

Citrix web interface software provides web access to Java, Unix and Windows applications which are hosted via Citrix application server software. Citrix offers server side control of hosted applications, while Citrix web interface makes applications accessible through a web browser interface.

Explain what is the step to clear XenServer cache?

To clear XenServer cache you have to use command Dnscmd Server Name/clearcache.

Key Features


Overview of Course and Learning analytic’s


Learn from Certified and Expert Trainers

Customized Course as per your requirement

24/7 online support for the course learners

High Quality E-learning Content for learning


Access to the Recorded Sessions and classes

Flexible Course timing and Payment terms

Live Practical Oriented Approach for learners

Course Curriculam

Data Science Course Modules

Duration: 45 Days

Support: 24×7

Video: Yes

Data Science Certified Professional