About Data Science Course

Data science is an “idea to bind together insights, information examination and their related techniques” to “comprehend and break down real wonders” with information. Data Science Training utilizes systems and speculations drawn from numerous fields inside the wide regions of arithmetic, measurements, data science, and software engineering from the sub-spaces of AI, order, bunch examination, information mining, databases, and perception.

Key Features

  Instructor-led Sessions
  Lifetime Access
  Real-life Case Studies
  24 x 7 Expert Support
  Instructor-led Sessions

Instructor Led Online Training


Start Date: 18 Dec, 2021

Course Duration: 60 Hours

Time: 10:00 AM - 12:00 PM


Instructor Led Classroom Training


Start Date: 21 Dec, 2021

Course Duration: 30 Hours

Time: 08:00 AM - 12:00 PM


Course Curriculum

  • Introduction to Data Science
  • Introduction to R programming
  • R Environment and Basic Commands
have acquired the right skills to take charge of your brand on Digital Media.
  • Importing data
  • Data Exploration
  • Creating calculated fields
  • Sorting & removing duplicates
  • Population and Sample
  • Measures of Central Tendency
  • Measures of Dispersion
  • Box plots and outlier detection
  • Creating Graphs and Reporting
  • What is Bigdata & Bigdata Use Cases
  • What is Distributed Computing
  • MapReduce Introduction
  • Hadoop & Tools
  • Bigdata on VM
  • Hadoop Basics
  • Map Reduce on Hadoop
  • Hive Introduction
  • Hive Queries
  • Pig
  • Pig Scripting
  • Connecting R to Hadoop
  • R Hadoop Reporting Analysis
  • Data import on to HDFS
  • Data Exploration using Hive and Pig
  • Data Analysis using R
  • Correlation
  • Simple Regression models
  • R-Square
  • Multiple regression
  • Multicollinearity
  • Redetection using model
  • Logistic regression models
  • Validation of logistic regression models
  • Multicollinearity in logistic regression
  • Trees, Entropy and Information Aain
  • Building Decision Trees
  • Validation of Trees
  • Fine tuning and Prediction using Trees
  • Model Validation measures
  • Cross validation techniques
  • Boot Strapping
  • Data exploration and Cleaning
  • Model Building
  • Validation and Implementation
  • Introduction
  • Algorithm of Neural Network
  • Building neural Network
  • Prediction using neural network

Course Description

  • The quantity of Data Science and Analytics work postings is anticipated to develop by almost 364,000 postings by 2020 – Forbes
  • The normal compensation for a Data Scientist is $130k according to Glassdoor
  • Organizations breaking down information will see $470 billion in efficiency benefits over their opponents not investigating information by 2020

The market for Data Analytics is developing over the world and this solid development example converts into an incredible open door for all the IT Professionals. Our Data Science Training causes you to snatch this chance and quicken your profession by applying the methods on various sorts of Data. It is most appropriate for:

  • Engineers trying to be an ‘Data Scientist’
  • Investigation Managers who are driving a group of examiners
  • Business Analysts who need to comprehend Machine Learning (ML) Techniques
  • Data Architects who need to pick up mastery in Predictive Analytics
  • ‘R’ experts who wish to work Big Data
  • Examiners needing to comprehend Data Science strategies

There is no particular pre-essential for Data Science Training. In any case, a fundamental comprehension of R can be advantageous. Edureka offers you a complimentary self-guided course, for example “R Essentials” when you try out Data Science Training.

Our blockchain online course will make you learn the core fundamentals of blockchain technology and demonstrate how it adds value to your existing job or business model.

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