Professional certification in Big Data

BIG DATA ANALYTICS TRAINING

Our IT training courses are developed with industry-standards and career-focused technologies.


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Duration & Study Mode:
Full time, Part time, Evening and Weekends, Virtual online
Location:
London, Flexible online
Duration: 5 Days / 5 Weeks

Big Data is no more a buzz word in the IT industry’s across the world, rather it is considered as one of the integrated parts of businesses regardless of the type and size of the business. The content of this training course will help you to learn about linear regression using one of the most widely used high-level programming languages using R. This course will also help you know and learn about the ways to interpret outputs from R. Gradually, you will learn how to use models in order to predict a response variable and validate the prediction of the model. Later, you will learn to work on the R programming language with multiple variables and the ways to select the most appropriate model by going through the most appropriate model from the output of the R programming language.

Later, we will let you know about the process to work on configurable nested data frames in R programming language. Through this course, you will also learn to implement simultaneous linear model, using R. Then, you will know and learn about the processes of working with Linear Regression (LR), Generalized Linear Models (GLMs) and Linear Discriminant Analysis (LDA). The last part of this training course is focused on supervised machine learning and deep learning.

Prerequisites

  • You are required to have fluency in at least one or more high-level programming languages.
  • You must have strong knowledge of Data Warehousing.
  • Having fundamental knowledge of computational frameworks is ideal but not required.
  • It is expected that you have the required knowledge of statistics.
  • You are also expected to have a fundamental knowledge of the Business Process of the organization.

What will you gain after this course

  • You will be considered as a certified Big Data Analyst
  • With the help of this course, you can work at different and diversified job roles, related to Big Data.
  • This Course will give you excellent job opportunities in different industries in the market.

Jobs you can get
with a Big Data Analytics Certification

  • Big Data Analyst
  • Big Data Engineer
  • Data Engineer
  • Data Scientist
  • Technical Advisor – Data Science

Corporate Group Training

  • Customized Training
  • Onsite / Virtual
  • Instructor-led Delivery
  • For small to large groups

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Who is this certification for?

  • IT professionals, who are willing to develop their work on Big Data, are the key target audience of this training course.
  • IT professionals who are responsible for extracting and analyzing the data from different and diversified unstructured sources in order to make a better business prediction are also the key audience of this training course.
  • Particularly those who are willing to develop their career as a Data Analyst and/or Data Scientists can consider this Big Data Analytics training course as one of the best options for their career path.

Syllabus

  • Big Data Characteristics, Challenges with traditional system
  • Hadoop Overview
  • Anatomy of Hadoop Cluster, Installing and Configuring Hadoop
  • Hands-On Exercise
  • Name Nodes and Data Nodes
  • Hands-On Exercise
  • HDFS Introduction 
  • The HDFS command line and web interfaces
  • The HDFS Java API (lab)
  • How Map Reduce Works?
  • The Mapper & Reducer, Input Formats & Output Formats, Data Type & Customer Writable
  • Setting up Eclipse Development Environment, Creating Map Reduce Projects,Debugging and Unit Testing MapReduce Code, Testing with MRUnit
  • More common algorithms: sorting, indexing and searching (lab)
  • Hive, pig & Mahout : Hands-On Exercise
  • Introduction to R tool
  • R and Hadoop Integration
  • Hadoop Streaming using R
  • RHadoop Overview
  • RHive Overview
  • Analytics Project Overview
  • Steps Invovled in Aanlytics Project
  • Analytics Techniques and Applications in Business
  • Implications of Big Data on Analytics

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