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Big Data Fundamentals Training

Live Online & Classroom Enterprise Training

Learn how big data is driving organisational change and essential analytical tools and techniques, including data mining and PageRank algorithms.

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What is Big Data Fundamentals Training about?

This Big Data MicroMasters course will teach you how big data drives organisational change and the fundamental issues businesses confront when attempting to analyse enormous data sets. 

Fundamental approaches such as data mining and stream processing will be covered. You'll also learn how to build and execute PageRank algorithms with MapReduce, a programming paradigm that enables huge scalability over hundreds or thousands of computers in a Hadoop cluster. You'll discover how big data has enhanced web search and how online advertising works. 

What are the objectives of Big Data Fundamentals Training ?

Knowledge and application of MapReduce 

Understanding the rate of occurrences of events in big data 

How to design algorithms for stream processing and counting of frequent elements in Big Data 

Understand and design PageRank algorithms 

Understand underlying random walk algorithms 

Who is Big Data Fundamentals Training for?

  • Network Operation Managers 
  • Financial Managers 
  • CRM Managers 
  • Top IT Managers in Telco Office 
  • Business Analysts in Telco 
  • QA Managers 

What are the prerequisites for Big Data Fundamentals Training?

  • Big Data Fundamentals 
  • Programming for Data Science  
  • Computational Thinking 

Available Training Modes

Live Online Training

60 Hours

Self-Paced Training

60 Hours

Course Outline Expand All

Expand All

  • Understand the four V’s of Big Data (Volume, Velocity, and Variety); Build models for data; Understand the occurrence of rare events in random data.
  • Understand characteristics of the web and social networks; Model social networks; Apply algorithms for community detection in networks.
  • Clustering social networks; Applying hierarchical clustering; Applying k-means clustering.
  • Understand the concept of PageRank; Implement the basic; PageRank algorithm for strongly connected graphs; Implement PageRank with taxation for charts that are not firmly connected.
  • Understand the architecture for massive distributed and parallel computing; Apply MapReduce using Hadoop; Compute PageRank using MapReduce.
  • Measure the importance of words in a collection of documents; Measure the similarity of sets and documents; Apply local sensitivity hashing to compute similar documents.
  • Understand the importance of frequent item sets, Design association rules, and Implement the A-priori algorithm.
  • Understand the differences between recommendation systems; Design content-based recommendation systems; Design collaborative filtering recommendation systems.
  • Understand the AdWords System; Analyse online algorithms in terms of competitive ratio; Use online matching to solve the AdWords problem.
  • Understand types of queries for data streams; Analyse sampling methods for data streams; Count distinct elements in data streams; Filter data streams.

Who is the instructor for this training?

The trainer for this Big Data Fundamentals Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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