Big Data Analytics (Long-Term Course)

Course Content

  • What is Big Data & Data engineering?
  • Importance of Data engineering in the Big Data world
  • Role of RDBMS (SQL Server), Hadoop, Spark, NOSQL and Cloud computing in Data engineering
  • What is Big Data Analytics
  • Key terminologies (Data Mart, Data ware house, Data Lake, Data Ocean, ETL, Data Model, Schema, Data pipeline etc)
  • Data Analytics ā€“ Mining and Analysis of Big Data
  • Associative Rule Mining
  • Introduction to Big Data
  • Big Data: A Small Introduction
  • Introduction to Clustering Analysis
  • Clustering Analysis
  • Experimentation and Active Learning
  • Introduction to Experimentation and Active Learning
  • An Introduction to Online Learning ā€“ Reinforcement Learning

 

What you will learn

  • How to develop algorithms for the statistical analysis of big data;
  • Knowledge of big data applications;
  • How to use fundamental principles used in predictive analytics;
  • Evaluate and apply appropriate principles, techniques and theories to large-scale data science problems.
  • Identify big data application areas;
  • use big data frameworks;
  • model and analyses data by applying selected techniques;
  • demonstrate an integrated approach to big data;
  • and participate effectively in a team working with big data experts

 

Requirements & who can attend

IT/ ITES, Business Intelligence, Database professionals/ computer science (or any other circuit branches) graduates who are not just looking for generic Hadoop training for Data Engineering role, but want Big Data Engineering certification based on practical Hadoop-Spark and Cloud Computing skills

Learn by doing

Able to:

  • Define association rule mining
  • Explain mining frequent patterns and rules
  • Define the apriori algorithm.
  • List the four Vā€™s of Big Data
  • Explain why social media data can be hard to disambiguate
  • Able to distinguish between clustering and classification
  • Explain why clustering is used

Course at a Glance

Price:

Starting and Ending Date

Last Date of Registration

Class Schedule

Enroll Now

Resource Person