Data Science and Big Data Analytics (MR-1CP-DSBDA) – Outline

Detailed Course Outline

Module 1 - Introduction to Big Data analytics
  • Big Data and its characteristics Lesson
  • Business value from Big Data
  • Data scientist
Module 2 – Data Analytics Lifecycle
  • Data analytics lifecycle overview
  • Discovery phase
  • Data preparation phase
  • Model planning phase
  • Model building phase
  • Communicate results phase
  • Operationalize phase
Module 3 – Basic data analytics methods using R
  • Introduction to the R programming language
  • Analyzing and exploring data
  • Statistics for model building and evaluation
Module 4– Advanced analytics theory and methods
  • Introduction to advanced analytics—theory and methods
  • K-means clustering
  • Association rules
  • Linear regression
  • Logistic regression
  • Text analysis
  • Naïve Bayes
  • Decision trees
  • Time series analysis
Module 5: Advanced analytics—technology and tools
  • Introduction to advanced analytics—technology and tools
  • Hadoop ecosystem
  • In-database analytics SQL essentials
  • Advanced SQL and MADlib
Module 6: Putting it all together
  • Preparing to operationalize
  • Preparing project presentations
  • Data visualization techniques