Programme Coverage for Business Analytics

MODULE 1 - Introduction to Big Data
  • 1.1 Introduction to Big Data
  • 1.2 Business Applications to Big Data
  • 1.3 Technologies for handling Big Data
  • 1.4 Understanding the Hadoop Ecosystem
  • 1.5 Map Reduce Fundamentals
MODULE 2 – Introduction to Analytics and R Programming
  • 2.1 Understanding Analytics
  • 2.2 Analytical Approaches and Tools
  • 2.3 Exporting R
  • 2.4 Reading Datasets into R and exporting data from R
  • 2.5 Manipulating and Processing data in R
MODULE 3 – Data Analytics using R
  • 3.1 Using Functions and Packages in R
  • 3.2 Descriptive Statistics in R
  • 3.3 Analyzing Big Data by Using Functions, Loops and Data Frames
  • 3.4 Graphical Analysis in R
  • 3.5 Hypothesis Testing in R
MODULE 4 - Big Data Analytics Methods
  • 4.1 Implementing a Big data solution
  • 4.2 Data Cleaning and Pre-processing
  • 4.3 Social media analytics and text mining
  • 4.4 Mobile Analytics
  • 4.5 Big Data visualizations
MODULE 5 – Advanced Analytics Using SAS
  • 5.1 Linear Regression in R
  • 5.2 Nonlinear Regression
  • 5.3 Cluster Analysis
  • 5.4 Decision Trees
  • 5.5 Integrating R and Hadoop and Understanding Hive

Additional Modules

1. Data Visualization with Tableau
  • Learn EDA and Basics of Data Visualization
  • Descriptive Analytics and various graphs in Tableau
  • Advanced graphs and features in Tableau
  • Creating dashboards and interactive visualizations in Tableau
2. Machine Learning Concepts
  • Understanding Machine Learning
  • Graphical Models and Bayesian Networks on R
  • Artificial Neural Networks
  • Dimensionality Reduction Using PCA and Factor Analysis in R
  • Support Vector Machines
3. Social Media, Mobile Analytics
  • Big Data Solution engineering
  • Social Media Analytics and Testing Mining
  • Performing Mobile Analytics
  • Big Data Visualization
  • Recruitment readiness