What you'll learn:
Big Data Overview
State of the practice in analytics
The role of the Data Scientist
Big Data Analytics in Industry Verticals
Key roles for a successful analytic project
Main phases of the lifecycle
Developing core deliverables for stakeholders
Naive Bayesian Classifier
K-Means Clustering
Association Rules
Decision Trees
Linear and Logistic Regression
Time Series Analysis
Text Analytics
How to operationalize an analytics project
Creating the Final Deliverables
Data Visualization Techniques
Hands-on Application of Analytics Lifecycle to a Big Data Analytics Problem