Detaillierter Kursinhalt
The following modules and lessons included in this course are designed to support the course objectives:
- Introduction and Course Agenda
- Introduction to Big Data Analytics
-Big Data Overview
-State of the Practice in Analytics
-The Data Scientist
-Big Data Analytics in Industry Verticals
- Data Analytics Lifecycle
- Discovery
- Data Preparation
- Model Planning
- Model Building
- Communicating Results
- Operationalizing
- Review of Basic Data Analytic Methods Using R
- Using R to Look at Data – Introduction to R
- Analyzing and Exploring the Data
- Statistics for Model Building and Evaluation
- Advanced Analytics – Theory And Methods
- K Means Clustering
- Association Rules
- Linear Regression
- Logistic Regression
- Naïve Bayesian Classifier
- Decision Trees
- Time Series Analysis
- Text Analysis
- Advanced Analytics - Technologies and Tools
- Analytics for Unstructured Data - MapReduce and Hadoop
- The Hadoop Ecosystem
- In-database Analytics – SQL Essentials
- Advanced SQL and MADlib for In-database Analytics
- The Endgame, or Putting it All Together
- Operationalizing an Analytics Project
- Creating the Final Deliverables
- Data Visualization Techniques
- Final Lab Exercise on Big Data Analytics