This intensive training course provides theoretical and technical aspects of Data Science and Business Analytics. The course covers the fundamental and advanced concepts and methods of deriving business insights from big” and/or “small” data. This training course is supplemented by hands-on labs that help attendees reinforce their theoretical knowledge of the learned material.
Business success in the information age is predicated on the ability of organizations to convert raw data coming from various sources into high-grade business information.
To stay competitive, organizations have started adopting new approaches to data processing and analysis. For example, data scientists are turning to Apache Spark for processing massive amounts of data using Spark’s distributed compute capability along with its built-in machine learning library, or switching from proprietary and costly solutions to the free R programming language.
- Applied Data Science and Business Analytics
- Algorithms, Techniques and Common Analytical Methods
- Machine Learning Introduction
- Visualizing and Reporting Processed Results
- The R Programming Language
- Data Analysis with R
- Elements of Functional Programming
- Apache Spark Introduction
- Spark SQL
- ETL with Spark
- MLlib Machine Learning Library
- Graph Processing with GraphX
Data Scientists, Software Developers, IT Architects, and Technical Managers