Objectives

• • Understand the main concepts of big data.• Understand the main concepts of big data analytics.• Understand data analysis life cycle.• Understand the different types of data analysis.• Understand and explain the evolution of a modern data center computing platform.

Outcomes

• Understanding the main concepts of big data. • Understanding the main concepts of big data analytics and how we can make use of big data insights.• Understand data analysis life cycle.• Understand the different types of data analysis.• Understand and explain the evolution of a modern data center computing platform.• Understanding the distributed scalable big data platform.• Qualifying our students for the increasing demand in the ICT market for IoT, big data and analytics engineers.

Course Contents

• Data and IoT.• Sensors as a major source for big data.• Difference between data and big data.• Understanding big data and analytics concepts.• Big data characteristics.• Data at rest.• Data in motion (transit).• Data in use.• Structured data.• Unstructured data.• Open and private data.• Exploratory data.• Data management.• Data acquisition.• Big Data and IoT systems. • Ethical use of big data.• Data analysis.• Data analytics models.• Descriptive analysis.• Predictive analysis.• Prescriptive analytics.• Statistical analysis.• Machine learning analysis.• Model evaluation.• Validity and reliability.• Errors in data analytics.• Visual representations of data. • Data analysis scalability.• Data engineering.• Big data pipe line.• Storytelling and data.• Big data Architecture.

Description

Data will be available soon!