About The Essential Big Data & Data Science

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The Essential Big Data & Data Science course provides a clear and practical introduction to big data and data science from both business and technology perspectives. It builds foundational knowledge of how big data works, how data is analyzed, and how insights are generated and applied in real-world environments. The course highlights key benefits, challenges, risks, and adoption considerations associated with big data initiatives.

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Program Structure  

• 100% online  

• Self-paced  

• 2 modules (20 hours total)  

• Includes lessons, examples, and exercises  

• Certificate of Completion provided  

 

Modules

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Fundamental Big Data Science & Analytics 

• Core big data concepts, terminology, and data characteristics

• Business and technology drivers for big data adoption

• Traditional enterprise systems and their relationship to big data (OLTP, OLAP, ETL, data warehouses)

• Structured, unstructured, and semi-structured data, including metadata and data quality

• Fundamentals of analytics, analysis types, and machine learning concepts

• Business intelligence, data visualization, and big data planning considerations

 

Big Data Analysis & Technology Concepts 

• The big data analysis lifecycle, from business case evaluation to data visualization

• Core analytics techniques, including A/B testing, regression, clustering, and classification

• Advanced analysis methods such as time series, network, and spatial analysis

• Filtering, sentiment analysis, and text analytics techniques

• Big data processing models, including batch and transactional workloads

• Big data technology foundations, including cloud computing, storage, and processing engines