About Big Data Analytics & Fundamental Data Science

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The Big Data Analytics & Fundamental Data Science course provides IT and business professionals with practical skills in big data analytics and a foundational understanding of data science. It covers big data from both business and technology perspectives, including core concepts, models, benefits, challenges, and adoption considerations. The course also explores contemporary data analysis practices, tools, and technologies used in big data environments.

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Program Structure  

• 100% online  

• Self-paced  

• 3 modules (30 hours total)  

• Includes lessons, examples, and exercises  

• Certificate of Completion provided  

 

Modules

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Fundamental Big Data Science & Analytics 

• Big data concepts, terminology, and business/technology drivers

• Traditional technologies and how they relate to big data (OLTP, OLAP, ETL, data warehouses)

• Structured, unstructured, and semi-structured data types and characteristics

• Data quality, metadata, and veracity in big data environments

• Fundamentals of data analysis: quantitative, qualitative, and machine learning types

• Descriptive, diagnostic, predictive, and prescriptive analytics

• Business intelligence, data visualization, and planning for big data adoption

 

Big Data Analysis &Technology Concepts 

• The big data analysis lifecycle: from business case to visualization

• Core techniques: A/B testing, regression, correlation, heat maps, time series, and network analysis

• Clustering, classification, and filtering (collaborative & content-based)

• Text and sentiment analysis in big data

• Batch vs. transactional processing workloads

• How cloud computing supports big data

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Big Data Analysis & Technology Lab 

• This module includes practical lab exercises designed to provide hands-on experience with big data environments, data analysis, customer insights, personalized solutions, and predictive analytics to strengthen your real-world skills.