Big Data in the Age of AI
2h 38mBeginner2026-03-16
Authors
Barton Poulson
Professor, Designer, Data Analytics Expert
Course details
Explore the integral relationship between big data and artificial intelligence in this comprehensive course. In this course, Barton Poulson—a professor, consultant, entrepreneur, and data expert—delves into the three Vs of big data: volume, velocity, and variety. Find out how they drive AI advancements. Learn how to handle enormous datasets, use machine learning algorithms, and employ predictive analytics to discover valuable insights. Discover techniques for anomaly detection, text analysis, and sentiment analysis. Understand the ethical considerations, legal implications, and environmental impacts associated with big data usage. Engage with real-world applications and see how big data translates into actionable small data for end-users. By the end of this course, you will be equipped with the skills to transform raw data into powerful, insightful, and practical solutions for your professional needs.
Learning objectives
Identify the components that make up big data.
Examine how big data has grown over the last few years.
Explain the importance of using big data in business organizations.
Distinguish between knowledge requirements for using big data and for understanding data science.
Justify the need for training on big data within an organization.
Analyze the factors that go into utilizing big data on a project.
Differentiate outcomes that are derived from big data from outcomes that are derived from observing behaviors.
Learning objectives
Identify the components that make up big data.
Examine how big data has grown over the last few years.
Explain the importance of using big data in business organizations.
Distinguish between knowledge requirements for using big data and for understanding data science.
Justify the need for training on big data within an organization.
Analyze the factors that go into utilizing big data on a project.
Differentiate outcomes that are derived from big data from outcomes that are derived from observing behaviors.
Skills covered
Data Science FoundationsData EngineeringArtificial Intelligence FoundationsData AnalysisArtificial Intelligence (AI)Data ScienceBusiness Analysis and StrategyBusiness Software and ToolsOne-Off
Concepts
Introduction
- Big data in the age of AI
Defining Big Data
- The volume, velocity, and variety of big data
- Machine learning and predictive AI
- Generative AI
- Agentic AI
- Social media and the Internet of Things
- Data warehouses, data lakes, and the cloud
- Edge computing, fog computing, and local computing
How Is Big Data Used
- Big data for competitive advantage
- Big data for change detection
- Big data as proxy data
Ethics in Big Data
- Big data and privacy
- Intellectual property, corporate data, and generative AI
- Environmental impact of big data and AI
- Social impact of big data and AI
- Data governance
- Laws affecting big data and AI
Data Logistics
- Structured, semi-structured, and unstructured data
- Batch processing vs. stream processing
- An evolving data landscape
- Distributed storage and processing
Analyzing Big Data
- Challenges with data preparation
- Visualizing big data
- Data mining
- Text analytics
- Sentiment analysis
- Predictive analytics
- Anomaly detection
- Retrieval-augmented generation (RAG)
- Using big data to make small data
Continuing Your Big Data in AI Learning Journey
- Next steps and additional resources
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