Big Data Mining
( 24 Modules )

Module #1
Introduction to Big Data
Overview of big data, its characteristics, and its importance

Module #2
Big Data Mining Concepts
Fundamentals of data mining, data preprocessing, and data warehousing

Module #3
Hadoop and Distributed Computing
Introduction to Hadoop ecosystem and distributed computing concepts

Module #4
MapReduce Programming
Basics of MapReduce programming and its applications

Module #5
Hive and Pig
Introduction to Hive and Pig, and their role in big data querying

Module #6
NoSQL Databases
Overview of NoSQL databases, including HBase, Cassandra, and MongoDB

Module #7
Data Ingestion and Streaming
Techniques for ingesting and processing high-volume and high-velocity data

Module #8
Data Preprocessing and Cleaning
Methods for preprocessing and cleaning big data

Module #9
Data Visualization
Techniques for visualizing big data insights and trends

Module #10
Supervised Learning
Introduction to supervised learning, regression, and classification

Module #11
Unsupervised Learning
Introduction to unsupervised learning, clustering, and dimensionality reduction

Module #12
Clustering Algorithms
Details of clustering algorithms, including k-means and hierarchical clustering

Module #13
Decision Trees and Random Forests
Introduction to decision trees and random forests algorithms

Module #14
Association Rule Mining
Techniques for discovering patterns and associations in big data

Module #15
Text Mining and Sentiment Analysis
Introduction to text mining and sentiment analysis techniques

Module #16
Big Data Analytics Tools
Overview of big data analytics tools, including R, Python, and Spark

Module #17
Apache Spark
In-depth coverage of Apache Spark, including Spark MLlib and Spark SQL

Module #18
Real-Time Big Data Analytics
Techniques for real-time big data analytics and stream processing

Module #19
Big Data Security and Governance
Importance of security and governance in big data analytics

Module #20
Big Data Ethics
Ethical considerations in big data analytics, including privacy and bias

Module #21
Case Studies in Big Data Mining
Real-world case studies of big data mining applications

Module #22
Big Data Mining Project Development
Guided project development in big data mining

Module #23
Big Data Mining Best Practices
Best practices and common pitfalls in big data mining

Module #24
Course Wrap-Up & Conclusion
Planning next steps in Big Data Mining career

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Big Data Mining ( 24 Modules )

Big Data Mining
( 24 Modules )