Data Mining for Big Data Analysis
( 25 Modules )

Module #1
Introduction to Data Mining
Overview of data mining, its importance, and applications

Module #2
Big Data Fundamentals
Introduction to big data, its characteristics, and importance

Module #3
Data Preprocessing
Data cleaning, transformation, and quality control for data mining

Module #4
Data Warehousing and OLAP
Introduction to data warehousing and online analytical processing (OLAP)

Module #5
Data Mining Techniques Overview
Introduction to data mining techniques:supervised, unsupervised, and semi-supervised learning

Module #6
Supervised Learning:Regression
Introduction to regression analysis and its applications

Module #7
Supervised Learning:Classification
Introduction to classification techniques:decision trees, random forests, and k-NN

Module #8
Unsupervised Learning:Clustering
Introduction to clustering techniques:k-means, hierarchical, and density-based clustering

Module #9
Unsupervised Learning:Association Rule Mining
Introduction to association rule mining and its applications

Module #10
Text Mining
Introduction to text mining:text preprocessing, sentiment analysis, and topic modeling

Module #11
Network Analysis
Introduction to network analysis:graph theory, network metrics, and community detection

Module #12
Big Data Mining Tools:Hadoop and Spark
Introduction to Hadoop and Spark for big data mining

Module #13
Big Data Mining Tools:NoSQL Databases
Introduction to NoSQL databases for big data mining:HBase, Cassandra, and MongoDB

Module #14
Data Mining for IoT Data
Introduction to IoT data mining:sensor data analysis and IoT applications

Module #15
Data Mining for Social Network Analysis
Introduction to social network analysis:network structure, centrality measures, and community detection

Module #16
Data Mining for Recommendation Systems
Introduction to recommendation systems:content-based, collaborative, and hybrid approaches

Module #17
Data Mining for Time Series Analysis
Introduction to time series analysis:ARIMA, prophet, and LSTM

Module #18
Data Mining for Spatial Data Analysis
Introduction to spatial data analysis:spatial autocorrelation, spatial regression, and geospatial visualization

Module #19
DataVisualization for Big Data
Introduction to data visualization for big data:visualization tools and best practices

Module #20
Evaluating Data Mining Models
Introduction to model evaluation metrics and techniques for data mining models

Module #21
Data Mining for Healthcare Analytics
Introduction to healthcare analytics:disease diagnosis, treatment outcomes, and health informatics

Module #22
Data Mining for Financial Analytics
Introduction to financial analytics:risk analysis, portfolio optimization, and credit scoring

Module #23
Data Mining for Marketing Analytics
Introduction to marketing analytics:customer segmentation, churn prediction, and sentiment analysis

Module #24
Big Data Mining Applications and Case Studies
Real-world applications and case studies of big data mining in various industries

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Data Mining for Big Data Analysis career

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Data Mining for Big Data Analysis ( 25 Modules )

Data Mining for Big Data Analysis
( 25 Modules )