Big Data Analytics
( 25 Modules )

Module #1
Introduction to Big Data
Defining big data, its characteristics, and importance in business decision-making

Module #2
Big Data Analytics Overview
Understanding the different types of analytics, and the role of big data analytics in business

Module #3
Big Data Technologies
Overview of Hadoop, Spark, NoSQL databases, and other big data technologies

Module #4
Hadoop Ecosystem
In-depth look at Hadoop, including HDFS, MapReduce, and YARN

Module #5
Spark Fundamentals
Introduction to Apache Spark, its architecture, and use cases

Module #6
NoSQL Databases
Understanding the different types of NoSQL databases, including key-value, document, and graph databases

Module #7
Data Ingestion and Processing
Collecting, processing, and storing big data using tools like Flume, Kafka, and NiFi

Module #8
Data Storage and Management
Designing and implementing data storage solutions using HDFS, HBase, and Cassandra

Module #9
Data Warehousing and ETL
Building data warehouses and performing ETL (Extract, Transform, Load) operations

Module #10
Big Data Analytics Tools
Overview of big data analytics tools, including Hive, Pig, and Spark SQL

Module #11
Machine Learning Fundamentals
Introduction to machine learning concepts, including supervised and unsupervised learning

Module #12
Machine Learning with Spark
Building machine learning models using Spark MLlib and Spark ML

Module #13
Deep Learning with Big Data
Introduction to deep learning concepts and techniques, including neural networks and convolutional neural networks

Module #14
Text Analytics and NLP
Analyzing and processing unstructured data using natural language processing (NLP) techniques

Module #15
Data Visualization for Big Data
Visualizing big data insights using tools like Tableau, Power BI, and D3.js

Module #16
Big Data Use Cases and Applications
Exploring real-world use cases and applications of big data analytics in various industries

Module #17
Big Data Security and Governance
Ensuring data security, privacy, and compliance in big data environments

Module #18
Big Data Analytics with Python
Using Python for big data analytics, including data manipulation, visualization, and machine learning

Module #19
Big Data Analytics with R
Using R for big data analytics, including data manipulation, visualization, and machine learning

Module #20
Big Data Analytics on the Cloud
Deploying big data analytics on cloud platforms, including AWS, Azure, and GCP

Module #21
Real-time Big Data Analytics
Designing and implementing real-time big data analytics solutions using tools like Apache Storm and Apache Flink

Module #22
Big Data Quality and Governance
Ensuring data quality, integrity, and governance in big data environments

Module #23
Big Data Analytics Case Studies
Exploring real-world case studies and success stories of big data analytics in various industries

Module #24
Big Data Analytics Best Practices
Best practices and guidelines for implementing big data analytics projects

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

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Big Data Analytics ( 25 Modules )

Big Data Analytics
( 25 Modules )