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
