Big Data Analytics with Machine Learning
( 30 Modules )

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

Module #2
Hadoop and Distributed Computing
Introduction to Hadoop, HDFS, MapReduce, and distributed computing concepts

Module #3
NoSQL Databases
Overview of NoSQL databases, including HBase, Cassandra, and MongoDB

Module #4
Data Ingestion and Processing
Introduction to data ingestion tools like Flume, Sqoop, and data processing frameworks like Spark

Module #5
Data Warehousing and ETL
Overview of data warehousing, ETL (Extract, Transform, Load) process, and tools like Hive and Pig

Module #6
Introduction to Machine Learning
Overview of machine learning, types of machine learning, and supervised/unsupervised learning

Module #7
Machine Learning with Python
Introduction to Python libraries like Scikit-learn, TensorFlow, and Keras for machine learning

Module #8
Data Preprocessing and Feature Engineering
Importance of data preprocessing, feature scaling, and feature selection

Module #9
Supervised Learning
Introduction to supervised learning, regression, and classification algorithms

Module #10
Unsupervised Learning
Introduction to unsupervised learning, clustering, and dimensionality reduction

Module #11
Model Evaluation and Selection
Metrics for evaluating machine learning models, and model selection techniques

Module #12
Big Data Machine Learning with Spark MLlib
Introduction to Spark MLlib, machine learning with Spark, and distributed machine learning

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

Module #14
Big Data Analytics with R
Introduction to R language, data visualization, and statistical analysis

Module #15
Big Data Analytics with Tableau
Introduction to Tableau, data visualization, and business intelligence

Module #16
Case Studies in Big Data Analytics
Real-world case studies in big data analytics, including sentiment analysis, recommender systems, and more

Module #17
Big Data Security and Governance
Importance of big data security, governance, and regulatory compliance

Module #18
Big Data Analytics in Industry
Applications of big data analytics in various industries, including healthcare, finance, and retail

Module #19
Big Data Analytics in IoT and Edge Computing
Applications of big data analytics in IoT and edge computing

Module #20
Scalable Machine Learning with Apache Spark
Scalable machine learning with Apache Spark, including distributed machine learning

Module #21
Big Data Analytics with Graph Databases
Introduction to graph databases, graph analytics, and applications

Module #22
Big Data Analytics with Time-Series Data
Introduction to time-series data, time-series analysis, and forecasting

Module #23
Big Data Analytics with Text Data
Introduction to text data, text analytics, and natural language processing

Module #24
Big Data Analytics with Image and Video Data
Introduction to image and video data, computer vision, and deep learning

Module #25
Big Data Analytics with Streaming Data
Introduction to streaming data, stream processing, and real-time analytics

Module #26
Big Data Analytics with Cloud Computing
Introduction to cloud computing, cloud-based big data analytics, and cloud-based machine learning

Module #27
Big Data Analytics with Docker and Containerization
Introduction to Docker, containerization, and containerized big data analytics

Module #28
Big Data Analytics with Kubernetes
Introduction to Kubernetes, container orchestration, and Kubernetes-based big data analytics

Module #29
Big Data Analytics Project Development
Guided project development in big data analytics, including dataset selection, data preprocessing, and model deployment

Module #30
Course Wrap-Up & Conclusion
Planning next steps in Big Data Analytics with Machine Learning career

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Big Data Analytics with Machine Learning ( 30 Modules )

Big Data Analytics with Machine Learning
( 30 Modules )