Cloud Computing for Big Data
( 25 Modules )

Module #1
Introduction to Cloud Computing
Overview of cloud computing, its benefits, and key characteristics

Module #2
Big Data and its Challenges
Understanding big data, its types, and the challenges associated with it

Module #3
Cloud Computing for Big Data
How cloud computing addresses big data challenges and its benefits

Module #4
Cloud Service Models
IaaS, PaaS, and SaaS service models, their differences, and use cases

Module #5
Cloud Deployment Models
Public, Private, Hybrid, and Community cloud deployment models, their differences, and use cases

Module #6
Cloud Providers Overview
Overview of popular cloud providers such as AWS, Azure, Google Cloud, and IBM Cloud

Module #7
Data Ingestion in Cloud
Ways to ingest big data into cloud storage, e.g., data lakes, data warehousing

Module #8
Cloud Storage Options
Object storage, block storage, and file storage options in cloud, e.g., S3, Blob Storage

Module #9
Cloud Computing for Batch Processing
Using cloud computing for batch processing, e.g., Hadoop, Spark

Module #10
Cloud Computing for Real-time Processing
Using cloud computing for real-time processing, e.g., stream processing, IoT

Module #11
Cloud-based Data Processing Tools
Overview of cloud-based data processing tools, e.g., AWS Glue, Azure Data Factory

Module #12
Cloud-based Data Warehousing
Cloud-based data warehousing solutions, e.g., Amazon Redshift, Google BigQuery

Module #13
Cloud-based NoSQL Databases
Cloud-based NoSQL databases, e.g., Amazon DynamoDB, Google Cloud Firestore

Module #14
Security and Compliance in Cloud
Security and compliance considerations in cloud computing for big data

Module #15
Cost Optimization in Cloud
Cost optimization strategies for big data workloads in cloud

Module #16
Cloud-based Machine Learning
Using cloud computing for machine learning and AI workloads, e.g., AWS SageMaker, Google Cloud AI Platform

Module #17
Big Data Analytics in Cloud
Big data analytics in cloud using tools, e.g., Apache Hive, Apache Pig

Module #18
Cloud-based Data Visualization
Cloud-based data visualization tools, e.g., Tableau, Power BI

Module #19
Cloud-based IoT Analytics
Using cloud computing for IoT analytics and edge computing

Module #20
Cloud-based Streaming Analytics
Cloud-based streaming analytics using tools, e.g., Apache Kafka, Apache Flink

Module #21
Cloud-based Governance and Quality
Governance and quality considerations for big data in cloud

Module #22
Cloud Migration Strategies
Strategies for migrating big data workloads to cloud

Module #23
Cloud-based Big Data Case Studies
Real-world case studies of big data in cloud

Module #24
Cloud-based Big Data Best Practices
Best practices for big data in cloud, including architecture, security, and cost optimization

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

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Cloud Computing for Big Data ( 25 Modules )

Cloud Computing for Big Data
( 25 Modules )