Duration

7 Weeks

Available Sessions

Thursday, Friday, Saturday

Class Timings

10 AM – 1 PM

Seats Available

30

Cloud Computing and Big Data Analytics is a comprehensive course designed to equip learners with the knowledge and practical skills required to manage cloud-based infrastructures and analyze large-scale datasets. The course covers modern cloud computing technologies, virtualization, distributed systems, data storage solutions, and big data processing frameworks. Participants will learn how organizations leverage cloud platforms and data analytics to improve decision-making, enhance operational efficiency, and build scalable, data-driven applications. The course combines theoretical concepts with hands-on experience in cloud services, big data tools, and analytics techniques used across various industries.

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Course Contents

  • Introduction to Cloud Computing
  • Cloud Service Models (IaaS, PaaS, and SaaS)
  • Cloud Deployment Models and Architectures
  • Virtualization and Cloud Infrastructure
  • Cloud Storage and Database Services
  • Cloud Security, Privacy, and Compliance
  • Introduction to Big Data and Data Analytics
  • Big Data Architecture and Ecosystem
  • Distributed Computing Concepts
  • Hadoop Framework and HDFS
  • Data Processing with Apache Spark
  • NoSQL Databases and Data Management
  • Data Warehousing and Data Lakes
  • Data Collection, Integration, and Transformation
  • Real-Time Data Processing and Streaming Analytics
  • Data Visualization and Business Intelligence
  • Machine Learning for Big Data Analytics
  • Cloud-Based Analytics Platforms
  • Scalability, Performance, and Resource Optimization
  • Industry Applications and Emerging Trends

Learning Outcomes

Upon successful completion of this course, participants will be able to understand cloud computing architectures and services, deploy and manage cloud-based resources, process and analyze large datasets using modern big data technologies, utilize distributed computing frameworks, implement data visualization and analytics solutions, apply machine learning techniques to big data environments, and design scalable, secure, and efficient cloud-based systems for real-world applications.