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Big Data Analytics Course

Handle massive datasets with Apache Spark, Hadoop, and cloud platforms. Learn distributed computing and real-time analytics to process terabytes of data and extract valuable insights at enterprise scale.

Apache Spark & Hadoop
Cloud Platform Integration
Distributed Computing
Real-time Stream Analytics

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Big Data Analytics Course

Course Overview

Key Features

  • Complete 10-Lesson Big Data Ecosystem covering from fundamentals to advanced applications
  • Industry-Standard Technology Stack including Hadoop, Spark, Kafka, and NoSQL databases
  • Hands-on Experience with distributed computing frameworks and cloud architectures
  • Real-world Use Cases across retail, fraud detection, and healthcare analytics domains
  • End-to-End Pipeline Development from data ingestion to real-time analytics
  • Comprehensive Capstone Project building complete big data solution on public datasets

Skills You'll Master

  • Big Data Fundamentals: 3 Vs concepts, processing paradigms, and scalability principles
  • Distributed Computing: Hadoop HDFS, MapReduce, Spark architecture, and PySpark programming
  • Data Storage Systems: NoSQL databases (MongoDB, Cassandra), sharding, and replication strategies
  • Stream Processing: Real-time data ingestion with Kafka, event-driven pipelines, and low-latency analytics
  • ETL at Scale: Big data wrangling, schema-on-read vs schema-on-write, and workflow orchestration
  • Architecture Design: Data lake vs data warehouse concepts, distributed file systems, and scalability patterns

Curriculum Details

Eligibility:
Data analysis experience and programming knowledge required
Prerequisites:
Python/Java/Scala proficiency and SQL experience
Duration:
12 weeks intensive advanced program
Download Complete Curriculum