Master Big Data tools like Hadoop/Spark, design ETL pipelines with Airflow, and implement real-time streaming with Kafka. Get job-ready in 3 months with hands-on cloud projects.
This intensive 3-month professional program transforms beginners into job-ready Big Data and ETL Developers. Learn to build, automate, and optimize enterprise-scale data pipelines using the Hadoop Ecosystem, Spark, Kafka, Airflow, and leading Cloud Data Platforms like AWS Redshift and GCP BigQuery.
Apply your learning through real-world projects that build your portfolio and showcase your skills
Progress through our comprehensive program which makes qualified professional to earn their awards
Begin your journey with foundational skills and basic certification.
Master the most in-demand tools and technologies for data analytics
Hear from our students who have transformed their careers with our courses
Discover the difference between Edjamon and traditional learning platforms
Features & Criteria | EdJAMON | Other Platforms |
---|---|---|
Duration | 3 Months (intensive, professional program) | 3–6 Months (varying duration, often less focused) |
Learning Format | Live Classes + Mentor Support + Hands-on Projects | Mostly self-paced/recorded videos or large batch live classes |
Core Focus | Deep ETL, Real-Time Streaming, Cloud Data Pipelines | May focus more on basic data analytics rather than deep ETL |
Data Governance/Security | Strong emphasis on best practices for Governance, Security, and Optimization | Weak focus on data governance/security or performance optimization |
Real-Time Streaming | Dedicated module on Kafka + Spark Streaming and real-time ETL | May not always include real-time streaming in depth |
Cloud Tools | AWS Redshift, GCP BigQuery, Azure Data Factory for deployment | Limited exposure to end-to-end cloud deployment |
Mentorship & Code Reviews | Exceptional mentors, small batches, and frequent code review feedback | Mentorship minimal or uneven quality; large batch sizes |
Capstone Project | End-to-end pipeline simulating industry use cases | Short courses lack capstone scale or production-level deployment |
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