Course Overview
This comprehensive Data Engineering course is designed to take you from core programming foundations to advanced cloud-based data systems. The curriculum covers:
Core Foundations: Mastery of Python, SQL, NoSQL, and essential libraries like Numpy and Pandas.
Big Data & Cloud: In-depth training on Hadoop, PySpark, and Kafka, along with major cloud platforms including AWS, Azure, and GCP.
Data Architecture: Designing ETL pipelines, Data Warehousing (Star and Snowflake Schema), and using tools like Apache NiFi and AWS Glue.
Advanced Operations: Learning DataOps, CI/CD pipelines (Jenkins, GitLab), and containerization with Docker and Kubernetes.
Career Support: Extensive placement assistance, live projects, and a global toolkit for international job applications.
Data Science January batches starting soon.
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Admission NowThe course includes work on real-world, industry-relevant live projects. Examples of these projects include creating a Ride Data Processing System for Uber, a Streaming Analytics Dashboard for YouTube, and an Inventory Forecasting Pipeline for Amazon.
Yes, the course offers a specific "Global Jobs Applying Toolkit" that teaches you how to build resumes for US, Europe, and Australian standards and how to get selected for visa-sponsored jobs. Additionally, you get 2 months of Spoken English classes at no extra cost to improve fluency and workplace communication.
The Advanced DataOps module covers high-availability designs and CI/CD pipelines using Jenkins and GitLab. It also trains you in containerization technologies like Docker and Kubernetes, as well as infrastructure tools like Terraform.
Prepare to build scalable and reliable data systems with a curriculum that bridges the gap between programming basics and modern industry requirements. This course starts by solidifying your programming skills in Python and SQL to help you solve complex data problems. You will progress to mastering Big Data technologies and cloud services, learning how to store and process data using services like S3 and BigQuery.
Beyond storage, the course focuses on execution. You will gain expertise in ETL and Data Warehousing, learning to design efficient pipelines and handle data ingestion. The training extends to Advanced DataOps, ensuring you can build secure, fault-tolerant systems using encryption, RBAC, and Terraform. To ensure you are future-ready, the syllabus also includes basics of Machine Learning and an introduction to Agentic AI.