This Data Engineering course is designed to help students, beginners, and aspiring developers master the skills required to collect, process, transform, and store large volumes of data for analytics. The program covers database management with SQL, programming with Python, Big Data tools like Apache Spark, and workflow orchestration. Students will gain hands-on experience building scalable data pipelines, executing ETL workflows, and working with modern cloud data architectures.
Master the core programming languages essential for manipulating data and querying large relational databases securely.
Design and automate Extraction, Transformation, and Loading processes to move data efficiently across scalable pipelines.
Utilize advanced distributed computing frameworks like Apache Spark and deploy scalable solutions on cloud environments.
Data Engineers are the backbone of any data-driven organization, responsible for constructing and maintaining the architecture that allows data analysts and scientists to extract insights. They are highly sought after to manage massive datasets, build robust data architectures, and ensure data quality. They are responsible for constructing data pipelines, executing ETL workflows, handling Big Data, and managing cloud databases using tools like Python, SQL, Apache Spark, and AWS.
Course Details |
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| Duration | 180 hrs |
| Class Hours | 2 hours/day |
| Mode | Online and Offline |
| Batches | Weekdays |
| Languages | English & Tamil |
Writing scripts for data manipulation, integration, and automation.
Querying relational databases for complex insights and data transformations.
Processing and analyzing massive, large-scale datasets in parallel.
Automating ETL workflows to move data reliably and securely.
Writing scripts for data manipulation, integration, and automation.
Querying relational databases for complex insights and data transformations.
Processing and analyzing massive, large-scale datasets in parallel.
Automating ETL workflows to move data reliably and securely.
Writing scripts for data manipulation, integration, and automation.
Querying relational databases for complex insights and data transformations.
Processing and analyzing massive, large-scale datasets in parallel.
Automating ETL workflows to move data reliably and securely.
Writing scripts for data manipulation, integration, and automation.
Querying relational databases for complex insights and data transformations.
Processing and analyzing massive, large-scale datasets in parallel.
Automating ETL workflows to move data reliably and securely.
Master Python scripting and advanced SQL queries for complex data manipulation.
Design and manage relational and NoSQL databases for analytics applications.
Learn to Extract, Transform, and Load data between diverse and complex systems.
Build and automate robust data pipelines to orchestrate analytical workflows.
Understand big data architecture and frameworks like Hadoop to manage massive datasets.
Process and analyze huge datasets in parallel using the Apache Spark engine.
Leverage modern AWS cloud services to host scalable data warehouses and data lakes.
Work on live, practical data engineering projects to build your portfolio and gain hands-on experience.
| Python | The primary programming language for creating data engineering scripts and automation. |
| SQL | The standard language used for querying, modifying, and managing relational databases. |
| MySQL | An open-source relational database management system for secure and structured data storage. |
| PostgreSQL | An advanced, enterprise-class open-source relational database supporting heavy workloads. |
| Apache Spark | A unified analytics engine for large-scale data processing and machine learning. |
| Hadoop | An open-source software framework for storing and processing large datasets in clusters. |
| Airflow | A platform created by the community to programmatically author, schedule, and monitor workflows. |
| AWS | Amazon Web Services provides scalable cloud infrastructure to host your big data platforms. |
| Git | The industry-standard version control system for tracking source code changes efficiently. |
| GitHub | A cloud-based platform for code hosting, collaboration, and version control management. |
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