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Courses

5 tracks. One outcome: you can do the job.

Each course runs between one and three months, ends in real-time project work, and includes interview preparation. Not sure where to start? SQL first, then ETL Testing, is a path many of our learners followed.

An illustrated study desk with a laptop, a calendar and stacked books labelled SQL, Python, ETL Testing and Data Analytics, beside a card noting 11 courses offered, one to three months per track, 1000+ learners supported and 26+ years of experience

Every track we teach

11 courses
Data Engineering1 month

SQL

Write production-grade queries and validate data like a working engineer.

Master SQL from Basics to Advanced including Joins, Subqueries, CTEs, Window Functions, ETL Validation and Real-Time Projects with Interview Preparation.

Beginner to AdvancedSyllabus
Data Engineering2 months

PySpark

Process data at enterprise scale with Spark.

Learn Big Data processing using PySpark, DataFrames, Spark SQL, transformations, actions, and data validation for enterprise-level applications.

IntermediateSyllabus
Data Engineering1 month

Data Warehousing

The conceptual backbone every data and ETL role assumes you already have.

Understand Data Warehouse architecture, dimensional modeling, fact and dimension tables, ETL processes, and business intelligence concepts.

BeginnerSyllabus
Quality & Testing2 months

ETL Testing

The flagship track behind most of our MNC placements.

Master ETL Testing concepts including data validation, source-to-target testing, data warehouse testing, SQL validation, and real-time project scenarios.

Beginner to AdvancedSyllabus
Quality & Testing3 months

Automation Testing

Build test frameworks teams actually maintain.

Gain expertise in Selenium, API Testing, Test Automation Frameworks, Python Automation, and industry-standard testing practices.

Beginner to AdvancedSyllabus
Cloud Platforms2 months

Databricks

The lakehouse skillset showing up in every data engineering JD.

Learn Databricks for Big Data and Cloud Analytics, including Spark, Delta Lake, Data Engineering, ETL pipelines, and real-world projects.

IntermediateSyllabus
Cloud Platforms2 months

Azure Data Factory

Orchestrate cloud ETL end to end on Azure.

Learn Azure Data Factory pipelines, data integration, cloud ETL processes, triggers, monitoring, and real-world data migration projects.

IntermediateSyllabus
Cloud Platforms2 months

Snowflake

Own the cloud warehouse that modern data teams run on.

Master Snowflake Cloud Data Warehouse, including SQL, data loading, Snowpipe, Time Travel, Streams, Tasks, and real-world data engineering projects.

IntermediateSyllabus
Programming3 months

Python

Go from first script to shipping automation and data pipelines in Python.

Learn Python programming from basics to advanced concepts including OOPs, File Handling, APIs, Pandas, Automation, and real-world project development.

Beginner to AdvancedSyllabus
Programming1 month

NumPy

The numerical foundation under Pandas, Spark and every ML stack.

Master NumPy for numerical computing, arrays, mathematical operations, data manipulation, and performance optimization in Python applications.

BeginnerSyllabus
Analytics & BI2 months

Power BI

Turn raw tables into dashboards leadership actually reads.

Learn Power BI from basics to advanced, including data modeling, DAX, Power Query, dashboard creation, data visualization, and business reporting.

Beginner to AdvancedSyllabus