Interview-based admission. Enrollment only after selection. Understand the process
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WHAT YOU LEARN

Learn the tools.
Understand the system.

SQL, Python, PySpark and the engineering tools behind reliable pipelines. Learn through self-paced content or mentorship guidance, then apply the skills across 15–20 projects.

See project workHow admission works
15–20 projectsSelf-paced or mentoredCareer preparation & application support
SQL / PYTHON / PYSPARKPROJECTS / AI / MENTORSHIPINTERVIEWS / YOUR NEXT ROLE
Explore the connections with your cursorLearn. Build. Explain. Get ready for the role.
ENGINEERING SKILLS. GUIDED PROJECTS. LEARNING AND CAREER SUPPORT.View the curriculum
Engineering learning path

Foundations first.
Project depth next.

01SQL & data modeling

Queries, joins, aggregations and data modeling. Understand the source data, relationships and expected analytical output.

What you practise: A query-based transformation and a documented data model.
02Python & engineering foundations

Read and transform data, write reusable functions, handle errors and use Git, Linux and shell tools in your workflow.

What you practise: A Python data-processing workflow with checks and error handling.
03PySpark & large-scale processing

Work with DataFrames, joins, partitions and transformations. Investigate skew, execution plans and performance trade-offs.

What you practise: A Spark pipeline with a performance investigation.
04AWS data engineering services

Work with Amazon S3 for data storage, AWS Glue and its Data Catalog for integration and metadata, Amazon EMR for Spark processing, Amazon Athena for querying, Amazon Redshift for warehousing and Amazon Kinesis Data Streams for streaming ingestion.

What you practise: A source-to-analytics AWS pipeline using services appropriate to the project.
05Azure data engineering services

Work with Azure Data Lake Storage Gen2 and Azure Blob Storage, Azure Data Factory for data pipelines, Azure Databricks for transformations, Azure Synapse Analytics for analytics and Azure Event Hubs for streaming ingestion.

What you practise: An Azure data pipeline from ingestion through transformation and analytical output.
06Warehousing & orchestration

Design analytical datasets and scheduled workflows with Snowflake, Databricks and Airflow. Apply warehouse or lakehouse concepts and investigate failed runs.

What you practise: An orchestrated pipeline with a clear warehouse or lakehouse design.
07AI-assisted engineering

Use AI to help draft SQL/Python, investigate errors, suggest tests and document the pipeline. Verify the output against the schema, sample data and your own reasoning.

What you practise: An AI-assisted task with validation evidence and your corrections.
08Projects, interviews & communication

Apply the learning through 15–20 projects. Practise coding discussions, project walkthroughs, interview answers and communication before career preparation.

What you practise: A project portfolio and explanations you can walk through in an interview.
The engineering toolkit

Learn how the pieces
work together.

Tools are selected to suit the project. The goal is an end-to-end understanding rather than using every service in every pipeline.

CODE & SOURCES

Programming and ingestion

SQL, Python, PySpark, Git, Linux, REST APIs, CSV/JSON/Parquet and relational databases. Practise full/incremental loads and change-data-capture concepts.

PLATFORM & WORKFLOWS

Cloud and analytical systems

AWS S3, Glue, EMR, Athena, Redshift and Kinesis; Azure ADLS Gen2, Blob Storage, Data Factory, Databricks, Synapse and Event Hubs; Snowflake, Delta Lake, Airflow, Kafka and dbt.

RELIABILITY & AI

Operate and explain the pipeline

Data-quality checks, testing, logs, retries, idempotent reruns, partitioning, performance, access-control concepts and cost awareness. Use AI for assistance while validating code and keeping sensitive data out of prompts.

Illustration of connected data platforms and guided engineering learning
Learn through the work

From a concept
to a working pipeline.

Learn the required skills before interview readiness. Build, test and document your projects so your portfolio shows the work behind your understanding.

Explore one-to-one mentorship
Selected through an interview

Your next role starts
with your readiness to learn.

We assess your capability and learning intent before offering enrollment.

Apply for the admission interview