Big Data with Apache Spark

Process terabytes of data with Spark, Databricks and the modern data stack

★ 4.6 (5,670 students) · 40 hours total · Certificate of completion

Created by Deepak Rao

What you'll learn

Build distributed data processing pipelines with PySpark

Architect a lakehouse with Delta Lake on Databricks

Process real-time streams with Spark Streaming & Kafka

Optimise Spark jobs for cost and performance

Orchestrate data pipelines with Apache Airflow

Implement data quality checks and lineage tracking

About This Course

Learn to engineer and process big data pipelines using Apache Spark on Databricks. Build batch and streaming pipelines, optimise queries, and integrate with the modern lakehouse architecture.

Course Curriculum

8 weeks · 40 hours total

Requirements

Python intermediate level
SQL proficiency
Basic cloud knowledge

Your Instructor

Deepak Rao

Data Science Expert

An industry practitioner actively working in Data Science. Brings real-world experience and production-grade examples to every session. Known for clear explanations and strong student outcomes.

★ 4.6 instructor rating · 5,670 students taught

Student Reviews

4.6

★★★★★

Course Rating

5★ 68%

4★ 24%

3★ 6%

2★ 1%

1★ 1%

Ravi M.

2 weeks ago

★★★★★

Absolutely fantastic course! The instructor explains complex concepts with ease, and the hands-on projects really solidified my understanding. Already applied several techniques at work.

Sakshi T.

1 month ago

★★★★★

Best course I've taken on this topic. The live sessions are incredibly valuable — you can ask questions in real time and get immediate feedback. Worth every rupee!

Karthik R.

1 month ago

★★★★

Very practical and well-paced. The project-based approach sets this apart from other online courses. Would appreciate a few more practice exercises, but overall excellent.

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