IITM BS Introduction to Big Data (BSDA5001): Syllabus and Tips

Introduction to Big Data (BSDA5001) is a 4 credit elective at the degree level of the IITM BS in Data Science. The handbook places it at level 5. It has no prerequisite. The course is about running data work at large scale: cloud basics first, then tools like Spark and Kafka on Google Cloud.

The course is taught by Rangarajan Vasudevan, Co-Founder and Chief Data Officer of Lentra.ai. The course page and the handbook agree on the credits and on having no prerequisite.

What you learn in Introduction to Big Data

The course has 11 weeks of coursework. They fall into four blocks.

• Weeks 1 to 3: cloud foundations. Big data ideas and setting up Google Cloud. Then cloud-native design, serverless computing, message queues and the IaaS, PaaS and SaaS models. Then data formats and sources, storage choices on the cloud and a first serverless task with Google Cloud Functions.
• Weeks 4 to 6: processing data at scale. Hadoop and PySpark. Then ETL and ELT, the difference between them and why a scheduler matters. Then SQL on big data through Spark SQL, and the main types of NoSQL stores.
• Weeks 7 and 8: streaming. How streaming systems work, with Google Pub/Sub and Dataflow as examples. Then Kafka as another message queue, and Spark Streaming.
• Weeks 9 to 11: machine learning on big data. Batch machine learning with Spark ML on Dataproc, then deep learning with big data on the cloud. Week 11 is set aside to prepare for a final project and clear doubts.

How the course is assessed

The course page lists weekly online assignments, 2 in-person invigilated quizzes and 1 in-person invigilated end term exam. Week 11 talks of a final project, but the assessment line does not list one. Ask the course team how the project is graded. For how quizzes work in general, see IITM BS Quiz 1 and Quiz 2.

Where it counts

• Minor in Cloud Computing for AI. It is one of three courses, with Deep Learning Practice (BSDA5013) and MLOps (BSDA5014). See the Cloud Computing for AI minor.
• BS level stream rule. It is a level 5 course tagged BD/BP. The handbook does not say which stream a BD/BP course counts for, so ask support before you count it toward the 2 programming or 2 data science stream courses. See the BS degree level.
• Terms. The DS course table (updated 18 March 2026) marks it only for September 2026, not May 2026 or January 2027. If you want this minor, plan around that.

The handbook says level 5 courses are more complex than level 3 and level 4 courses, but carry the same credits and fee as level 4.

Who finds it hard and how to prepare

The syllabus is more about tools than maths. The hard part is the number of tools and the setup work. Students who have never used a cloud console or a terminal spend the first weeks fighting setup instead of learning.

• Revise SQL before the term. Spark SQL builds on it. Database Management Systems (BSCS2001) covers what you need.
• Get comfortable with basic Linux commands. Many cloud tools are driven from a terminal.
• On any cloud account, set a budget alert and shut down clusters after each session. A forgotten cluster can keep running for days.
• For each new tool, write down in two lines what problem it solves. Kafka, Pub/Sub and Dataflow are easy to mix up otherwise.
• Keep your PySpark notebooks tidy and reusable. The later ML weeks build on the same patterns.

What to take before and after

No course is required first, though DBMS helps with the SQL weeks. For the Cloud Computing for AI minor, pair it with MLOps (BSDA5014), which also has no prerequisite in the table, and Deep Learning Practice, which needs Deep Learning (BSCS3004) first.

Common questions

Do I need to pay for Google Cloud to do this course?

The course page does not say. Week 1 includes setting up the Google Cloud platform, so ask the course team in week 1 whether credits are provided.

Is Big Data the same as Big Data and Biological Networks?

No. Big Data and Biological Networks is a different course with the code BSBT4002. This one, BSDA5001, is about cloud and large scale data tools.

Can I take it before the BS level?

Yes, it can go in the BSc level. The handbook's fee table notes that BP and BD courses can be done at the BSc level too, and this one is tagged BD/BP with no prerequisite. Confirm the rules for your term before you register.