Semester 5 — ML

SRM Machine Learning syllabus units, course code and exam plan for Semester 5.

Machine Learning (ML) is a Semester 5 subject under the SRMIST 2021 regulation. The checklist below lists its units; the exam pattern and a unit-by-unit preparation plan follow.

Machine Learning syllabus unit checklist

Course code 21CSC305P · 3 credits · Semester 5. The 5 unit titles below are from the SRMIST 2021 regulation syllabus (official curriculum); tick each one as you revise it.

ML in the Semester 5 subject map

Machine Learning is listed for Semester 5 under the SRMIST 2021 regulation. These are the pages around it: the semester hub first, then the other subjects listed for the same semester.

Machine Learning study resources

Exam pattern

What the SEM, CT and model papers are for ML, how long each runs, and where the marks sit across Part A, Part B and Part C.

Revision plan

How to fit the 5 units above into a one-night or multi-day plan, and what to do in each block.

Using your papers

This site does not host question papers. Collect the ML papers you have and use the unit-topic matrix method to see what repeats.

Tools

GPA and attendance calculators plus browser study tools, so planning and revision do not need a separate app.

How to prepare ML for SRM semester exams

1

Check the syllabus

Open the syllabus guide and confirm the ML unit topics. Only study what is listed for the 2021 regulation.

2

Collect your ML papers

Gather the ML SEM papers you already have and build a unit-topic matrix: one row per unit, one column per year. Anything that appears twice is worth learning properly.

3

Revise unit by unit

Work the units in the order above and answer the questions your matrix flagged. The exam strategy guide covers how Part B and Part C answers are marked.

4

Attempt a full paper under time

Pick a SEM paper you have and attempt it in the three hours with no notes. Note what cost you time, then revise those units again.