🎓DSE – Sem 2 – Overview
Welcome to Semester 2 of the BITS M.Tech in Data Science & Engineering (DSE) program. How to choose DSE Electives for sem 2? This post is your all-in-one guide to understanding what to expect, how to plan, and how to navigate the semester with confidence. Whether you’re planning your electives or previous year papers or study notes —this guide has you covered.
Before start of the semester two of BITS WILP AIML there be a batch wide orientation session in which the students are introduced to various subjects and electives structure and how to choose each. Each subject will have a prescribed handout which lists the topics and syllabus for that course.
Refer here to choose electives (as per orientation)
- One course are mandatory (Core Courses) & the other two electives can be chosen by students based on elective groups
- It is not compulsory to choose a specialization, you can choose any electives and it wont have any impact on your degree/graduation. Even if you choose random electives it is fine. It is preferrable to choose based on your domain & interest.
- After the orientation they will send out a survey and based on the survey results they will decide which electives to keep and plan for faculty and sections (This is only for operational planning from BITS faculty to decide on courses faculty etc.). But final electives choosing will happen once the results for semester one are published
- During registration there will be details on class schedule, faculty etc. Sections & Electives once selected during registration cannot be changed.
Semester Structure at a Glance
- Duration: 2nd semester of the 2-year (4 semesters) M.Tech program
- Minimum Units Requirement: 16 units in Sem 2
Structure – DSE Core & DSE Electives
📚Core Courses (Mandatory)
Click on each of the below for more details
Introduction to Statistical Methods (DSECLZC418) – 4 Units
- Handout link – here
- Topics: Descriptive & Inferential Statistics, Probability Distributions, Hypothesis Testing, Regression, Time Series, Gaussian Mixture Models
- Tools: Excel, R, Python, SPSS, ML Libraries
- Evaluation: Assignments 30% + EC2 30% + EC3 40%
📚Elective Group – 1 (Choose One)
Click on each of the below for more details
Machine Learning (DSECLZG565)
- Note: Machine Learning is a prerequisite for Deep Learning in Sem 3.
- Handout link – here
- Topics: Regression, Classification, SVMs, Ensemble Models, Unsupervised Learning
- Exclusions: No deep learning, NLP, MLOps, or deployment
- Evaluation: Quizzes – 10% (Best 2 of 3), Assignment – 20%, Lab Modules – 5, Mid-Sem – 30%, Comprehensive – 40%
Applied Machine Learning (DSECLZG568)
- Handout link – here
- Topics: End-to-End ML Pipeline, Linear Models, SVMs, Ensemble Methods, Neural Networks, CNNs, RNNs, Fairness in ML
- Evaluation: Similar to ML course structure
📚Elective Group – 2 (Choose Any Two)
Click on each of the below for more details
Data Visualization and Interpretation (DSECLZG555)
- Handout link – here
- Tools: Tableau, Power BI, Plotly, Seaborn, Matplotlib, Superset, QuickSight
- Focus: Storytelling, Dashboards, Communication
- Evaluation: S – 5%, Assignments – 25%, 6 Lab Modules with recorded demos.
Artificial & Computational Intelligence (DSECLZG557)
- Handout link – here
- Topics: Search, Game Playing, Probabilistic Reasoning, Reinforcement Learning
- Exclusions: No deep learning or computer vision
- Evaluation: Quiz – 5%, Assignments – 25%, Lab Capsules – 6%.
Data Management for ML (DSECLZG529)
- Handout link – here
- Topics: Modern Data Stack, Data Pipelines, Storage, Processing, Metadata, Privacy
- Focus: Cloud-based tools & real-world data workflows
- Evaluation: Group Assignments, Lab Capsules, 30% Assignment Weight
DSE – Sem 2 – Important Academic Dates (2025)
- Lectures Start: 3 May 2025
- Mid-Sem Exams: 27-29 June 2025
- Comprehensive Exams: 5-7 September 2025
- Make-up Exams: 11-14 July (Mid-Sem EC2), 12-14 Sept (EC3)
- Last Lecture: 31 August 2025
Lecture days are usually Saturdays and Sundays. Buffer sessions are planned on select Fridays.
Evaluation & Schedule
- Tutorials/Webinars: 4 per course (90–120 mins), typically on Tue–Thu evenings (7 PM+)
- Note: No make-ups for quizzes/assignments
- Exam Slots: Fixed structure (e.g., 9–11 AM, 1–3 PM, etc.)
DSE Subject Wise Resources – DSE Electives & Core
📚DSECLZC418 – Introduction To Statistical Methods – DSE Core
Click on each of the below for more details
ISM Previous Year Papers
- 2023-04 – ISM EC3M Paper – here
- 2023-04 – ISM EC3R Paper – here
- 2023-01 – ISM EC2R Paper – here
- 2023-07 – ISM EC2R Paper – here
- 2023-01 – ISM EC2M Paper – here
- 2024-01 – ISM EC2R Paper – here
- 2024-02 – ISM EC2M Paper – here
ISM Practice Papers (Of AIML Course, Can be used for practice)
- 2024-07 – ISM EC2 (Mid Sem Exam Regular) Paper – here
- 2024-07 – ISM EC2 (Mid Sem Exam Makeup) Paper – here
- 2024-09 – ISM EC3 (Final Sem Exam Regular) Paper – here
- 2024-09 – ISM EC3 (Final Sem Exam Makeup) Paper – here
- 2024-09 – ISM EC3 (Final Sem Exam Makeup) Paper – here
- 2025-02 – ISM EC2 (Mid Sem Exam Regular) Paper – here
- 2025-02 – ISM EC2 (Mid Sem Exam Makeup) Paper – here
📚DSECLZG565- Machine Learning – DSE Electives
Click on each of the below for more details
ML Previous Year Papers (DSE)
- 2023-24 S1 – ML Mid-Sem Regular QP & Answer Keys – here
- 2023-24 S2 – ML Mid-Sem Make-up Answer Keys (Student Version) – here
- 2023-24 S2 – ML Mid-Sem Regular Answer Keys (Student Version) – here
- Sample QP – ML – here
ML Practice Papers (Of AIML Course, Can be used for practice)
📚DSECLZG568- Applied Machine Learning – DSE Electives
Click on each of the below for more details
Applied ML Previous Year Papers (DSE)
- 2023-24 S1 – AML Mid-Sem Regular QP & Answer Keys – here
- 2023-24 S1 – AML End-Sem Regular QP & Answer Keys – here
📚DSECLZG555- Data Visualization & Interpretation
Click on each of the below for more details
📚DSECLZG557- Artificial & Computational Intelligence
Click on each of the below for more details
ACI Sample Papers (Of AIML Course, Can be used for practice)
📚DSECLZG529- Data Management For ML
Click on each of the below for more details
DMML Previous Year Papers (DSE)
💡Final Thoughts
Semester 2 is where the DSE journey starts to pick up real pace. Choose electives wisely, stay organized, and don’t underestimate the assignments—they’re crucial for hands-on learning.
If this DSE knowledge base helped you, consider sharing it with your peers! For more semester-wise breakdowns, tips, and student resources, stay tuned to crackbitswilp.in Save this knowledge base for future reference, This is actively maintained throughout the semester. Happy Learning