This knowledge base has all essential resources for Semester 1 of the BITS WILP AIML program — including previous years’ question papers, PDF and printed notes, key topics, exam-focused questions, exam tips and more.
Overview
AIML Semester 1 will ideally have four subjects (listed below); Each subject will have a prescribed handout which lists the topics and syllabus for that course. Each course will have quizzes, assignments, (EC1) mid-semester exam (EC2), final-semester exam (EC3).
Exam results are usually displayed on the mettle portal and you can download the PDF of your results for your reference. Example report of ISM EC3(Final Exam) can be found here
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1. Mathematics For Machine Learning (MML/MMFL)
MFML is one of the toughest subjects in AIML semester one. Since it involves understanding of the concepts thoroughly, this is not a subject you can just a day before exam and still score good marks. But, this subject can be easily conquered if concepts are understood well.
- Previous Year Handout Link
- Recommended Books:
- Linear Algebra and Optimization for ML by Charu C. Aggarwal –
Buy on Flipkart - Linear Algebra and Optimization for ML by Charu C. Aggarwal – Buy from crackbitswilp – Discounted
- Linear Algebra and Optimization for ML by Charu C. Aggarwal –
- MFML exercise solutions
- Topic wise study guide for Math for ML (Detailed)
- MFML Topic Wise Notes (Free)
- Linear Algebra: Matrices, Vectors, Determinants, Linear Systems: here
- Eigen Values & Eigen Vectors: here
- 🚀 Access all notes & premium study materials → Enroll Now
- Matrix Operations – Scalar Multiplication, Row Exchange : here
- Sign Up for more free resources: – here
MFML Topic Wise Notes (Premium)
- 🚀 Below links accessible for premium users only → Enroll Now
- More coming soon …
2. Introduction To Statistical Management (ISM)
- Previous Year Handout Link
- Printed Text Books
- Recommended Books:
- Statistics for Data Scientists by Maurits Kaptein – Buy from crackbitswilp – Discounted
- Statistics for Data Scientists by Maurits Kaptein –
Buy on Amazon
- Topic wise study guide for ISM (Free Version)
- Topic wise study guide for ISM (Detailed Paid Version)
3. Deep Neural Networks (DNN)
- Deep Neural Networks Handout – here
- Concepts: Fundamental concepts of deep learning concepts & deep neural networks, Artificial neural networks, evaluation & optimization of deep learning models
- Exams will have a mix of numerical, justifications, reasoning questions
- Topic wise study guide for DNN (Detailed Paid Version)
- DNN Topic Wise Notes(Free)
- All important activation functions in neural networks: here
- 🚀 Access all notes & premium study materials → Enroll Now
- Sign Up for more free resources: – here
4. Machine Learning (ML)
- Previous Year Handout Link
- Printed Text Books
- ML Cheat Sheet (Last Minute Revision)
- Topic wise study guide for ML (Free Version)
- Topic wise study guide for ML (Detailed Paid Version)
BITS WILP AIML SEM 1 – Previous Year Question Papers
MFML Previous Year Papers
- 2024-09 – MFML EC3 (Final Exam Regular) Paper – here
- 2024-09 – MFML EC3 (Final Exam Makeup) Paper – here
- 2024-09 – MFML EC2 (Mid Sem Regular) Paper – here
- 2025-01 – MFML EC2 (Mid Sem Regular) Paper – here
- For more previous year question papers & other resources – Enroll Here
ISM Previous Year Papers
- 2024-07 – ISM EC2 (Mid Sem Exam Regular) Paper – here
- 2024-07 – ISM EC2 (Mid Sem Exam Makeup) Paper – here
- For more previous year question papers & other resources – Enroll Here
Deep Learning Previous Year Papers
- DNN_Cluster_S1_23_EndSem_Makeup – Download PDF
- DNN_Cluster_S1_23_EndSem_Regular – Download PDF
- DNN_Cluster_S1_23_MidSem_Makeup – Download PDF
- DNN_Cluster_S1_23_MidSem_Regular – Download PDF
- For more previous year solved question papers & other resources – Enroll Here
ML Previous Year Papers
- 2024-07 – ML EC2 (Mid Sem Exam Regular) Paper – here
- 2024-09 – ML EC3 (Final Sem Exam Regular) Paper – here
- For more previous year question papers & other resources – Enroll Here
Frequently Asked Questions (FAQ)
– Will they allow Textbooks in exams
Textbooks are allowed in Final sem exam (EC3) for AIML course.
– What is the passing criteria
It will totally depend on the toughness of the paper and performance of your class.
Explore topics & themes in Semester Two!