B.Tech. Coursework

MA101 - Mathematics I (10/10)
Taneja, H. C. Advanced engineering mathematics. IK International Pvt Ltd, 2010.

MA102 - Mathematics II (10/10)
Taneja, H. C. Advanced engineering mathematics. IK International Pvt Ltd, 2010.

MC201 - Discrete Mathematics (10/10)
Rosen, Kenneth H., and Kamala Krithivasan. Discrete mathematics and its applications. Vol. 6. New York: McGraw-Hill, 1999.

MC202 - Real Analysis (09/10)
Malik, Subhash Chandra, and Savita Arora. Mathematical analysis. New Age International, 1992.

MC203 - Mathematics III (10/10)
Taneja, H. C. Advanced engineering mathematics. IK International Pvt Ltd, 2010.

MC204 - Scientific Computing (Numerical Methods) (10/10)
Jain, Mahinder Kumar, Satteluri RK Iyengar, and Rajinder Kumar Jain. Numerical methods: problems and solutions. New Age International, 2007.

MC205 - Probability and Statistics (09/10)

MC207 - Engineering Analysis and Design (Differential Equations) (10/10)

MC208 - Linear Algebra (10/10)
Lipschutz, Seymour. Linear Algebra 4th ed. McGraw-Hill, 2009.

MC303 - Stochastic Processes (10/10)
Taneja, H. C. Statistical methods for engineering and sciences. IK International Pvt Ltd, 2013.

MC305 - Operation Research (10/10)
Taha, Hamdy A. Operations research: an introduction. Pearson Education India, 2013.

MC306 - Financial Engineering (10/10)
Chandra, S., and S. Dharmraja, Mehra Aparna and Khemch-andani R "Financial Mathematics an Introduction" Narosa publishing house pvt Ltd (2013).

MC315 - Modern Algebra (10/10)
Gallian, Joseph. Contemporary abstract algebra. Chapman and Hall/CRC, 2021.

MC317 - Numerical Methods for ODE (10/10)
LeVeque, Randall J. Finite difference methods for ordinary and partial differential equations: steady-state and time-dependent problems. Society for Industrial and Applied Mathematics, 2007.

MC407 - Cryptography and Network Security (10/10)
Mukhopadhyay, Debdeep, and B. A. Forouzan. "Cryptography and network security." Noida: Tata Mcgraw Hill (2011).
Stallings, William. Cryptography and network security, 4/E. Pearson Education India, 2006.

MC418 - Optimization Techniques (10/10)
Chandra, Suresh, Jayadeva, and Aparna Mehra. Numerical optimization with applications. Alpha Science International, 2009.

MC419 - Machine Learning (10/10)
Deisenroth, Marc Peter, A. Aldo Faisal, and Cheng Soon Ong. Mathematics for machine learning. Cambridge University Press, 2020.
Kim, Phil. "Matlab deep learning." With machine learning, neural networks and artificial intelligence 130, no. 21 (2017). 

CO102 - Programming Fundamentals (10/10)
Kanetkar, Yashavant. Let us C. BPB publications, 2018.

CS251 - Data Structures (10/10)

CS262 - Algorithm Design and Analysis (10/10)
Cormen, Thomas H., Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. Introduction to algorithms. MIT press, 2022.

MC206 - Computer Organization and Architecture (10/10)
Mano, M. Morris. Computer system architecture. Prentice-Hall, Inc., 1993.

MC301 - Operating Systems (10/10)
Silberschatz, Abraham, Peter B. Galvin, and Greg Gagne. Operating System Concepts, Windows XP update. John Wiley & Sons, 2006.

MC302 - Database Management Systems (10/10)
Elmasri, Ramez, and Shamkant B. Navathe. "Fundamentals of Database Systems 7th ed." (2016).

MC304 - Theory of Computation (10/10)
Mishra, K. L. P., and N. Chandrasekaran. Theory of computer science: automata, languages and computation. PHI Learning Pvt. Ltd., 2006.

MC307 - Object Oriented Programming (09/10)
Balagurusamy, Entrepreneurial. "Object oriented programming with C++." (2021).
Deitel, Paul, and Harvey Deitel. C how to program: with case studies in applications and systems programming. No. PUBDB-2022-03757. Pearson Education Limited, 2022.
Sierra, Kathy, and Bert Bates. Head First Java: A Brain-Friendly Guide. " O'Reilly Media, Inc.", 2005.

MC312 - Artificial Intelligence (10/10)
Khemani, Deepak. A first course in artificial intelligence. McGraw Hill Education (India), 2013.

MC405 - Graph Theory (10/10)
Deo, Narsingh. Graph theory with applications to engineering and computer science. Courier Dover Publications, 2017.

Python Fundamentals Track (DataCamp)  [Link]

AI for Scientific Research Specialization (LearnQuest, Coursera)  [Link]

Infectious Disease Modelling Specialization (Imperial College London, Coursera)  [Link]

Machine Learning Specialization (Stanford University & Deeplearning.ai, Coursera)  [Link]

CS107: C++ Programming (Saylor.org Academy)  [Link]