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Courses Taught at TIET
● PAI104 Advanced Deep Learning (ODD Semester 2025-26)
(M.E. First Year)
● UCS761 Deep Learning (ODD Semester 2025-26)
(B.E. Final Year)
● PCS109 Advanced Algorithms (EVEN Semester 2024-2025)
(M.E. First Year, MECS1-4)
● PCS109 Advanced Algorithms Lab (EVEN Semester 2024-2025)
(M.E. First Year, MECS2, MECS4)
● UCS761 Deep Learning (ODD Semester 2024-25)
(B.E. Final Year, 4CO15-28)
● UCS761 Deep Learning Lab (ODD Semester 2024-25)
(B.E. Final Year, 4CS5-8, 4CO22-24, 4CO14-15, 4CO4-7)
● UCS301 Data Structures Lab (ODD Semester 2024-25)
(B.E. Second Year, 2CO10, 2CO22)
● UCT501: DESIGN AND ANALYSIS OF ALGORITHMS
(Summer Semester 2024, Self Study Mode)
● UCS856: COMPUTER VISION AND AUGMENTED REALITY
(Summer Semester 2024, Self Study Mode)
● UCS415: Design and Analysis of Algorithms (Even Semester 2023-24)
B.E. COE/CSE (2nd Year, 4th Semester)
● UCS415: Design and Analysis of Algorithms Lab (Even Semester 2023-24)
B.E. COE/CSE (2nd Year, 2CO5, 2CO17, 2CO19, 2CO20, 2UoQ/2TCD)
Courses Taught at Amrita Vishwa Vidyapeetham
● 19CSE456: Neural Networks and Deep Learning (Odd Semester 2023-2024)
(V SEM-B Tech CSE-PE1)
● 21CS644/21AI604 Machine Learning (Odd Semester 2023-2024)
(I SEM -MTech CSE/AI (SoftCore1/Core))
● 19CSE205: Program Reasoning Lab
(III SEM-BTech CSE A)
Jointly with Dr. Padmavathi S
● 21AI639: Computer Vision (Even Semester 2022-2023)
(M.Tech CSE/AI - II Sem)
● 19CSE212: Data Structures and Algorithms (Even Semester 2022-2023)
(B.Tech - CSE IV Sem - Sec A), Batch 2021-2025
● 19CSE212: Data Structures and Algorithms Lab (Even Semester 2022-2023)
(B.Tech - CSE IV Sem - Sec A)
Jointly with Ms. R. R. Sathiya and Ms. Anisha Radhakrishnan
● 19CSE302: Design and Analysis of Algorithms (Odd Semester 2022-2023)
(V Sem. B.Tech. CSE)
Guest Lectures, Jointly with Dr. T. Gireesh Kumar
● 19CSE435: Computer Vision (Odd Semester 2022-2023)
(PE V - VII Sem. B.Tech. CSE)
Guest Lecture, Nov 18th 2022
Courses Taught at IIT Madras
All the teachers and courses at IIT Madras are evaluated by the students who attend the course, referred to as the Teacher Course Feedback (TCF)
Online Courses/Certification Completed
Online Courses/Certification Completed
Artificial Intelligence & Data Science Courses
● AI for Everyone [by Andrew Ng, DeepLearning.AI/Coursera]
● Python for Data Science, AI & Development [by Joseph Santarcangelo, Authorized by IBM]
● Fundamentals of Deep Learning [by Nvidia]
● Introduction to Data Engineering [by IBM]
● Exploratory Data Analysis for Machine Learning [by IBM Machine Learning]
● Introduction to Artificial Intelligence (AI) [by IBM]
● Introduction to Large Language Models [By Google Cloud]
● Generative AI Explained [By NVDIA DLI]
● Augment your LLM Using Retrieval Augmented Generation [By NVDIA DLI]
● Industrial Applications for AI [By L&T EduTech]
● Innovative Teaching with ChatGPT [Generative AI and ChatGPT for K-12 Educators]
● An Even Easier Introduction to CUDA [By NVIDIA DLI]
● Generative AI Content Creation [By Adobe]
● Large Language Models with Semantic Search [By DeepLearning.AI]
● Foundations of Local Large Language Models [By Duke University]
● Large Language Models [By H20.ai]
● Developing Explainable AI (XAI) [By Duke University]
● Generative AI: Introduction and Applications [By IBM]
● Generative AI and LLMs: Architecture and Data Preparation [By IBM]
● Machine Learning with Python [By IBM]
● Introduction to Deep Learning & Neural Networks with Keras [By IBM]
● Building Generative AI-Powered Applications with Python [By IBM]
● Generative AI: Prompt Engineering Basics [By IBM]
● Fundamentals of AI Agents Using RAG and LangChain [By IBM]
● Generative AI Advance Fine-Tuning for LLMs [By IBM]
● Generative AI Engineering and Fine-Tuning Transformers [By IBM]
● Generative AI Language Modeling with Transformers [By IBM]
● Gen AI Foundational Models for NLP & Language Understanding [By IBM]
● Generative Pre-trained Transformers (GPT) [By University of Glasgow]
● How to Build a Diffusion Model - An Introduction [By Fractal]
● Attention Mechanisms and Transformer Models Course [By Simplilearn]
● Introduction to Data Analytics [By IBM]
● How Transformer LLMs Work [By DeepLearning.AI]
● Prompt Engineering for Vision Models [By DeepLearning.AI]
● Large Language Models with Semantic Search [By DeepLearning.AI]
● How Diffusion Models Work [By DeepLearning.AI]
● Introduction Course to Autoencoders, VAEs, and GANs [By simpliLearn]
● Agentic AI and AI Agents: A Primer for Leaders [By Vanderbilt University]
Vision & Imaging Courses
● Computer Vision for Embedded Machine Learning [by Edge Impluse]
Cybersecurity Courses
● Introduction to Blockchain Technologies [by INSEAD]
Programming Courses
● Crash Course on Python [by Google]
Computing Courses
● Introduction to Cloud Computing [By IBM]
● Quantum Computing for Everyone - An Introduction [By Fractal Analytics]
● Python Programming for Quantum Computing [By Packt]
● Hands-on quantum error correction with Google Quantum AI [Google Quantum AI]
Mathematics Courses
● Linear Algebra from Elementary to Advanced Specialization [By Johns Hopkins University]
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