Guided over 250+ students from diverse backgrounds in a Deep Learning course. Responsibilities included setting complex term paper problems challenging beyond textbook knowledge, solving doubts, and designing practical problem sets. Developed comprehensive notebooks demonstrating deep learning concepts like text processing, sentence tagging, and transfer learning.
Organized a Kaggle competition focused on image restoration, guiding students through approaches such as diffusion models and GANs. Assessed 200+ reports, using a scoring system that balanced innovation, performance, and effort to measure deeper understanding.
Served as a Teaching Assistant, mentoring over 150+ students in C/C++ programming and foundational Data Structures and Algorithms. Responsibilities included crafting lab problems, evaluating solutions, and providing detailed feedback with a focus on edge cases. Played a key role in guiding students to ideate and approach problem-solving more efficiently.
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