How Data Science and Artificial Intelligence intersect across the 4-year undergraduate engineering trajectory.
Covers data ingestion, noisy pipeline cleaning, distributed SQL/NoSQL storage (Hadoop, Spark), statistical variance testing, and business intelligence dashboards. Data Science fuels the feature store required for AI training.
Focuses on mathematical optimization, backpropagation, convolutional and recurrent networks, transformer architectures, reinforcement learning agents, and model quantization for edge deployment.
Unlike standard IT degrees, 22-25% of coursework is dedicated to Multivariable Calculus, Probability Density, Linear Algebra, and Discrete Math to ensure deep understanding of gradient optimization mechanics.
Formatted 4-Year B.Tech in AI & Data Science Degree Schedule ready for academic credit verification or portfolio planning.
In the degree pathway map, every course node sits on a directed prerequisite lineage across eight engineering semesters. Clicking an active course highlights its required prerequisites in green and illuminates all downstream dependent subjects in violet. Toggling a lab credit updates the inspector, recomputes practical hours, and immediately balances overall degree telemetry toward the 160-credit benchmark.