- Foundations of Data Science
- Linear Algebra
- Optimization
- Statistics
- Probability
- Machine Learning: Foundations and Algorithms
- Supervised Learning
- Unsupervised Learning
- Machine Learning: Real-world use-cases in sectors and associated challenges
- Real world use case: Covering the entire ML pipeline for specific focus areas
- Deep Learning: Foundations and Algorithms
- ANN
- FNN
- Backpropagation
- SGD
- ADAM
- CNN
- GAN
- Deep Learning: Real-world use-cases in sectors and associated challenges
- Real world use-cases in specific areas and associated challenges.
- Sequential Learning
- Intro to Online Learning
- MAB
- RL
- Some of the Capstone Projects
- Attention Mechanisms in Deep Neural Networks
- Safety and Stability Preserving Reinforcement
- Cancer Genomics
- Biological Network Analytics
- Domain Agnostic Methods
- Smart Mobility
- Traffic Modelling and Analysis
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