Academics help us to acquire knowledge and to put it to test in the real world!
Skills Together:
Programming Languages: Python, C++, Java
Packages/frameworks, Skills for ML-AI: Computer Vision, Machine learning, Deep Learning, Pytorch, Tensorflow,
Natural Language Processing (NLP), Time Series Forecasting, MySQL, Data Analytics, MLOPS, AWS
Master of Science
Arizona State University, Robotics and Autonomous Systems
Aug 2023 - May 2025
Current GPA: 3.89 / 4.00
Courses
Applied Linear Algebra: Operations of Matrices, Mappings, Subspaces, Matrix Factorizations and Decompositions, Eigen Vectors and ValuesMechatronic Systems: Design processes, Measurements and Controls, Sensors and Transducers, Signal Conditioning, Digital Signals and Logic, Pneumatic/ Hydraulic & Actuating Systems, Micro-controllers, Communication, System Integration
Robotic Systems 1: Vector Analysis, Forward and Inverse Kinematics, MATLAB, Simulink, Homogeneous Matrix Transformations, Motion Control, Hand-on on Cobot, D-H Parameters, Quaternions, Trajectory Planning
Post-Graduate Diploma
International Institute of Information Technology (Bangalore, India), Machine Learning and Artificial Intelligence
Feb 2021 - Mar 2022
GPA: 3.28 / 4.00
Courses
Statistics Essentials: Exploratory Data Analysis, Inferential Statistics, Hypothesis TestingMachine Learning: Linear Regression, Logistic Regression, Naive Bayes, Advanced Regression (Regularizations, L1 and L2 penalties), Support Vector Machines, Tree Models (Decision Trees and Ensemble Models), Boosting Models, Unsupervised Learning(Clustering and Principal Component Analysis), Model Selection, Bias and Variance Tradeoff
Deep Learning and Neural Networks: Convolution Neural Networks, Recurrent Neural Networks(Vanilla, LSTM,GRUs,etc), Attention Models, Transformer Models
Natural Language Processing: Lexical/Semantic/Syntactic Processing, Word-embeddings, Knowledge Graphs Reinforcement Learning: Classical RL(Markov Decision Process, Model Based and Model Free methods), Deep RL (Q-Learning)
Model Deployments: Model API creation(Flask), Model Packaging(Docker), Model Deployment(Heroku/AWS)