| Day (Date) | 10:00 - 13:00 | 15:00 - 18:00 |
|---|---|---|
| Monday (26.06.2023) | Registration | Inauguration ceremony |
| Tuesday (27.06.2023) | Fundamental of Neural Network (NN) | Hands-On for Python Programming (Introduction, Expression Variable) |
| Wednesday (28.06.2023) | Fundamental of Deep learning | Hands-On for Python Programming (Functions, Conditions, Iterations) |
| Thursday (29.06.2023) | Fundamental of Convolution NN | Hands-On for Python Programming (Strings, Tuples, Lists) |
| Friday (30.06.2023) | Fundamental of Recurrent NN | Hands-On for Python Programming (Dictionaries, Sets, Text Files) |
| Saturday (01.07.2023) | Speech Processing | Hands-On for Python Programming (Binary Files, Math Functionas, Graphs) |
| Day (Date) | 10:00 - 13:00 | 15:00 - 18:00 |
|---|---|---|
| Monday (03.07.2023) | Data Preprocessing techniques (feature scaling, handling missing values, encoding categorical data, etc.) | Hands-On based on Morning Lecture |
| Tuesday (04.07.2023) | Regression (Simple linear regression, multiple linear regression, polynomial regression, Support vector regression, Decision tree regression, Random forest regression) | Hands-On based on Morning Lecture |
| Wednesday (05.07.2023) | Classification (K nearest neighbour, logistic regression, Naïve Bayes) | Hands-On based on Morning Lecture |
| Thursday (06.07.2023) | Classification (Support Vector Machine, Kernel SVM, Decision Trees, Random Forest, XGBoost) | Hands-On based on Morning Lecture |
| Friday (07.07.2023) | Dimensionality Reduction (Principal Component Analysis, Linear Discriminant Analysis, Kernel PCA) | Hands-On based on Morning Lecture |
| Saturday (08.07.2023) | Clustering (K-Means clustering, Hierarchical clustering) | Hands-On based on Morning Lecture |
| Day (Date) | 10:00 - 13:00 | 15:00 - 18:00 |
|---|---|---|
| Monday (10.07.2023) | Basics of Markov Decision processes, Application of MDP to real world problems Problem formulation, Dynamic programming algorithm (Value iteration algorithm), Greedy algorithm | Hands on: Simulation of dynamic programming algorithm in python, Implementation of DP algorithm for real world application |
| Tuesday (11.07.2023) | Markov decision processes, Policy Evaluation, Policy Improvement, Policy iteration algorithm, Epsilon greedy algorithm | Hands on: Implementation of policy evaluation algorithm in python, Implementation of policy iteration algorithm in python, Implementation of epsilon greedy algorithm |
| Wednesday (12.07.2023) | Reinforcement learning ideas, Q-learning algorithm and its application to real world problems, SARSA algorithm | Hands on: Implementation of q learning algorithm, Implementation of SARSA algorithm |
| Thursday (13.07.2023) | Deep Q-learning network (DQN) algorithm and its application to real world problems | Hands on: Implementation of DQN algorithm |
| Friday (14.07.2023) | Reinforcement learning algorithm: Policy gradient algorithm, Application to real world problems | Hands on: Implementation of policy gradient algorithm |
| Saturday (15.07.2023) | Advanced reinforcement learning algorithm: Proximal policy optimization algorithm, Multi-armed bandit problems: UCB and Thompson sampling algorithms, Future directions of RL | Hands on: Implementation of proximal policy algorithm, UCB algorithm and Thompson sampling algorithm in python |
| Day (Date) | 10:00 - 13:00 | 15:00 - 18:00 |
|---|---|---|
| Monday (17.07.2023) |
Introduction to Robotics: Localization, Mapping, SLAM, Control | Lab Visit/Playing with CoppeliaSim (or) SLAM Libraries |
| Tuesday (18.07.2023) | Configuration Space and Deliberative Planning Algorithms | Introduction to ROS |
| Wednesday (19.07.2023) | Reactive Planning Algorithms | Playing with TurtleSim, Gazebo |
| Thursday (20.07.2023) | Hybrid Planning Algorithms, Behavioral Programming of Robots | ROS Navigation Stack, Programming Multiple Robots |
| Friday (21.07.2023) |
A peek into Multi-Robot Motion Planning, Swarms, Evolutionary Robotics | ARGOS (or) Programming PRM |
| Saturday (22.07.2023) | Imitation Learning, Reinforcement Learning, Inverse Reinforcement Learning for Robot Motion | OMPL and MoveIt |