FDPS & Workshops

S. No.

Title of the Program

Duration/ Date

Who should attend?

Content

Poster

Apply button / Last date

8

5 Days Online Bootcamp on Deep Learning Technologies

13th May 2024 to 17th May 2024

Theory: Perceptron model, Activation function, Loss Function, Building Neural Networks, Cross Entropy loss, loss optimization, Gradient decent, Learning rate, Overfitting, Dropouts. Features Extraction, Feature Representation, Fully Connected Neural Network, CNN, pooling, stride, padding, Transfer Learning and Fine-tuning.

Hands-on Session: Basic Python Programming, Intro to Training resources, Import packages and loading of datasets, Creating CNN models from scratch, Compiling of models, Training and Testing of Models, Training with pertained models.

7

1 day Workshop on DEPLOYMENT of AI MODELS on Edge Devices

15th May 2024

Hands-on Training to configure edge devices (Like Raspberry Pi/Jetson Nano) and deploy AI models for real-world AI applications.

For Students who has experience to train Deep Learning models - Learn to deploy it in edge devices.

6

5 Days Workshop / FDP Artificial Intelligence for Management & Business Analytics

5 Days from 3rd June 2024 to 7th June 2024

Theory: Machine Learning, Supervised Learning, Perceptron model, Building Neural Networks, Cross Entropy loss, loss optimization, Gradient decent, Learning rate, Overfitting, Dropouts, CNN, Case study of use of Business analytics, Machine learning for Business analytics, Case study of use of Deep Learning based AI models for Business analytics

Hands-on Session: Basic Python Programming, Intro to Training resources, Introduction to packages and loading of datasets, Creating CNN models from scratch for Business analytics, Compiling of models, Training and Testing of Models, Training with pertained models for business analytics.

5

5 Days Workshop / FDP Artificial Intelligence in Life Science, Healthcare & Biotechnology

5 Days from 3rd June 2024 to 7th June 2024

Theory: Machine Learning, Supervised Learning, Perceptron model, Activation function, Loss Function, Building Neural Networks, Cross Entropy loss, loss optimization, Gradient decent, Learning rate, Overfitting, Dropouts, CNN, Case study of use of Machine learning for Biological / Clinical Applications, Case study of use of Deep Learning based CNN models for Biological / Clinical Applications. 

Hands-on Session: Basic Python Programming, Intro to Training resources, Introduction to packages and loading of datasets, Creating CNN models from scratch for Biological Application, Compiling of models, Training and Testing of Models, Training with pertained models for Biological / Medical Applications. 

4

5 Days FDP/ Workshop on Machine Learning & Deep Learning

5 Days from 3rd June 2024 to 7th June 2024

Theory: Perceptron model, Activation function, Loss Function, Building Neural Networks, Cross Entropy loss, loss optimization, Gradient decent, Learning rate, Overfitting, Dropouts. Features Extraction, Feature Representation, Fully Connected Neural Network, CNN, pooling, stride, padding, Transfer Learning and Fine-tuning.

Hands-on Session: Basic Python Programming, Intro to Training resources, Import packages and loading of datasets, Creating CNN models from scratch, Compiling of models, Training and Testing of Models, Training with pertained models.

3

4 weeks Summer Internship/ Summer training on Artificial Intelligence

From 10th June 2024 (Dates are Flexible)

Theory: Perceptron model, Activation function, Loss Function, Building Neural Networks, Cross Entropy loss, loss optimization, Gradient decent, Learning rate, Over fitting, Dropouts. Features Extraction, Feature Representation, Fully Connected Neural Network, CNN, pooling, stride, padding, Transfer Learning and Fine-tuning.Recurrent Neural Networks (RNNs), Sequential models for solving Long-term dependency issues. LSTM models, Introduction to Autoencoders and Variational Autoencoders, Generative Adversarial Networks (GANs), Applications of GANs.

Hands-on Session: Basic Python Programming, Intro to Training resources, Import packages and loading of datasets, Creating ANN & CNN models from scratch, Compiling of models, Training and Testing, Plotting of curves, feature extraction, Models training with some pertained models, Image Augmentation, Implementation of RNN, GAN architecture implementation.

2 weeks research project to build a Deep Neural Network for solving a problem. 

2

2 weeks Certificate Program in Artificial Intelligence

2 weeks 17th June 2024 to 28th June 2024

Theory: Perceptron model, Activation function, Loss Function, Building Neural Networks, Cross Entropy loss, loss optimization, Gradient decent, Learning rate, Over fitting, Dropouts. Features Extraction, Feature Representation, Fully Connected Neural Network, CNN, pooling, stride, padding, Transfer Learning and Fine-tuning.

Recurrent Neural Networks (RNNs), Sequential models for solving Long-term dependency issues. LSTM models, Introduction to Autoencoders and Variational Autoencoders, Generative Adversarial Networks (GANs), Applications of GANs.

Hands-on Session: Basic Python Programming, Intro to Training resources, Import packages and loading of datasets, Creating ANN & CNN models from scratch, Compiling of models, Training and Testing, Plotting of curves, feature extraction, Models training with some pertained models, Image Augmentation, Implementation of RNN, GAN architecture implementation. 

1

5 days Bootcamp on Deep Learning Technologies

5 days 17th June to 21st June 2024

Theory: Perceptron model, Activation function, Loss Function, Building Neural Networks, Cross Entropy loss, loss optimization, Gradient decent, Learning rate, Overfitting, Dropouts. Features Extraction, Feature Representation, Fully Connected Neural Network, CNN, pooling, stride, padding, Transfer Learning and Fine-tuning.

Hands-on Session: Basic Python Programming, Intro to Training resources, Import packages and loading of datasets, Creating CNN models from scratch, Compiling of models, Training and Testing of Models, Training with pertained models.