14th IACC-Individual Workshop

Registration Fees	Registration Fees for IACC Member
1000 INR	500 INR
Note: Non Refundable (Every participant will get certificate).

Cloud Computing :

Workshop Target:

Each module will have demos, case studies & practical implementations so that participants get the better understanding of the concepts.
Our target goal will be to provide them enough information on the AWS services so that they can prepare themselves & gain certifications for AWS Cloud certified Practitioner and Solution Architect exams.

Research Topics:

Research topics in cloud computing such as cloud resource provisioning, task scheduling, Green Cloud Computing, Edge and Fog computing will also be covered during the workshop.

Workshop Schedule:

Day 1
Introduction - Cloud Computing and Virtualization, Datacentre Cloud Service & Deployment Models, Mapping - Enterprise DC & AWS	Compute - EC2 (Elastic Compute Cloud) Storage - EBS (Elastic Block Store)
Network - VPC (Virtual Private Cloud) Network - ELB (Elastic Load Balancer)	Compute - Auto Scaling Network - Route53
Day 2
Storage - S3 (Simple Storage Service) Storage - EFS (Elastic File Store)	Security & Identity - IAM (Identity and Access Management) Command Line Interface
Database -RDS & DynamoDB Notification - Simple Notification Service (SNS)	Monitoring - CloudWatch Serverless Compute
Lambda Automation - Infrastructure as a Code (IaaC)	Cloud Trial Trusted Advisor

Lab Platform:

AWS Cloud (every participant will have to create own AWS free tier account to perform AWS Lab Hands-on)

Deep Learning:

Workshop Target:

Each module will have demos, case studies & practical implementations so that participants get the better understanding of the concepts.

Our target goal will be to provide enough information on the Deep Learning, so the participant can utilize the gained knowledge for the development of various applications.

Workshop Schedule:

Day 1
Theory Session	Motivation: Foundations and Terminology of Deep Learning AI vs ML vs DL: A comparison Features and Weights Machine Learning Recap: Linear Regression, Logistic Regression Activation Functions Neural Networks Loss Functions Gradient Descent Feedforward and Backward Propagation Deep Learning Model training
Lab Session	Hands on with Python Building Neural Networks Lab
Theory Session	Dataset splitting and distribution Evaluation Metrics Error Analysis Bias vs Variance Performance comparison Regularization L1/L2 regularization, Dropout Early Stopping, Normalization Optimization methods Hyperparameter Tuning
Lab Session	Neural Network Hyperparameter Tuning and Optimization
Day 2
Theory Session	ANN vs CNN Convolution, pooling, padding, striding Inception Network Transfer Learning Applications of CNN Object Detection Landmark Detection Siamese Networks
Lab Session	Building Convolutional Neural Networks Analysis of convolution, pooling, padding and striding
Lab Session	ANN vs RNN Sequential Processing with RNN Forward and Back Propagation Language Models Sampling data from RNN
Lab Session	Building Recurrent Neural Networks Text Classification with Custom Dataset
Theory Session	LSTM and GRU Word Embedding Models Sentiment Analysis Image Captioning Machine Translation Speech Transcription
Online Exam

Advanced Deep Learning:

Workshop Target:

Each module will have demos, case studies & practical implementations so that participants get the better understanding of the concepts.

Our target goal will be to provide enough information on the Advanced Deep Learning, so the participant can utilize the gained knowledge for the development of various applications.

Workshop Schedule:

Day 1
Hands on with Tensorflow 2.0 and PyTorch Unsupervised Deep Learning Sparse Coding Restricted Boltzman Machine
Day 2
Deep Belief Networks Autoencoders, Variational Autoencoders Generative Adveersial Networks (GANs) 3D CNN, YOLO v3, RefineDet, M2Det Image Segmentation, Style Transfer

Quantum Computing Workshop:

Workshop Target:

Each module will have demos, case studies & practical implementations so that participants get the better understanding of the concepts.

Our target goal will be to provide enough information on the Quantum Computing and Quantum machine Learning so the participant can utilize the gained knowledge for the development of various applications.

Workshop Schedule:

Day 1
Quantum System Physical phenomena Quantum Superposition principle Normalization Hermitian, Unitary Pauli matrices, Complex Vector Space, State Space: Hilbert Space
Day 2
Quantum states and Qubit, Representing Qubit States Quantum Algorithms Quantum Auto Encoder Quantum kernel estimation Quantum machine Learning

Workshop	Date	Timing
Deep Learning	14th December & 15th December, 2024	9.00 AM to 5.00 PM
Advanced Deep Learning
Cloud Computing
Quantum Computing

Registration Fees

Individual Workshop (Online Workshop/Training)

Duration - Two Days Workshop

Timing - 09.00 AM to 5.00 PM

Registration Fee - 1000 INR, Non Refundable (Every participant will get certificate).

Requirement and prerequisite - A laptop with good internet connectivity and knowledge of any one programming language is required.

Workshop Content

Cloud Computing :

Workshop Target:

Research Topics:

Workshop Schedule:

Lab Platform:

Deep Learning:

Workshop Target:

Workshop Schedule:

Advanced Deep Learning:

Workshop Target:

Workshop Schedule:

Quantum Computing Workshop:

Workshop Target:

Workshop Schedule:

Online Workshop/Training