AI shiksha IIT Goa

	Date	Topic	Instructor
Week 1	28th June	Overview/History: AI and its different forms	Prof. Clint P George
	30th June	Overview/History: Machine Learning, Need for Deep Learning, Deep Learning Architectures	Prof. Chandra Sekhar
	2nd July	Basics of Neural Networks:Sigmoidal Neuron, Softmax Neuron, ReLU Neuron, Multilayer Feedforward Neural Networks for Classification and Regression Tasks, Backpropagation method for training	Prof. Chandra Sekhar
Week 2	5th July	Optimisation Methods: Stochastic gradient descent, Momentum, AdaGrad, AdaDelta, ADAM, Second order methods	Prof. Chandra Sekhar
	7th July	Regularization methods: Underfitting and Overfitting, Hyperparameter Tuning, Regularization, Dropout, Dropconnect, Batch Normalization	Prof. Chandra Sekhar
	9th July	Autoassociative Neural Networks, Stacked Autoencoder based pre-training for Deep Feedforward Neural Networks	Prof. Chandra Sekhar
Week 3	12th July	System Software and Development Environment for Deep Learning	Mr. Bharat
	14th July	Foundation of: CNN: Layers (Pooling Convolution), Object Detection	Mr. Bharat
	16th July	Hands-On Case Study: Object Detection with Pytorch	Mr. Bharat
Week 4	19th July	Introduction to Deep Learning for NLP.	Prof. Mausam
	21st July	Holiday (Id-ul-Zuha)
	22nd July	Recurrent Neural Networks and LSTM	Prof. Mausam
	26th July	Sequence to Sequence Models with Attention	Prof. Mausam
Week 5	28th July	Transformer Architecture & a Demo in Pytorch	Prof. Mausam
	30th July	Markov Decision Processes and Value Iteration	Prof. Mausam
	2nd Aug	TD Learning and Q Learning	Prof. Mausam
Week 6	4th Aug	Deep Q Learning and Policy Gradient	Prof. Mausam
	6th Aug	High Performance Computing for Deep Learning: Compute, Storage and Networking	Mr. Bharat
	9th Aug	High Performance Computing for Deep Learning: Compute, Storage and Networking	Mr. Bharat
Week 7	11th Aug	Deep Learning on Edge Devices	Mr. Bharat
Week 7	13th Aug	Live Q&A	Prof. Chandra Sekhar, Prof. Mausam, Mr. Bharat

AI Shiksha

Introduction to Deep Learning