Introduction to Artificial Intelligence
  • • Natural Intelligence vs Artificial Intelligence
  • • Conversion of Natural Brain into Artificial Brain
  • • Introduction to Artificial Brain
Introduction to Machine Learning- PART I
  • • History of Machine Learning
  • • Schema of Machine Learning
  • • Supervised Learning - Classification
  • • Supervised Learning - Regression
  • • Unsupervised Learning - Association
  • • Unsupervised Learning - Clustering
  • • Introduction to Reinforcement Learning
Introduction to Machine Learning- PART II
  • • ML for classification applications
  • • Data Representation/Feature Extraction
  • • Underfitting and Overfitting
  • • Evaluation of Learning Algorithms - Performance Measures - Cross Validations
  • • Advantages and Disadvantages of ML
Introduction to Artificial Neural Networks
  • • Basic technical concepts
  • • Back Propagation Neural Network - Architecture - Training Algorithm
  • • Kohonen neural networks - Architecture - Training Algorithm
  • • ANN for classification applications
Introduction to Deep Learning
  • • Artificial Neural Networks vs Deep Networks
  • • Convolutional Neural Networks - Convolutional layers - Max Pooling Layers
  • • Convolutional Neural Networks - Fully Connected Layers
  • • Transfer Learning - Pre-trained models
Applications of Machine Learning – PART I
  • • Brain tumor detection from images using ML – CASE STUDY 1
  • • Retinal abnormalities detection from fundus images using ML – CASE STUDY 2
Applications of Machine Learning – PART II
  • • COVID19 detection from lung images – CASE STUDY 3
  • • Biometric authentication from iris images – CASE STUDY 4
  • • Satellite Image Analysis using ML techniques – CASE STUDY 5
Applications of Machine Learning – PART III
  • • Human Emotion Identification from face images – CASE STUDY 6
  • • Sentiment Analysis from social media data – CASE STUDY 7
  • • General Applications of ML