Artificial Intelligence

• Welcome & Introduction
  • Ice-breaking session
  • Setting expectations and objectives
• History and Evolution of AI
  • From Turing to Deep Blue to AlphaGo: Major milestones
• Basic Terminologies in AI and ML
  • Key concepts: Algorithms, Neural Networks, Training Data, etc.
• AI in the Modern World
  • Practical demonstrations of everyday AI applications
  • Discussion: AI's most transformative uses in the last decade
• Hands-on: Setting up Python & necessary tools for AI development

• The Lifeblood of AI: Data
  • Types of data: Quantitative vs Qualitative, Time series, etc.
  • Data Collection methods and tools
• Data Cleaning and Pre-processing
  • Outliers, Missing Data, Normalization
  • Hands-on: Cleaning a sample dataset using Python
• Basics of Databases and Data Warehouses
  • SQL and NoSQL databases
  • Hands-on: Querying databases using SQL
• Big Data and AI
  • Hadoop and Spark basics
  • Hands-on: Setting up a basic Spark environment and processing data

• Basics of Parallel Processing & Cluster Computing
  • Benefits and challenges
• Role of Cluster Computing in Big Data
  • Introduction to tools: Kubernetes, Docker
  • Hands-on: Setting up a basic Kubernetes cluster
• Data Streaming and Real-Time Processing
  • Kafka, Storm: Overview and usage
  • Hands-on: Building a simple real-time data streaming application
• Deep Dive: Defense Industry's Use of Cluster Computing
  • Case studies and insights

• ML Fundamentals
  • Dive into Supervised and Unsupervised Learning
  • Popular algorithms: Decision Trees, SVM, Clustering
  • Hands-on: Training a simple model using a supervised algorithm in Python
• Deep Learning Basics
  • Neural Networks, Activation functions
  • Introduction to platforms: TensorFlow, PyTorch
  • Hands-on: Building a basic Neural Network for image recognition
• Model Evaluation
  • Understanding Precision, Recall, ROC, AUC
  • Hands-on: Evaluating the models built earlier

• Natural Language Processing
  • Tokenization, Named Entity Recognition, Sentiment Analysis
  • Hands-on: Building a basic sentiment analysis tool
• Computer Vision
  • Convolutional Neural Networks, Image Processing techniques
  • Hands-on: Image classification using CNNs
• AI Ethics
  • Discussing real-world cases of AI bias and implications
  • Ethical considerations in defense AI: Autonomous weapons, decision-making algorithms
• Closing Session
  • Recap and insights from trainers' industry experience
  • Predictions for AI's future: Opportunities and challenges
  • Q&A and Feedback session

This training promises not just a glimpse into AI's capabilities but also hands-on experience, ensuring participants are well-equipped to harness its potential. Drawing from the rich experiences of our trainers, who have been at the helm of cutting-edge AI advancements, we aim to inspire, educate, and empower our participants. There will be hand-crafted guidance from the trainers to ensure that the trainees benefit to the maximum.