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EIEIO / ARTIFICIAL INTELLIGENCE

AI-NT - AI for Non-Technical

Course outline

2 days

Duration

2 days

Module 1: Welcome and Introduction

  • Overview of course objectives and structure
  • Introduction to AI and its relevance in today's world

Module 2: Understanding Artificial Intelligence

  • Definition and types of AI
  • History and evolution of AI
  • Applications of AI in various industries

Module 3: Core Concepts of AI

  • Data and its importance in AI
  • Machine Learning vs. Traditional Programming
  • Key terminologies (e.g., algorithm, model, training, testing)

Module 4: Types of AI and Machine Learning

  • Narrow AI vs. General AI
  • Supervised, Unsupervised, and Reinforcement Learning

Module 5: Artificial Neural Networks (ANN)

  • Basic concepts of ANNs
  • Structure and functioning (neurons, layers, weights)
  • Real-world examples of ANN applications

Module 6: Interactive Session: Q&A and Group Discussions

  • Discussing participants' thoughts and experiences with AI

Module 7: AI in Everyday Life

  • AI in healthcare, finance, transportation, and more
  • Demonstrations of AI-powered applications and tools

Module 8: AI Tools and Technologies

  • Overview of popular AI tools (e.g., chatbots, image recognition, virtual assistants)
  • Hands-on activity: Exploring an AI tool (e.g., interacting with a chatbot)

Module 9: Building a Simple AI Model: MNIST Digit Classifier

  • Introduction to the MNIST dataset
  • How digit classification works
  • Demonstration: Training a simple ANN to classify MNIST digits
  • Interpreting the results and understanding model accuracy

Module 10: AI Project Lifecycle

  • Steps involved in developing an AI project
  • Importance of data collection and preprocessing
  • Model building, evaluation, and deployment

Module 11: Building a Simple Weather Chatbot

  • Introduction to the NLP
  • Introduction to python NLP modules (NLTK and spacy)
  • Demonstration: Simple Weather Chatbot

Module 12: Ethical and Social Implications of AI

  • Bias in AI and how to mitigate it
  • Privacy concerns and data protection
  • The impact of AI on jobs and society

Module 13: Future of AI

  • Emerging trends in AI research and development
  • Potential future applications of AI
  • Preparing for an AI-driven future

Programme scope, delivery arrangements and suitability are confirmed during enquiry.