Basics of AI and Foundations

Learn the core principles behind AI systems, from rule-based logic to data-driven learning.

Basics of AI and Foundations showcase image
Track
New Collar
Level
Beginner
Language
English
Duration
30 hours
Learning Mode
Learn at ALC or at Home

Introduction

  • Describe the core concepts of Artificial Intelligence (AI) and offer a historical context to understand its development.
  • Classify different types of AI, distinguishing between Narrow AI and General AI for a comprehensive perspective.
  • Explain the key components of AI and their roles in machine learning processes, emphasizing their connection to data.
  • Discuss the ethical considerations in AI, highlighting issues related to privacy, bias, and sustainability.
  • Explore the practical applications of AI in diverse fields such as healthcare, finance, and entertainment to showcase its versatility.
  • Analyse the societal impact of AI, focusing on its benefits and potential challenges to provide a well-rounded view.
  • Examine ethical frameworks in real-world AI scenarios, fostering responsible and ethical practices in the implementation of artificial intelligence.

What you'll learn ?

  • By the end of the course, learners will be able to:
  • Define AI and articulate its historical development, providing a comprehensive overview.
  • Identify and classify different types of AI, facilitating a nuanced understanding of AI diversity.
  • Explain the fundamental components of AI, fostering a clear comprehension of machine learning processes.
  • Discuss ethical considerations in AI, demonstrating an awareness of privacy, bias, and sustainability.
  • Explore and apply AI in various industries, showcasing practical knowledge and insights.
  • Analyse the societal impact of AI, critically evaluating its contributions and potential drawbacks.
  • Apply ethical frameworks to real-world AI scenarios, ensuring a responsible and ethical approach to AI implementations.

Syllabus

Course Introduction
  • Introduction to Artificial Intelligence and Machine Learning
  • Objectives
  • Introduction to AI
    • History of AI
    • Definition and its importance
    • What is Generative AI?
    • Teaching machines to mimic human intelligence
  • Understanding the basics of AI
    • Concept of ‘Intelligence’
    • Machine Intelligence
  • Types of AI
    • Narrow AI
    • General AI
    • Super intelligent AI
  • Components of AI
    • Understanding how machines learn from data
    • Power of ‘Reasoning’
    • The ability of problem-solving
    • Discussing how machines interpret sensory information
    • Linguistic Intelligence
    • Perception and Computer Vision
    • Robotics and Motion
    • Knowledge Representation
    • Planning and Navigation
  • Ethics in AI
    • The 3 key areas of AI ethics
    • Privacy and data protection
    • Bias and discrimination
    • How to establish AI ethics?
    • Sustainability in AI
  • Recap and outcome
  • FAQs
  • Summary
  • Objectives
  • Introduction to Machine Learning
    • Key components and processes of Machine Learning
    • How Algorithms work in Machine Learning?
    • Applications of Machine Learning
    • Benefits and drawbacks of Machine Learning
  • Introduction to Deep Learning
    • Artificial Neural Networks
    • Structure and components of Artificial Neural Networks
    • Overview of Neural Network types
    • Benefits and drawbacks of Deep Learning
  • Introduction to Natural Language Processing (NLP)
    • Applications of NLP in Machine Learning
  • Introduction to Computer Vision
    • Technologies involved in Computer Vision
  • Introduction to Cognitive Computing
    • Benefits of Cognitive Computing
  • Summary

Work-Centric Approach

The academic approach of the course focuses on ‘work-centric’ education. With this hands-on approach, derive knowledge from and while working to make it more wholesome, delightful and useful. The ultimate objective is to empower learners to also engage in socially useful and productive work. It aims at bringing learners closer to their rewarding careers as well as to the development of the community.

  • Step 1: Learners are given an overview of the course and its connection to life and work
  • Step 2: Learners are exposed to the specific tool(s) used in the course through the various real-life applications of the tool(s).
  • Step 3: Learners are acquainted with the careers and the hierarchy of roles they can perform at workplaces after attaining increasing levels of mastery over the tool(s).
  • Step 4: Learners are acquainted with the architecture of the tool or tool map so as to appreciate various parts of the tool, their functions, utility and inter-relations.
  • Step 5: Learners are exposed to simple application development methodology by using the tool at the beginner’s level.
  • Step 6: Learners perform the differential skills related to the use of the tool to improve the given ready-made industry-standard outputs.
  • Step 7: Learners are engaged in appreciation of real-life case studies developed by the experts.
  • Step 8: Learners are encouraged to proceed from appreciation to imitation of the experts.
  • Step 9: After the imitation experience, they are required to improve the expert’s outputs so that they proceed from mere imitation to emulation.
  • Step 10: Emulation is taken a level further from working with differential skills towards the visualization and creation of a complete output according to the requirements provided. (Long Assignments)
  • Step 11: Understanding the requirements, communicating one’s own thoughts and presenting are important skills required in facing an interview for securing a work order/job. For instilling these skills, learners are presented with various subject-specific technical as well as HR-oriented questions and encouraged to answer them.
  • Step 12: Finally, they develop the integral skills involving optimal methods and best practices to produce useful outputs right from scratch, publish them in their ePortfolio and thereby proceed from emulation to self-expression, from self-expression to self-confidence and from self-confidence to self-reliance and self-esteem!