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Artificial Intelligence - An essential Introduction
Rating: 4.7 out of 5(16 ratings)
23 students

Artificial Intelligence - An essential Introduction

Master the fundamentals of AI and discover how it's transforming industries, technology, and everyday life
Created byGurjit Bhairon
Last updated 7/2025
English
English [Auto],

What you'll learn

  • Gain a clear understanding of how artificial intelligence functions
  • Understand machine learning components ( Data, algorithms and models)
  • Familiarize themselves with essential AI terminology
  • Understand how models and large language models are trained
  • Understand what AI agents are and how AI agents work
  • Be able to talk about the different types of AI ( Narrow AI, AGI, ASI)
  • Be able to discuss the tools used for generative AI
  • Understand why and how AI needs to be controlled so as to not pose an existential threat
  • Be able to discuss ethical considerations in AI
  • Explore practical, real-world applications of AI
  • Discover and evaluate today’s leading AI tools
  • Understand the difference between machine learning and deep learning
  • Understand why and how neural networks are used

Course content

1 section • 9 lectures • 36m total length

  • Introduction2:31

    This introduction gives an overview of the key areas of Artificial Intelligence that we will be covering .


    There is a short quiz at the end of each lecture to test and reinforce your understanding of the lecture.

  • Lecture 2: Artificial Intelligence Technologies3:23

    AI Technologies

    What you will learn about :

    • Types of Machine Learning

    • Deep Learning ( DL) 

    • Natural Language Processing ( NLP) 

    • Conversational AI 

    • Characteristics of Large Language Models


      Apply your learning to a quiz at the end of the lecture

  • Lecture 3 - Generative AI2:13

    Generative AI 

    What you will learn about :

    • Tools for text generation

    • tools for image generation

    • tools for music and video generation

    • some key applications of AI


      Apply your learning to a quiz at the end of the lecture

  • Lecture 4 - Machine Learning Components3:44

    Machine Learning Components

    You will learn about :

    • Datasets

    • Algorithms

    • Models

    • Training Models


      Apply your learning to a quiz at the end of the lecture

  • Lecture 5 - How Large Language Models Work5:31

    Training a Large Language Model

    You will learn about

    • Data collections

    • Model pre-training

    • Reward modelling

    • Reinforcement learning

    • what are alligned LLMs

    • Prompting


    Apply your learning to a quiz at the end of the lecture

  • Lecture 6 - AI Agents7:32

    AI Agents

    You will  :

    • Understand what an AI agent is and how it differs from traditional software

    • Identify the main types of AI agents (simple reflex, model-based, goal-based, utility-based)

    • Recognize real-world examples of AI agents in action

    • Apply key concepts through a short quiz to solidify learning


      Apply your learning to a quiz at the end of the lecture



  • Lecture 7 - AI an Existential Threat7:19

    AI An Existential Threat

    You will learn about :

    • Philosophical discussions on AI consciousness

    • Existential Risks of AI

    • AI and Human Control

    • Balancing innovation and risk

    • AI ethics and fairness

    • Regulation and responsible AI 


      Apply your learning to a quiz at the end of the lecture



  • Lecture 8 - Types of AI2:26

    Types of AI 

    You will learn about :

    • Narrow AI 

    • General AI ( AGI) 

    • Super AI ( ASI) 


      Apply your learning to a quiz at the end of the lecture

  • Lecture 9 - Conclusion1:22

    Summary and final thoughts

Requirements

  • No prior experience in AI , you will learn all of the fundamentals of Artificial Intelligence here
  • People who may have learnt something about AI but want a more complete picture of the AI landscape

Description

Artificial Intelligence (AI) is rapidly reshaping how we live, work, and interact with the world. This beginner-friendly course offers a comprehensive introduction to key AI concepts, designed for anyone curious about intelligent technologies and their real-world impact.

You'll learn the fundamentals of machine learning, neural networks, natural language processing (NLP), computer vision, and the difference between narrow AI and artificial general intelligence (AGI). The course explains how parameters influence model outputs, how AI systems are trained, and how large language models (LLMs) work within practical workflows—covering everything from data input to training cycles and feedback.

Each lecture includes a short reinforcement quiz to help solidify your understanding and encourage retention. With clear, jargon-free explanations, learners gain a strong foundation in AI model architecture, types of learning (like supervised, unsupervised, and reinforcement learning), and ethical implications of modern AI systems.

Authored by an experienced software developer with 35+ years in the tech industry and a passion for science and innovation, this course prioritizes clarity, curiosity, and real-world relevance.

Whether you're a student, professional, or tech enthusiast, you'll finish with the confidence to engage in AI discussions and explore advanced topics. No prior experience required—just basic English comprehension and an internet-enabled device.

Who this course is for:

  • General Learners & Ethicists
  • Lifelong Students, Entrepreneurs & Innovators
  • Tech Enthusiasts & Hobbyists
  • Policymaker
  • Ethicists
  • Beginners who want to know more about AI
  • Students
  • People curious about AI

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