From Zero to Hero in AI & Machine Learning (No Coding)

Name: From Zero to Hero in AI & Machine Learning (No Coding)
Rating: 3.5 (3 reviews)

Your complete non-technical introduction to the world of Artificial Intelligence and Machine Learning.

Created byLamis Elia

Last updated 6/2025

English

What you'll learn

Explain the key concepts of Artificial Intelligence and Machine Learning in simple terms
Differentiate between AI, Machine Learning, and Deep Learning with real-world examples
Identify common machine learning types like supervised and unsupervised learning
Recognize real-life applications of AI in healthcare, marketing, social media, and more

Course content

6 sections • 93 lectures • 3h 0m total length

Course Introduction: Mastering AI & Machine Learning (No Coding Required)4:30

Introduction to AI0:51
Welcome!
Hey there, and welcome! Zero to Hero in AI & Machine Learning (No Coding)
You’ve just taken your very first step into one of the most exciting, fast-growing, and life-changing fields of our time — Artificial Intelligence.
Now, don’t worry — you don’t need to be a tech genius or know how to code. This course is designed for everyone, whether you’re just curious about AI or already thinking about how to use it in your career or everyday life.
In this lesson, we’re going to break down what AI really means — beyond all the sci-fi movies and buzzwords. You’ll learn what I actually am, how it works in simple terms, and why it matters in our world today.
From your smartphone to smart assistants, AI is already part of your life — and this course will help you understand it like never before.
Ready to dive in? Let’s get started!
Do I Need to Be a Tech Expert?2:58
So… what exactly is AI?1:24
It’s Not About Emotions or Robots2:27
Think of a Baby…1:57
Real-Life AI Examples1:57
But AI Isn’t Perfect1:39
Testing Your Understanding
History & Evolution of AI1:32
The Birth of Modern AI (1950s)1:47
Early AI Hopes and Hype (1960s–1970s)1:21
The AI Winters (1970s–1990s)1:09
AI Comeback – The Rise of Machine Learning (2000s)1:02
AI Explosion – Today’s AI (2010s–Now)2:41
Testing Your Understanding
Introduction — You Use AI More Than You Think0:58
Streaming Platforms — Netflix, YouTube, Spotify1:16
Smart Cars & Navigation (Google Maps, Tesla, Uber)1:06
Shopping — Amazon, Instagram & E-commerce1:14
Social Media — Facebook, TikTok, Instagram1:27
TESTING YOUR UNDERSTANDING
Introduction — AI vs Human Intelligence1:14
Speed — AI is Fast, Humans are Flexible1:38
Creativity — Humans Lead Here1:38
Problem Solving — Logic vs. Intuition1:30
Learning Style — AI Needs Data, Humans Need Life1:29
Emotions & Ethics — Only Humans Feel1:28
Testing Your Knowledge

Introduction – Understanding Machine Learning1:34
INTRODUCTION: What is Machine Learning?1:44
The Role of Data1:55
Algorithms at Work2:07
Training and Testing the Model1:46
Learning from Mistakes1:45
TESTING YOUR UNDERSTANDING
Introduction: AI vs ML vs Deep Learning1:38
What is Artificial Intelligence (AI)?1:40
What is Machine Learning (ML)?1:30
What is Deep Learning (DL)?1:37
TESTING YOUR UNDERSTANDING
What is Supervised Learning?3:08
Examples of Supervised Learning3:07
What is Unsupervised Learning?3:19
Examples of Unsupervised Learning & Key Differences3:43
TESTING YOUR UNDERSTANDING
Introduction — Applications of Machine Learning Around You3:00
Personal Assistants2:35
Entertainment Recommendations2:51
Social Media Feeds3:03
Healthcare and ML3:10
Transportation & Navigation2:22
TESTING YOUR UNDERSTANDING

Introduction: Key Concepts Made Easy Introduction2:09
What is a Machine Learning Model?1:26
How a Model Learns from Data (Training Phase)1:41
Real-Life Example – Training a Model to Recognize Cats and Dogs1:32
TESTING YOUR UNDERSTANDING
Understanding Data in Machine Learning0:42
What is Data in Machine Learning + Types of Data1:12
Features, Labels, and Why Good Data Matters3:52
Real-Life Example – Predicting House Prices0:54
Testing Your Understanding
Classification vs Regression (with Examples)0:40
What is Classification in Machine Learning?1:38
What is Regression in Machine Learning?1:29
How to Tell If a Problem Needs Classification or Regression1:23
Testing Your Understanding
Overfitting and Underfitting (in simple terms) Introduction:1:52
What is Overfitting?1:28
What is Underfitting?1:17
How to Avoid Overfitting and Underfitting4:11
Testing Your Understanding

Introduction-Real-World Applications & Case Studies1:37
Introduction AI in Healthcare, Marketing, Beauty Tech, and More0:40
AI in Healthcare: Early Detection and Personalized Medicine1:25
AI in Marketing — Personalization and Customer Insights1:21
AI in Beauty Tech — Virtual Try-Ons and Skin Analysis2:38
TESTING YOUR Understanding
AI in Recommendation Systems (Netflix, Amazon)3:15
How AI Predicts User Preferences2:54
Collaborative Filtering vs. Content-Based Filtering2:21
Challenges of AI in Recommendation Systems2:04
TESTING YOUR UNDERSTANDING
AI in Social Media, Facial Recognition, and Chatbots2:10
AI in Social Media — Content Curation and Personalization1:30
AI in Facial Recognition — Benefits and Concerns1:30
AI Chatbots — Revolutionizing Customer Service2:49
TESTING YOUR UNDERSTANDING

Introduction: The Future and Next Steps1:41
Introduction: Ethics in AI: Can We Trust Machines?1:15
Understanding Ethical Dilemmas in AI2:11
AI Bias and Fairness: The Role of Data2:17
Accountability and Transparency in AI Decision-Making2:28
Building Ethical AI — What Can We Do?3:03
TESTING YOUR UNDERSTANDING
Introduction: Jobs in AI & ML (Non-Coding Roles Too!)1:21
Topic 1: Exploring Non-Coding Roles in AI and ML2:55
AI Data Analyst: The Bridge Between Data and Action2:41
AI in Business: Strategic Roles and Impact2:12
TESTING YOUR UNDERSTANDING
Free Resources to Continue Learning Introduction1:12
Leveraging Online Platforms and Courses for AI Learning2:21
AI Communities: Learning from Others2:19
Using Free AI Tools for Hands-On Learning2:04
TESTING YOUR UNDERSTANDING
Introduction — How to Keep Growing in This Field Introduction1:01
Setting Learning Goals in AI1:47
Staying Updated with AI News and Trends1:32
Building a Portfolio and Networking in AI1:33
FINAL COURSE OUTRO0:54
TESTING YOUR UNDERSTANDING

Requirements

No programming or technical background needed — just curiosity and a willingness to learn

Description

Are you curious about Artificial Intelligence and Machine Learning but have no technical background? Do words like “algorithms” and “models” feel overwhelming? This course is for you.

“From Zero to Hero in AI & Machine Learning (No Coding Required)” is a beginner-friendly course designed to simplify complex concepts using real-world examples and plain language. You don’t need to know how to code or have any prior experience in tech.

We start by helping you understand what AI really is, how it’s evolved, and where it appears in your everyday life. You’ll learn the difference between Artificial Intelligence, Machine Learning, and Deep Learning, and how machines learn from data to make decisions.

We'll break down key topics like models, training, classification vs. regression, and demystify terms like overfitting and underfitting.

This course also explores real-world applications — from healthcare and marketing to Netflix recommendations, chatbots, facial recognition, and more.

You’ll also learn about AI ethics, the future of intelligent systems, and the kinds of jobs available in AI and ML — even if you're not a programmer.

Whether you're a student, career-changer, entrepreneur, or just someone interested in the future of technology, this course is designed to give you the foundation to talk about AI confidently and explore how it impacts the world around you.

No coding. No complicated math. Just clear, engaging learning. Let’s get started!

Who this course is for:

Anyone curious about AI and Machine Learning, especially beginners with no coding experience — students, career switchers, and non-tech professionals

From Zero to Hero in AI & Machine Learning (No Coding)

What you'll learn

Explore related topics

Course content

Course Introduction1 lecture • 5min

MODULE 124 lectures • 38min

MODULE 220 lectures • 48min

MODULE 316 lectures • 27min

MODULE 413 lectures • 26min

MODULE 519 lectures • 37min

Requirements

Description

Who this course is for: