From Using Ai To Understanding It

Machine Learning Concepts, NLP, Object Detection, GenAI, Prompt Engineering, Deployment, Ethical AI, Real-World Examples

What you'll learn

Understand core AI concepts

Learn the key terminology around AI

Understand supervised, unsupervised and reinforcement learning concepts

Discover Feature Engineering

Learn the steps to build an AI model

Differences between a supervised and unsupervised learning

A concrete example of unsupervised learning using k-means

Basics of neural networks and the deep learning notions

Introduction to Tensorflow as a library for building deep learning models

Introduction to computer vision

Understand object detection and data labeling

Discover Natural Language Processing (NLP)

Learn about Generative AI

Find the right Generative AI tool for your task

Text, image, audio and video generation

Prompt engineering tips and tricks

Understand APIs and how to expose an AI model through an API

Discover the cloud and AI cloud services

Understand AI Ethics principles

Discover fairness, transparency, accountability, privacy and reliability in AI systems

Explore ethical considerations and how to achive ethical AI

Real-world examples to form a solid understanding of the real AI adoption

Requirements

No programming experience needed, just a curiosity around the topic

Description

From Using AI to Understanding It was inspired by the many non-technical professionals who told me they wanted to better understand AI's capabilities and to truly grasp how AI works, so that they can use it in their careers and personal lives. You are an user of AI powered tools — now it’s time to go deeper and figure out what’s happening behind the scenes and what it means to integrate AI.Whether you're a tech enthusiast, a product manager, a department lead that wants to boost the team's productivity, but lacks prior understanding of what it means to adopt AI in production, or simply someone who wants to understand AI on a deeper level, this course will give you the knowledge you need.The concepts are presented in a clear, approachable way, so that you can understand them without coding experience.You'll explore different types of machine learning, learn how AI systems are trained using data, understand computer vision and NLP, so that you have a solid knowledge across diverse areas of AI. Using GenerativeAI can open so many possiblities that we will discover together. We will even dive deeper on how to compose the best prompt to get to the best results.We'll address deployments and cloud services so that you can know before hand what it would mean to use AI in your company, and we'll address AI ethical principles to set you on the right track for a responsible AI adoption.Through real-world examples, visual explanations, and easy-to-follow lessons, you’ll develop a solid foundation that will enable you to fully understand AI's capabilities and implications.By the end of this course, you’ll :Be able to speak confidently about how AI worksUnderstand the building blocks of modern AIKnow what goes into training a model — and why it mattersMake smarter decisions when working with or around AIBe ready to adopt AIIf you're ready to lift the curtain behind the buzzwords, this course will give you the solid understanding that you've been looking for, and who knows, you may be that professional that makes a difference with AI.

Overview

Section 1: Course Introduction

Lecture 1 Introduction and Learning Objectives

Section 2: Introduction to Artificial Intelligence

Lecture 2 What is AI? How about ML, Deep Learning, GenAI, Data Science?

Lecture 3 A Brief History of AI

Lecture 4 Supervised, Unsupervised, Reinforcement Learning

Lecture 5 AI Examples in the Real World

Lecture 6 Introduction to Kaggle

Section 3: Steps for Building a Supervised Learning Model

Lecture 7 Feature Engineering

Lecture 8 Supervised Learning Models

Lecture 9 Steps for Building a Model

Section 4: Discover Unsupervised Learning

Lecture 10 Understanding Unsupervised Learning

Lecture 11 K-Means Clustering Example

Section 5: Neural Networks and Deep Learning

Lecture 12 What are Neural Networks

Lecture 13 Using Deep Learning

Section 6: Computer vision and NLP

Lecture 14 Understanding Object Detection

Lecture 15 On Data Labeling

Lecture 16 AI for Images

Lecture 17 Introduction to NLP

Section 7: Generative AI

Lecture 18 Generative AI Introduction

Lecture 19 GenAI Models

Lecture 20 Prompt Engineering Introduction

Lecture 21 Prompt Engineering Techniques

Lecture 22 How to Improve the Answer?

Lecture 23 Understanding the Answer Better

Lecture 24 Prompt Engineering Summary

Lecture 25 Data Exploration with GenAI

Lecture 26 GenAI Text Examples

Lecture 27 Image Generation

Lecture 28 Video Generation

Lecture 29 Audio Generation

Section 8: Deployment and Cloud Services

Lecture 30 Exposing a Model Through an API

Lecture 31 What is the Cloud

Lecture 32 AI in the Cloud

Section 9: Ethical AI and Responsible AI

Lecture 33 AI Ethics Principles

Section 10: Final Thoughts

Lecture 34 Congratulations!

Anyone interested to understand Artificial Intelligence, what it is, how it works, how to adopt it and where it can be used,Product Managers that want to integrate AI into their projects,Business professionals that want to understand what AI can do for them,Anyone interested in how to make the most out of GenAI tools