Ai Essentials : Concepts And Demos

Ai Essentials : Concepts And Demos
Published 4/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English

| Size: 1.27 GB[/center]
| Duration: 2h 36m
A Comprehensive Course for getting stated with Artificial Intelligence

What you'll learn

Detailed Understanding of AI Terminology

Key Concepts - AI / ML, Prompt Engineering, Neural Network

Industry use cases and ideas that can be implemented

Hands-on experience, for ChatGPT, Bard, Amazon CodeWhisperer, creating a chatbot

Requirements

Basic understanding of IT

Description

Artificial intelligence is not just the future, it's the now. Through this course, you will not only understand this revolution, but also learn how to be a part of it. This course is your gateway to understanding this extraordinary ally. It's not just about learning the theoretical aspects of AI. It's about diving into real-world case studies, understanding the practical applications, and grasping the limitless opportunities that AI presents. In the journey of this course, we will demystify the complexities of AI, uncover its mysteries, and learn through relatable examples. You will come to appreciate how AI is not a distant concept, but a tangible reality that's part of our everyday lives.What you learn from this course?Understand and differentiate between AI terms.Learn about prompt engineering. Get started with developing Chatbot, with no prior coding experienceLearn how to use ChatGPT, Google Bard, Amazon QEthics and Regulations in AI. No prior experience is required to learn this course. For those curious to learn basic and advanced concepts in AI, this course is very suitable for you. In this course, we will not only look into theoretical concepts and AI terminology, but we will Get hands-on experience with real-world projects, sharpening your AI skills every step of the way.

Overview

Section 1: AI terminology

Lecture 1 Course Introduction

Lecture 2 Introduction

Lecture 3 Intro-1

Lecture 4 AI-Terms

Lecture 5 Data

Lecture 6 Machine-Learning

Lecture 7 ML-Reinforcement

Lecture 8 ML-Supervised-Learning

Lecture 9 ML-Unsupervised

Lecture 10 ML-UnSupervised-Learning

Lecture 11 ML-Reinforcement Learning

Lecture 12 Deep Learning

Lecture 13 Generative-AI

Lecture 14 Comparison

Section 2: How AI works?

Lecture 15 AI Process

Lecture 16 Understanding the Problem

Lecture 17 Data Collection

Lecture 18 Data Processing

Lecture 19 Model Selection

Lecture 20 Training and Evaluation

Lecture 21 Model Optimization

Lecture 22 Deployment and Continuous Learning

Section 3: AI Hands-on Example

Lecture 23 Introduction

Lecture 24 Problem Statement

Lecture 25 Amazon Lex Intro

Lecture 26 Chatbot-Demo

Lecture 27 Practice Example

Section 4: Generative AI

Lecture 28 Introduction to Generative AI

Lecture 29 Foundational Models

Lecture 30 ChatGPT

Lecture 31 ChatGPT Demo

Lecture 32 Amazon Q

Lecture 33 Amazon Q- Demo

Lecture 34 Google Bard

Lecture 35 Google Bard Demo

Section 5: Prompt Engineering

Lecture 36 Prompt Engineering Intro

Lecture 37 What is Prompt?

Lecture 38 Prompt Component

Lecture 39 Prompt-Eng

Lecture 40 Prompt Lifecycle

Lecture 41 Importance of Prompt

Lecture 42 Text-Text-Technique

Lecture 43 Zero-shot-Chain of thought

Lecture 44 Least-to most

Lecture 45 Text to Text Other Techniques

Lecture 46 Text-image-Prompt

Lecture 47 Text-to-Image-2

Section 6: AI Ethics and Regulations

Lecture 48 Ethics-Introduction

Lecture 49 Define Ethics

Lecture 50 Ethics Pillars

Lecture 51 Ethics Regulations

All Levels