Intro course about the value of Artificial Intelligence, how it works and benefits of including AI in your API projects
What you'll learn
Learn the basics of AI and the tech behind its amazing capabilities.
Define machine learning, how it relates to AI, and distinguish between structured and unstructured data.
Understand the Need for Neural Networks.
Discover the capabilities of generative AI and the technology that powers it.
Learn how AI enables computers to interpret and generate natural human language.
Learn the importance of data and ethics to prep for the AI innovations shaping our future.
Remove bias from data and algorithms to create ethical AI systems.
Identify the technologies related with AI.
Discover the capabilities of generative AI and the technology that powers it.
Discover how generative AI can boost productivity throughout your organization.
Requirements
Basic Computer Knowledge and internet access
You have an attitude to learn while having fun :)
Want to learn Artificial Intelligence from scratch
Description
This course was created with one goal only: to support you with the very first steps about Artificial Intelligence providing a person, API developer or not, with the basic ideas about what is AI, how it works and what are the benefits of using it within our company and internal software projects.In resume, this course will level up your AI game and help you out getting the fundamental concepts about Artificial Intelligence!So, don't worry if you have no prior knowledge!Start Learning Now. Hit the Enroll Button!The main principle behind this course is to introduce all contents in a very detailed but easy way, so it can results in a few benefits for all students enrolled:Reduces your learning curve at maximum by going straight to the point;Clear Introduction to the most popular concepts about Artificial Intelligence (AI);Gives you the knowledge and foundations to become an API developer that can take advantage of Artificial Intelligence (AI);In resume, it gives you all the tools to get a high-paying job. But how we will accomplish that?Shortly, through short and clear videos, we will cover in detail all the most important topics which are required for being familiar in Artificial Intelligence (AI) and using its potential to boost your software development lifecycle project.Thus, at the end of the course you will:test your knowledge with dozens of quizzesa practical exam.So, what are you waiting for?Be an API developer with Artificial Intelligence (AI) knowledge. Hit the Enroll Button!
Overview
Section 1: First Principles of Artificial Intelligence
Lecture 1 Introduction
Lecture 2 AI Capabilities
Lecture 3 Defining AI
Section 2: Introduction to Machine Learning
Lecture 4 Feeding Machine Learning models with data
Lecture 5 Data Types
Section 3: Basics of Neural Networks
Lecture 6 Understand the Need for Neural Networks
Lecture 7 Adding Complexity to Neural Networks
Section 4: First Principles of Generative AI
Lecture 8 Capabilities of Generative AI - Part 1
Lecture 9 Capabilities of Generative AI - Part 2
Lecture 10 How to charge Generative AI Training
Lecture 11 Emerging Ecosystem
Lecture 12 Common Concerns About Generative AI
Section 5: First Principles of Natural Language Processing
Lecture 13 Introduction
Lecture 14 Defining natural language
Lecture 15 Natural Language Understanding vs Natural Language Generation
Lecture 16 Basic Elements of Natural Language
Lecture 17 Parsing Natural Language - Part 1
Lecture 18 Parsing Natural Language - Part 2
Section 6: Data Fundamentals for AI
Lecture 19 The Importance of data today
Lecture 20 What is data-driven decision-making?
Lecture 21 The Significance of data in AI
Lecture 22 Data Classification and Types - Part 1
Lecture 23 Data Classification and Types - Part 2
Lecture 24 Data Classification and Types - Part 3
Lecture 25 The Importance of Data in AI
Lecture 26 Data Lifecycle for AI
Lecture 27 Ethics, Data, and AI - Part 1
Lecture 28 Ethics, Data, and AI - Part 2
Lecture 29 Ethics, Data, and AI - Part 3
Lecture 30 Legal and Regulatory Frameworks for Data and AI
Section 7: Create ethical AI systems
Lecture 31 Bias vs Fairness
Lecture 32 Recognize Bias in Artificial Intelligence
Lecture 33 Types of Bias - Introduction
Lecture 34 Types of Bias - Measurement Bias
Lecture 35 Types of Bias - Type 1 vs. Type 2 Error
Lecture 36 Types of Bias - Association Bias
Lecture 37 Types of Bias - Confirmation Bias
Lecture 38 Types of Bias - Automation Bias
Lecture 39 Types of Bias - Interaction Bias
Lecture 40 How Does Bias Enter the AI System?
Lecture 41 Remove Bias from Data and Algorithms - Introduction
Lecture 42 Remove Bias from Data and Algorithms - Part 1
Lecture 43 Remove Bias from Data and Algorithms - Part 2
Lecture 44 Remove Bias from Data and Algorithms - Part 3
Section 8: Artificial Intelligence Technologies
Lecture 45 Introduction
Lecture 46 Types of Machine learning
Lecture 47 The Role of Machine Learning
Lecture 48 Limitations of Machine Learning
Section 9: Exploring Generative AI
Lecture 49 Introduction
Lecture 50 What is Predictive AI
Lecture 51 What is Generative AI - Part 1
Lecture 52 What is Generative AI - Part 2
Lecture 53 Predictive AI vs Generative AI
Lecture 54 Potential risks to Generative AI
Lecture 55 Creating Responsible Generative AI
Lecture 56 Guidelines Govern AI Action
Lecture 57 Image Generative AI Models
Lecture 58 Uses of Generative AI for Imagery - Part 1
Lecture 59 Uses of Generative AI for Imagery - Part 2
Lecture 60 Uses of Generative AI for Imagery - Part 3
Lecture 61 Uses of Generative AI for Imagery - Part 4
Lecture 62 Uses of Generative AI for Imagery - Part 5
Lecture 63 Ethics of Generated Artwork
Section 10: Generative AI for Organizations
Lecture 64 The Potential of Generative AI for Companies
Lecture 65 Boost Companies with Generative AI - Part 1
Lecture 66 Boost Companies with Generative AI - Part 2
Lecture 67 Boost Companies with Generative AI - Part 3
Lecture 68 Boost Companies with Generative AI - Part 4
Lecture 69 Boost Companies with Generative AI - Part 5
Lecture 70 Boost Companies with Generative AI - Part 6
Section 11: Change Management for AI Execution
Lecture 71 What Is Change Management
Lecture 72 The Keys to Change Management
Lecture 73 Human-centered approach to AI adoption - Part 1
Lecture 74 Human-centered approach to AI adoption - Part 2
Lecture 75 Embrace the change
Lecture 76 Build Trust
Lecture 77 Increase Collaboration
Section 12: Wrap up
Students curious to learn about a top trending technology for the future.,Software professionals who are looking for a career change option into Artificial Intelligence.,Non-software professionals who are looking for to start a new career in the IT sector.,All professionals who are looking for to work with one of to most in-demanding technology and get a better salary.
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