Responsible Machine Learning

Responsible Machine Learning, available at Free, with 20 lectures, and has 450 subscribers.

You will learn about Understand Responsible Machine Learning Know of some mitigating Responsible ML tools Understand Bias in AI understand fairness and AI safety This course is ideal for individuals who are AI enthusiasts or Programmers or Educators or Teachers or Cyber Fanatics or Internet Regulators It is particularly useful for AI enthusiasts or Programmers or Educators or Teachers or Cyber Fanatics or Internet Regulators.

Enroll now: Responsible Machine Learning

Summary

Title: Responsible Machine Learning

Price: Free

Number of Lectures: 20

Number of Published Lectures: 20

Number of Curriculum Items: 20

Number of Published Curriculum Objects: 20

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

Understand Responsible Machine Learning
Know of some mitigating Responsible ML tools
Understand Bias in AI
understand fairness and AI safety

Who Should Attend

AI enthusiasts
Programmers
Educators
Teachers
Cyber Fanatics
Internet Regulators

Target Audiences

AI enthusiasts
Programmers
Educators
Teachers
Cyber Fanatics
Internet Regulators

Welcome to “Responsible Machine Learning,” a comprehensive course designed to equip you with the knowledge and skills necessary to develop and implement ethical and fair AI systems. This course delves into the principles and practices essential for creating machine learning models that adhere to human-centric values and societal norms.

Throughout this course, we will explore key topics including accountability, transparency, explainability, safety, fairness, and bias in AI. You will learn how to identify and mitigate bias using tools like Microsoft Fairlearn and IBM AI Fairness 360, ensuring that your AI systems operate without discrimination.

We will also discuss the importance of adhering to institutional, national, and international guidelines, maintaining detailed documentation, and defining clear roles and responsibilities within AI development teams. Real-world examples and case studies will illustrate how these principles are applied in various industries, from finance and healthcare to transportation and security.

By the end of this course, you will have a robust understanding of the ethical implications of AI, practical strategies for implementing responsible machine learning, and the ability to create transparent, accountable, and fair AI models. Join us to become a leader in the development of responsible AI technologies, fostering trust and reliability in your AI solutions.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Getting Started

Chapter 2: Why Responsible ML

Lecture 1: Why the need for Responsible Machine Learning

Chapter 3: Ensuring Responsible ML

Lecture 1: How to ensure Responsible Machine Learning

Chapter 4: Accountability- Responsible Machine Learning

Lecture 1: How to ensure Accountability in Responsible Machine Learning

Chapter 5: Transparency-Responsible Machine Learning

Lecture 1: How to ensure Transparency in Responsible Machine Learning

Chapter 6: Explainability-Responsible Machine Learning

Lecture 1: Ensuring Explainability in Responsible Machine Learning

Chapter 7: Safety in Responsible Machine Learning

Lecture 1: How to ensure safety in Responsible Machine Learning

Chapter 8: Fairness-Responsible Machine Learning

Lecture 1: Fairness in AI

Chapter 9: Bias-Responsible Machine Learning

Lecture 1: Understanding Bias

Chapter 10: Privacy and Robustness Responsible ML

Lecture 1: Privacy and Robustness Responsible ML

Chapter 11: Recommended Actions

Lecture 1: Some Recommended Actions to take in ensuring Responsible ML

Chapter 12: Mitigating Tools

Lecture 1: Mitigating Tools-Responsible Machine Learning

Chapter 13: Federated Learning

Lecture 1: Futture Trends in Responsible ML

Lecture 2: Federated Learning

Lecture 3: Explainable AI

Lecture 4: AI in Education

Chapter 14: Ethical AI

Lecture 1: Technology

Lecture 2: Ethical AI

Lecture 3: Misuse AI

Lecture 4: Ai for Social Good

Instructors

Bliva TangerynTech
Cyber Analyst | Artist | IT Specialist | WordPress Developer
Christian Kusi
Instructor at Udemy

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Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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