Introduction to Amazon Cognito from Pluralsight

More and more organizations are implementing artificial intelligence (AI) within their processes. In this course, you'll learn the importance of responsible use of AI by taking ethics and bias into account.

More and more organizations are implementing artificial intelligence (AI) within their processes for hiring, automation, autonomous and predictive devices, and many other use cases.

In this course, Artificial Intelligence Essentials: Responsible AI, you'll discover the meaning and impact of a responsible way to implement AI.

First, you'll build an understanding of what we mean when we talk about responsibility in terms of AI.

Next, you'll see how bias comes into play and how we face it in a conscious or unconscious way every single day.

Finally, you'll get into the importance of ethics in AI by looking at unethical means in AI implementations and principles to avoid them.

When you’re finished with this course, you’ll have the skills and knowledge needed to understand what ethics and bias in AI are, and how to make sure you’re using AI in a responsible way that is benefitting users without putting others or society at a disadvantage.

What's inside

Syllabus

Course Overview

Responsible and Ethical Artificial Intelligence (AI)

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops foundational skills and knowledge about responsible use of AI, which is essential for anyone working in AI-related fields

Taught by Ben Weissman, an expert in the field of AI ethics and governance

Examines ethical considerations for using AI, which are important for addressing potential negative effects and biases

Covers responsible AI implementation, which is highly relevant to organizations using AI across industries

Provides a starting point for exploring ethical considerations in AI, though it may require supplemental learning for in-depth knowledge

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Amazon Cognito with these activities:

Review AI Fundamentals

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Reinforce your understanding of core AI concepts to enhance comprehension of ethical issues.

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Review introductory AI and machine learning materials.
Attend a refresher course or workshop.

Review: The Ethical Algorithm

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Gain a deeper understanding of the ethical principles and challenges in AI algorithm design.

View The Ethical Algorithm: The Science of Socially... on Amazon

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Read and summarize key chapters.
Identify and analyze case studies of ethical algorithm design.

Responsible AI Frameworks and Best Practices

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Explore established frameworks and guidelines for implementing responsible AI.

Browse courses on AI Ethics

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Review industry standards for ethical AI.
Identify best practices for responsible AI development.
Apply frameworks to real-world AI scenarios.

Six other activities

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Case Study Discussions

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Engage with peers to analyze real-world examples of responsible AI implementation.

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Identify case studies of responsible AI.
Analyze the ethical considerations and outcomes.
Discuss best practices and lessons learned.

Bias Exercises

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Practice recognizing and reducing bias in AI algorithms.

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Identify sources of data bias.
Analyze algorithms for potential bias.
Develop techniques to mitigate bias.

AI Ethics and Regulatory Compliance Workshop

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Attend workshops to gain practical insights on ethical AI implementation and regulatory compliance.

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Identify relevant workshops or conferences.
Attend sessions on AI ethics and regulations.
Engage with speakers and network with experts.

Ethical AI Impact Assessment

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Evaluate the ethical implications of implementing an AI solution.

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Identify stakeholders and their ethical concerns.
Analyze potential risks and benefits of the AI solution.
Develop strategies to mitigate ethical risks.
Create a report outlining the ethical impact assessment.

Contribute to Open Source Ethical AI Projects

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Collaborate on open-source initiatives to advance responsible AI practices.

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Identify open-source projects focused on ethical AI.
Contribute to codebase, documentation, or community discussions.
Showcase your contributions in a portfolio or resume.

Develop a Responsible AI Policy for an Organization

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Apply ethical principles to create a comprehensive policy for AI implementation within an organization.

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Research industry best practices and regulatory guidelines.
Conduct stakeholder interviews to identify ethical concerns.
Draft and refine an AI policy document.

Career center

Learners who complete Introduction to Amazon Cognito will develop knowledge and skills that may be useful to these careers:

Artificial Intelligence Specialist

Artificial Intelligence Specialists design, develop, and implement AI systems. Introduction to Amazon Cognito may help Artificial Intelligence Specialists gain a strong foundation in AI ethics and bias, which are important considerations for the field.

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AI Ethicist

AI Ethicists ensure that AI systems are developed and used in an ethical and responsible manner. Introduction to Amazon Cognito may provide AI Ethicists with a foundation in AI ethics.

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Machine Learning Engineer

Machine Learning Engineers work with Artificial Intelligence (AI) and related technologies to create intelligent and useful software programs. As an AI-focused course, Introduction to Amazon Cognito may help Machine Learning Engineers learn about responsible AI usage. The course could also be useful for engineers seeking to build a foundation in ethical AI for machine learning.

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Algorithm Developer

Algorithm Developers design and develop algorithms for use in computer programs. Introduction to Amazon Cognito may be helpful for Algorithm Developers seeking to create ethical and responsible AI algorithms.

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Data Scientist

Data Scientists help turn raw data into usable information. This role involves building models and analyzing data in order to provide insights. Introduction to Amazon Cognito may be useful to Data Scientists seeking to create and implement ethical AI solutions.

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Data Analyst

Data Analysts clean, analyze, and interpret data to help businesses make better decisions. Introduction to Amazon Cognito may be useful for Data Analysts seeking to implement ethical AI into their data analysis.

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Software Engineer

Software Engineers design, develop, maintain, and manage computer software systems. As an AI-focused course, Introduction to Amazon Cognito can help Software Engineers by providing a foundation for building reliable, responsible AI software.

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Business Analyst

Business Analysts work with stakeholders and analyze data to improve business processes. Introduction to Amazon Cognito may be useful for Business Analysts seeking to create ethical AI solutions that meet the needs of stakeholders.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze data and provide insights for businesses. Introduction to Amazon Cognito may be useful for Quantitative Analysts who want to develop ethical AI-powered models.

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Product Manager

Product Managers are responsible for planning and developing new products or features. Introduction to Amazon Cognito may be helpful for Product Managers hoping to incorporate ethical AI into their products.

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Data Engineer

Data Engineers design, build, and manage data pipelines and systems. Introduction to Amazon Cognito may be useful for Data Engineers seeking to incorporate ethical AI into their data engineering

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Project Manager

Project Managers plan, execute, and oversee projects. Introduction to Amazon Cognito may be useful for Project Managers who are working with AI-powered projects and who want to ensure they are done responsibly.

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