Machine Teaching for Autonomous AI from Coursera

Just as teachers help students gain new skills, the same is true of artificial intelligence (AI). Machine learning algorithms can adapt and change, much like the learning process itself. Using the machine teaching paradigm, a subject matter expert (SME) can teach AI to improve and optimize a variety of systems and processes. The result is an autonomous AI system.

In this course, you’ll learn how automated systems make decisions and how to approach designing an AI system that will outperform current capabilities. Since 87% of machine learning systems fail in the proof-concept phase, it’s important you understand how to analyze an existing system and determine whether it’d be a good fit for machine teaching approaches. For your course project, you’ll select an appropriate use case, interview a SME about a process, and then flesh out a story for why and how you might go about designing an autonomous AI system.

At the end of this course, you’ll be able to:

• Describe the concept of machine teaching

• Explain the role that SMEs play in training advanced AI

• Evaluate the pros and cons of leveraging human expertise in the design of AI systems

• Differentiate between automated and autonomous decision-making systems

• Describe the limitations of automated systems and humans in real-time decision-making

• Select use cases where autonomous AI will outperform both humans and automated systems

• Propose an autonomous AI solution to a real-world problem

• Validate your design against existing expertise and techniques for solving problems

This course is part of a specialization called Autonomous AI Fundamentals.

What's inside

Syllabus

An Introduction to Autonomous AI & Machine Teaching

This module lays the foundation for this course and the entire specialization. You'll learn what makes autonomous AI different from other forms of artificial intelligence. You're invited to take a behind the scenes look at some organizations using autonomous AI and hear from operators and managers about the benefits they're realizing by harnessing autonomous AI. The focus will then transition to you! You'll explore five different mindset profiles that describe different approaches to building AI systems.

Analyzing the Problem

Not all problems are right for an autonomous AI solution. In this module, we explore types of automated systems and their strengths and limitations for various issues. You'll learn how to determine whether a problem needs a solution that goes beyond automated systems and into useful AI.

Learning the Solution

In the last module we looked at "automated" systems (math, menus, and manuals); examining situations where they excel and understanding their limitations. In this module we'll focus on "autonomous" systems such as: machine learning (ML), reinforcement learning (RL), neural networks (NN) and deep reinforcement learning (DRL); assessing both the strengths and weaknesses of each autonomous system. Lastly you'll see how "machine teaching" can tap into the strengths of all the automated and autonomous systems.

Storytelling

Wondering what has storytelling has got to do with AI? Good storytelling is a tool of persuasion. Dry facts and data are not as compelling as persuasion arguments. In the real world someone has to fund the development of your autonomous AI design, and you need to tell that person a persuasive story.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops students' understanding of machine teaching, a topic that is highly relevant to fields like computer science and artificial intelligence

Taught by Kence Anderson, an experienced instructor known for their work in machine learning and artificial intelligence

Provides hands-on experience through a course project, allowing learners to apply their knowledge of machine teaching to a real-world problem

Examines the limitations of both automated and autonomous decision-making systems, providing a balanced perspective on the capabilities of AI

Requires learners to have a basic understanding of machine learning and artificial intelligence concepts

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 Machine Teaching for Autonomous AI with these activities:

Review key concepts from introductory machine learning

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Refresh your knowledge of fundamental machine learning concepts to enhance your understanding of machine teaching.

Browse courses on Machine Learning Basics

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Review lecture notes or textbooks from an introductory machine learning course.
Go through online tutorials or videos that cover the basics of machine learning.

Review probability and statistics concepts

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Refresh your understanding of probability and statistics to strengthen your foundation for machine learning and autonomous AI concepts.

Browse courses on Probability

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Review textbooks or online resources on probability and statistics.
Solve practice problems to test your understanding.

Participate in online discussion forums

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Engage with peers and experts in online discussion forums to exchange ideas, ask questions, and expand your understanding of machine teaching.

Browse courses on Machine Teaching

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Identify relevant online forums or discussion groups focused on machine teaching or AI.
Join the forums and actively participate in discussions, sharing your insights and asking questions.

Four other activities

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Show all seven activities

Develop a concept map of machine teaching

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Create a visual representation of the relationships between the key concepts in machine teaching to enhance understanding and retention.

Browse courses on Machine Teaching

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Start by identifying the core concepts of machine teaching, such as supervised learning, unsupervised learning, and reinforcement learning.
Brainstorm the relationships between these concepts and how they connect to one another.
Use a mind mapping tool or software to visually represent the relationships, creating a comprehensive concept map.

Follow online tutorials on autonomous AI

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Explore online resources and tutorials to supplement the course material and gain a deeper understanding of autonomous AI concepts.

Browse courses on Autonomous AI

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Identify reputable online platforms or resources that offer tutorials on autonomous AI.
Select tutorials that align with your learning goals and interests.
Follow the tutorials, completing any exercises or assignments to reinforce your understanding.

Solve machine learning practice problems

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Practice solving machine learning problems to build a strong foundation in the concepts of machine teaching.

Browse courses on Machine Learning

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Identify a reputable online platform or textbook with machine learning practice problems.
Start solving the problems, focusing on understanding the concepts and algorithms being used.
Review your solutions with an experienced ML practitioner or instructor to identify any errors or areas for improvement.

Design an autonomous AI system for a real-world problem

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Apply the concepts of machine teaching to design and develop an autonomous AI system that addresses a specific real-world problem.

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Identify a real-world problem that can be addressed using an autonomous AI system.
Research and gather data relevant to the problem.
Design the autonomous AI system, selecting appropriate algorithms and techniques.
Implement the system and evaluate its performance.

Career center

Learners who complete Machine Teaching for Autonomous AI will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use a variety of approaches to extract actionable insights from data. They use their knowledge of mathematics, modeling, and analysis to build systems that make predictions or power other types of decision making. Machine Teaching for Autonomous AI can help you develop the skills needed to design and implement these systems. You will learn how to analyze problems, choose the right approach, and evaluate the results. This course can help you build a foundation for a successful career as a Data Scientist.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning systems. They work closely with Data Scientists to ensure that these systems are accurate and reliable. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Machine Learning Engineer. You will learn how to build machine learning models, train them on data, and deploy them in production. This course can help you build a foundation for a successful career as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Software Engineer

Software Engineers design, develop, and maintain software systems. They work on a variety of projects, from small websites to large enterprise applications. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Software Engineer. You will learn how to design and implement software systems that are reliable, scalable, and efficient. This course can help you build a foundation for a successful career as a Software Engineer.

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Data Analyst

Data Analysts use data to solve business problems. They work with Data Scientists to identify trends and patterns in data, and they develop visualizations and reports to communicate their findings. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Data Analyst. You will learn how to analyze data, identify trends and patterns, and communicate your findings effectively. This course can help you build a foundation for a successful career as a Data Analyst.

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Business Analyst

Business Analysts work with businesses to identify and solve problems. They use their knowledge of business processes and technology to develop solutions that improve efficiency and profitability. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Business Analyst. You will learn how to analyze business problems, identify solutions, and develop implementation plans. This course can help you build a foundation for a successful career as a Business Analyst.

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Project Manager

Project Managers plan, execute, and close projects. They work with teams of people to achieve project goals on time and within budget. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Project Manager. You will learn how to plan and execute projects, manage teams, and communicate with stakeholders. This course can help you build a foundation for a successful career as a Project Manager.

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Product Manager

Product Managers work with teams to develop and launch new products. They work with engineers, designers, and marketers to ensure that products meet the needs of customers. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Product Manager. You will learn how to define product requirements, develop product roadmaps, and launch new products. This course can help you build a foundation for a successful career as a Product Manager.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve complex problems. They work with businesses to improve efficiency, reduce costs, and make better decisions. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Operations Research Analyst. You will learn how to use mathematical and analytical techniques to solve problems, and you will develop the skills needed to communicate your findings to decision makers. This course can help you build a foundation for a successful career as an Operations Research Analyst.

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Financial Analyst

Financial Analysts use financial data to make investment decisions. They work with companies to analyze their financial performance and make recommendations on how to improve it. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Financial Analyst. You will learn how to analyze financial data, make investment decisions, and communicate your findings to clients. This course can help you build a foundation for a successful career as a Financial Analyst.

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Market Research Analyst

Market Research Analysts conduct research to understand consumer behavior and trends. They work with businesses to develop marketing campaigns and strategies that reach their target audience. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Market Research Analyst. You will learn how to conduct research, analyze data, and make recommendations on marketing campaigns and strategies. This course can help you build a foundation for a successful career as a Market Research Analyst.

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Human Factors Engineer

Human Factors Engineers design products and systems that are easy to use and safe. They work with engineers, designers, and psychologists to ensure that products meet the needs of users. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Human Factors Engineer. You will learn how to design products and systems that are easy to use and safe, and you will develop the skills needed to evaluate the usability of products and systems. This course can help you build a foundation for a successful career as a Human Factors Engineer.

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Ergonomist

Ergonomists design workplaces and products that are comfortable and safe for workers. They work with engineers, designers, and safety professionals to ensure that workplaces meet the needs of workers. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Ergonomist. You will learn how to design workplaces and products that are comfortable and safe, and you will develop the skills needed to evaluate the ergonomics of workplaces and products. This course can help you build a foundation for a successful career as an Ergonomist.

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Technical Writer

Technical Writers create documentation for technical products and systems. They work with engineers and other technical professionals to ensure that documentation is accurate and easy to understand. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Technical Writer. You will learn how to write clear and concise documentation, and you will develop the skills needed to work with engineers and other technical professionals. This course can help you build a foundation for a successful career as a Technical Writer.

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Instructional Designer

Instructional Designers design and develop educational programs and materials. They work with teachers and other educators to ensure that programs and materials are effective and engaging. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful Instructional Designer. You will learn how to design and develop educational programs and materials, and you will develop the skills needed to work with teachers and other educators. This course can help you build a foundation for a successful career as an Instructional Designer.

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User Experience Designer

User Experience Designers design products and systems that are easy to use and enjoyable. They work with engineers, designers, and other professionals to ensure that products and systems meet the needs of users. Machine Teaching for Autonomous AI can help you develop the skills needed to be a successful User Experience Designer. You will learn how to design products and systems that are easy to use and enjoyable, and you will develop the skills needed to evaluate the user experience of products and systems. This course can help you build a foundation for a successful career as a User Experience Designer.

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