This course is part of the Autonomous AI for Industry Specialization

Kence Anderson

Offered By

Autonomous AI for Industry SpecializationUniversity of Washington

About this Course

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When children learn how to hit a baseball, they don’t start with fastballs. Their coaches begin with the basics: how to grip the handle of the bat, where to put their feet and how to keep their eyes on the ball. Similarly, an autonomous AI system needs a subject matter expert (SME) to break a complex process or problem into easier tasks that give the AI important clues about how to find a solution faster.  
In this course, you’ll learn how to distill a business challenge into its component parts by creating an autonomous AI design plan. Using lessons, goal setting, skills, strategies and rewards, you’ll incorporate your SME’s knowledge directly into your AI’s “brain,” the agent that powers your autonomous system. You'll learn when and how to combine various AI architecture design patterns, as well as how to design an advanced AI at the architectural level without worrying about the implementation of neural networks or machine learning algorithms. 

At the end of this course, you’ll be able to: 
•  Interview SMEs to extract their unique knowledge about a system or process  
•  Combine reinforcement learning with expert rules, optimization and mathematical calculations in an AI brain 
•  Design an autonomous AI brain from modular components to guide the learning process for a particular task 
•  Validate your brain design against existing expertise and techniques for solving problems 
•  Produce a detailed specifications document so that someone else can build your AI brain 

This course is part of a specialization called Autonomous AI for Industry.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 2 of 3 in the

Autonomous AI for Industry Specialization

Beginner Level

Familiarity with engineering concepts like robotics and manufacturing is helpful but not required. Coding experience is not needed.

Approx. 12 hours to complete

English

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What you will learn

You'll gain key AI terminology and understand how to teach and train AI.
You'll design your own original autonomous AI system.

Skills you will gain

Architecture Design Patterns
Simulated Environments
AI Brain Design
AI Brain Performance
Reinforcement Learning

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 2 of 3 in the

Autonomous AI for Industry Specialization

Beginner Level

Familiarity with engineering concepts like robotics and manufacturing is helpful but not required. Coding experience is not needed.

Approx. 12 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Kence Anderson

Director, Autonomous AI Adoption

Microsoft

3,958 Learners

3 Courses

Offered by

Microsoft

Our goal at Microsoft is to empower every individual and organization on the planet to achieve more.

In this next revolution of digital transformation, growth is being driven by technology. Our integrated cloud approach creates an unmatched platform for digital transformation. We address the real-world needs of customers by seamlessly integrating Microsoft 365, Dynamics 365, LinkedIn, GitHub, Microsoft Power Platform, and Azure to unlock business value for every organization—from large enterprises to family-run businesses. The backbone and foundation of this is Azure.

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Syllabus - What you will learn from this course

Week1

Week 1

3 hours to complete

Defining your AI

3 hours to complete

7 videos (Total 43 min), 5 readings, 3 quizzes

7 videos

0.1 - A glimpse ahead2m1.0 - Scenarios: The basis for learning6m1.1 - Actions: Sense, plan, act5m1.2 - Actions: String together into scenarios3m1.3 - Navigating Actions (Map analogy)5m1.4 - Real Autonomous AI Stories: Bell Flight4m1.5 - What are the goals of the brain?14m

5 readings

Real Autonomous AI10mThe Instructional Team5mAbout "Brain Design Challenge" the Honors track10mDiscussion | Introduce Yourself10mGlossary & Course Map10m

2 practice exercises

Practice Questions | Identifying Actions5mGraded Quiz | "Actions & Goals" Review30m

Week2

Week 2

4 hours to complete

Teaching Skills to your AI

Autonomous AI brains are built from skills. Skills are “units of competence for completing tasks that have sub-goals associated with them.” This week you'll learn to outline the skills you want your autonomous AI brain to learn. First, you’ll identify three different types of skills that you can build into your brains. Then, you’ll learn a strategy that will help easily extract and document skills from subject matter experts you interview. Along the way we’ll look at some design patterns that you can use as templates to start your use case brain designs.

4 hours to complete

7 videos (Total 55 min), 3 readings, 5 quizzes

7 videos

2.1 – Defining: Concepts, Skills, & Strategies7m2.2 – Matching Skills to Scenarios4m2.3 – (Fantastic) Skills: Perception, Action & Selector14m2.4 – "Heuristic Strategies" (Where to find them)13m2.5 – How goals relate to scenarios3m2.6 – Navigating by Landmarks (Goals)6m2.7 – Real Autonomous AI Stories: Tesla4m

3 readings

Example Use Case | Baggage ProcessingOptimization10m3 Basic Brain Design Patterns10mExample Use Case | Rail Yard Optimization10m

4 practice exercises

Practice Questions | Matching skills and strategies to scenarios30mPractice Questions | Setting good goal objectives for skills and strategies30mPractice Questions | Identifying: primary, secondary, and trade-off goals5mGraded Quiz | "Skills & Scenarios" Review30m

Week3

Week 3

2 hours to complete

Organizing Skills in your AI

Now that you understand how to interview a subject matter expert and lay out all the skills that you want your AI to practice, you need to organize those skills in the brain. In this module you’ll learn two organizing paradigms for skills in autonomous AI, and a three-step framework for completing this orchestration. This week you’ll see some brain design patterns for example use cases, to help you with thinking about organizing your own use case brain design.

2 hours to complete

5 videos (Total 49 min), 1 reading, 2 quizzes

Week4

Week 4

3 hours to complete

Putting it All Together

Now it's time to put it all together. You've defined your AI, you've identified a set of skills that you want to teach your AI and you've used brain design patterns in the paradigms of orchestration to snap those skills together in the right arrangement. There's a few pitfalls to orchestration that you should be aware of and you’ll have lots of opportunity to practice creating variations on brain designs for sample problems. Make sure to share your brain designs from the lab in the forum, so we can discuss them together and learn from each other.

3 hours to complete

4 videos (Total 39 min), 2 readings, 2 quizzes

About the Autonomous AI for Industry Specialization

Artificial intelligence (AI) is embedded in our daily life, from predictive text on our smart devices to the GPS that helps us navigate to a destination. But AI has been slower to transform industries that deal in tangible objects, like manufacturing and transportation. Yet there's enormous potential: Businesses can generate over $460 billion in incremental profit by integrating AI practices into their business operations, according to research from Infosys Knowledge Institute. This means there's immense opportunity to implement a successful model in your business. And this program will show you how.

This specialization offers a new approach to successfully using AI in industry — by applying machine teaching techniques to bring intelligence to autonomous systems and radically transforming and improving processes. Through machine teaching, subject matter experts in engineering and other disciplines infuse their skills and decision-making abilities, honed over years of experience, directly into the AI system. You’ll learn how to break a complex problem into individual skills and give your AI brain, the agent that powers your autonomous system, important clues about how to learn faster. By the end of the specialization, you’ll know how to build smarter, more agile control systems that can help your machinery and processes adapt in real time to changing conditions.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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