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Juan Vergara, John Alexander, and Kence Anderson
Practice makes perfect. It’s true for people learning to master a new skill, and it’s also true for your AI brain. Just as you need the right environment to practice, get feedback and try again, so does your AI brain. In this course, you’ll solve industrial engineering problems inspired by real problems your instructors have worked on in industry. You’ll learn how to build, test and deploy an AI brain using Microsoft Bonsai, a cloud-based, low-code platform. We’ll walk through the entire Bonsai platform from setup to deployment. Along the way, you’ll use Bonsai to conduct machine teaching experimentation to train a brain and...
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Practice makes perfect. It’s true for people learning to master a new skill, and it’s also true for your AI brain. Just as you need the right environment to practice, get feedback and try again, so does your AI brain. In this course, you’ll solve industrial engineering problems inspired by real problems your instructors have worked on in industry. You’ll learn how to build, test and deploy an AI brain using Microsoft Bonsai, a cloud-based, low-code platform. We’ll walk through the entire Bonsai platform from setup to deployment. Along the way, you’ll use Bonsai to conduct machine teaching experimentation to train a brain and assess its progress. Because you’ll be teaching the brain a relatively complex task, you’ll run multiple simulations until you’re satisfied with the results. You’ll then prep the brain for graduation into the real world — deploying it into a machinery control system or other live environment. At the end of this course, you’ll be able to: • Build an autonomous AI that combines reinforcement learning with machine learning, expert rules and other methods that you’ve used in the first two courses of the specialization •  Establish requirements for a simulated environment for your brain to practice a task •  Validate and assess your brain’s performance of a task and make improvements to your brain design • Evaluate whether a simulator is a good practice environment • Deploy a brain on a real piece of hardware This course requires an Azure subscription. This course is part of a specialization called Autonomous AI for Industry.
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Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Suitable for learners who seek to develop their autonomous AI skills
Introduces reinforcement learning, machine learning, expert rules, and other specialized AI techniques
Provides hands-on experience in building, testing, and deploying AI solutions using Microsoft Bonsai
Suitable for individuals with some background in AI or related fields
Requires an Azure subscription, which may involve additional costs
Taught by experienced instructors with industry experience in industrial engineering

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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 Building Autonomous AI with these activities:
Compile and organize course materials
Organize your course materials for easy access and efficient learning, establishing a solid foundation for success.
Show steps
  • Gather all course handouts and notes
  • Organize materials into folders and subfolders
  • Create a study schedule and stick to it
Refresh your programming skills before the course
Ensure a strong foundation by refreshing your programming skills, enhancing your ability to understand and implement AI concepts.
Browse courses on Programming Fundamentals
Show steps
  • Review basic programming concepts
  • Practice solving coding problems
  • Complete a short programming course or tutorial
Follow Bonsai documentation and tutorials
Expand your knowledge of Bonsai by exploring its documentation and tutorials, enhancing your understanding of its features and capabilities.
Show steps
  • Read the Bonsai documentation
  • Complete the Bonsai tutorials
  • Experiment with different Bonsai features
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice using Bonsai to build and test simple AI brains
Practice using Bonsai's features to build and test simple AI brains, reinforcing your understanding of the platform's capabilities.
Show steps
  • Create a Bonsai workspace and project
  • Import the provided training data
  • Design and build an AI brain
  • Test the AI brain using simulations
  • Iteratively refine the AI brain based on test results
Create a simple AI brain for a specific industrial engineering problem
Apply your skills to a practical project, building an AI brain for a specific industrial engineering problem, reinforcing your understanding of the problem-solving process.
Browse courses on Industrial Engineering
Show steps
  • Identify a specific industrial engineering problem
  • Design an AI brain to solve the problem
  • Implement the AI brain using Bonsai
  • Evaluate the performance of the AI brain
  • Document your work
Start a personal project using Bonsai
Embark on a personal project that utilizes Bonsai, deepening your understanding and skills in AI development.
Show steps
  • Define the scope of your project
  • Gather the necessary resources
  • Build and test your AI brain
  • Deploy your AI brain
Mentor junior students or colleagues in AI development
Share your knowledge and expertise by mentoring others, solidifying your understanding of AI concepts.
Show steps
  • Identify individuals who would benefit from your mentorship
  • Structure a mentorship program
  • Provide guidance and support to your mentees
  • Evaluate the progress of your mentees

Career center

Learners who complete Building Autonomous AI will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
A Machine Learning Engineer builds and deploys machine learning models to solve complex problems in various industries. The Building Autonomous AI course provides a solid foundation in AI and machine learning concepts, enabling you to design, develop, and deploy your own AI solutions. Furthermore, the course's focus on real-world problems prepares you to tackle challenges faced in the industry.
Autonomous Vehicle Engineer
Autonomous Vehicle Engineers design and develop self-driving cars. The Building Autonomous AI course provides you with a comprehensive understanding of AI and machine learning techniques used in autonomous vehicles. The course also covers the challenges and considerations in deploying and testing autonomous vehicles.
Data Scientist
Data Scientists analyze and interpret data to extract insights and make predictions. The Building Autonomous AI course equips you with the skills to apply machine learning and AI techniques to large datasets, helping you become a more effective Data Scientist. The course's focus on practical, industry-inspired problems will provide you with a competitive edge in the job market.
AI Research Scientist
AI Research Scientists conduct research and develop new AI algorithms and techniques. The Building Autonomous AI course provides a solid foundation in AI fundamentals, enabling you to contribute to the advancement of AI technology. The course's focus on practical, real-world problems will help you translate your research into industry applications.
Industrial Engineer
Industrial Engineers optimize processes and systems in various industries. The Building Autonomous AI course provides you with the knowledge to apply AI and machine learning techniques to industrial applications. The course's focus on real-world problems will help you design and implement innovative solutions for industry challenges.
Software Engineer
Software Engineers design, develop, and maintain software applications. The Building Autonomous AI course provides you with an overview of AI and machine learning principles, enabling you to incorporate these technologies into your software development projects. The course also covers the process of deploying AI models, which is essential for Software Engineers working on AI-powered applications.
Control Systems Engineer
Control Systems Engineers design and maintain systems that control physical processes. The Building Autonomous AI course provides you with the skills to develop and deploy AI-based control systems. The course covers techniques for modeling, simulation, and optimization, which are essential for Control Systems Engineers working on complex systems.
Robotics Engineer
Robotics Engineers design, build, and maintain robots. The Building Autonomous AI course provides you with the skills to develop autonomous robots capable of performing complex tasks. The course's emphasis on simulation and deployment prepares you for real-world challenges in robotics.
Business Analyst
Business Analysts analyze business processes and identify opportunities for improvement. The Building Autonomous AI course may be useful for Business Analysts who want to understand how AI and machine learning can be used to optimize business processes. The course will provide you with the knowledge to evaluate AI solutions and make recommendations based on business needs.
Product Manager
Product Managers plan and manage the development and launch of new products. The Building Autonomous AI course may be useful for Product Managers who want to understand the potential of AI and machine learning in product development. The course will provide you with insights into the design and implementation of AI-powered products.
Data Analyst
Data Analysts collect, analyze, and interpret data to solve business problems. The Building Autonomous AI course may be useful for Data Analysts who want to specialize in AI and machine learning. The course will provide you with the skills to apply AI and machine learning techniques to data analysis and extract valuable insights.
Consultant
Consultants advise businesses and organizations on how to improve their operations. The Building Autonomous AI course may be useful for Consultants who want to specialize in AI and machine learning consulting. The course will provide you with the knowledge to understand the potential of AI and machine learning and advise clients on how to implement it successfully.
Project Manager
Project Managers plan and execute projects, ensuring their successful completion. The Building Autonomous AI course may be useful for Project Managers who want to lead AI and machine learning projects. The course will provide you with the knowledge to understand the technical aspects of AI projects and manage them effectively.
Technical Writer
Technical Writers create and maintain documentation for technical products and systems. The Building Autonomous AI course may be useful for Technical Writers who want to specialize in documenting AI and machine learning systems. The course will provide you with the knowledge to understand the technical concepts and communicate them effectively.
System Analyst
System Analysts analyze and design computer systems. The Building Autonomous AI course may be useful for System Analysts who want to specialize in AI and machine learning systems. The course will provide you with the knowledge to understand the technical concepts and design AI-powered systems.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Building Autonomous AI.
Classic introduction to reinforcement learning, providing a comprehensive overview of the field's theory and algorithms. It's essential reading for anyone looking to build autonomous AI systems.
Provides a comprehensive overview of simulation modeling and analysis, including topics such as model building, data collection, and analysis. It's a valuable resource for anyone looking to build and deploy autonomous AI systems in simulated environments.
Provides a comprehensive overview of building autonomous agents, including topics such as planning, learning, and communication. It's a useful reference for anyone looking to build autonomous AI systems that can operate in complex environments.
Provides a comprehensive overview of deep learning, including topics such as neural networks, convolutional neural networks, and recurrent neural networks. It's a valuable resource for anyone looking to build autonomous AI systems that can learn from data.
Provides a comprehensive overview of probabilistic robotics, including topics such as localization, mapping, and planning. It's a valuable resource for anyone looking to build autonomous AI systems that can operate in uncertain environments.
Provides a comprehensive overview of computer vision, including topics such as image processing, object detection, and scene understanding. It's a valuable resource for anyone looking to build autonomous AI systems that can see and interpret the world around them.
Provides a comprehensive overview of natural language processing, including topics such as tokenization, parsing, and machine translation. It's a valuable resource for anyone looking to build autonomous AI systems that can understand and generate human language.
Provides a comprehensive overview of speech and language processing, including topics such as speech recognition, natural language understanding, and dialogue systems. It's a valuable resource for anyone looking to build autonomous AI systems that can communicate with humans.
Provides a comprehensive overview of machine learning, including topics such as supervised learning, unsupervised learning, and reinforcement learning. It's a valuable resource for anyone looking to gain a deeper understanding of the field.
Provides a comprehensive overview of deep learning with Python, including topics such as neural networks, convolutional neural networks, and recurrent neural networks. It's a valuable resource for anyone looking to build autonomous AI systems that can learn from data.
Provides a comprehensive overview of computer vision with OpenCV, including topics such as image processing, object detection, and scene understanding. It's a valuable resource for anyone looking to build autonomous AI systems that can see and interpret the world around them.
Provides a comprehensive overview of natural language processing with NLTK, including topics such as tokenization, parsing, and machine translation. It's a valuable resource for anyone looking to build autonomous AI systems that can understand and generate human language.

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