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Avkash Chauhan
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What's inside
Syllabus
In this lesson, you will learn why computer vision is important, among other foundational topics. You will get an overview of what we will cover in this course.
Read more
Syllabus
In this lesson, you will learn why computer vision is important, among other foundational topics. You will get an overview of what we will cover in this course.
Read more
In this lesson, you will learn about the business and technical considerations of computer vision applications and solutions. This lesson provides the fundamentals for you to get started.
In this lesson, you will apply computer vision technology to extract text from various kinds of digital images & documents using specialized Azure Cognitive Services.
In this lesson, you will learn how to apply face detection and facial recognition using various Azure Face APIs. You can easily get started with little to no deep learning knowledge.
The best business use cases of AI are in image classification and object detection solutions, and this lesson gives you a head start on how to implement these with the Azure Custom Vision service.
Object Detection & Spatial Analysis
This lesson provides the operational knowledge on how to deploy and manage your computer vision solutions at Azure to make sure they are running smoothly to produce results.
In this project, you will build an automated passenger boarding kiosk. Your objective will be to perform various validation processes and confirm if a given passenger can board the plane or not.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides an introduction to computer vision concepts, technologies, and applications, making it suitable for learners new to the field
Emphasizes business applications of computer vision, helping learners understand the practical value of these technologies
Involves hands-on labs and interactive materials, reinforcing the practical aspects of computer vision
Utilizes Azure Cognitive Services and APIs, which are industry-standard tools for computer vision
Focuses on building end-to-end computer vision solutions, including deployment and management
Provides a starting point for beginners looking to explore computer vision and its applications
Taught by Avkash Chauhan, who has experience in applying computer vision technologies to business problems
Save this course
Save Building Computer Vision Solutions with Azure to your list so you can find it easily later:
Save
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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 Computer Vision Solutions with Azure with these
activities:
Review computer vision concepts
Show steps
Refresh your knowledge of basic computer vision concepts and techniques, such as image processing, feature extraction, and object recognition, to strengthen your foundation for the course.
Browse courses on
Computer Vision
Show steps
-
Review textbook chapters or online resources on computer vision fundamentals.
-
Work through practice problems or exercises to reinforce your understanding.
Participate in peer code review sessions
Show steps
Enhance your learning by participating in peer code review sessions. This will allow you to provide and receive feedback on your code, improving its quality and your understanding.
Browse courses on
Collaborative Learning
Show steps
-
Find a study partner or group who is also taking the course.
-
Set up regular meetings to review each other's code.
-
Provide constructive feedback and suggestions for improvement.
Explore Azure Cognitive Services tutorials
Show steps
Enhance your understanding of Azure Cognitive Services for computer vision by following guided tutorials provided by Microsoft or the community to gain hands-on experience with the platform.
Browse courses on
Azure Cognitive Services
Show steps
-
Choose a tutorial that aligns with your interests or learning goals.
-
Follow the instructions and complete the exercises in the tutorial.
-
Troubleshoot any issues you encounter during the tutorial.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice image annotation and labeling
Show steps
Sharpen your skills in image annotation and labeling by working on practice datasets. This will enhance your ability to prepare training data for computer vision models.
Show steps
-
Find a dataset that aligns with your interests or project needs.
-
Annotate and label images according to the dataset guidelines.
-
Review your annotations and make corrections as needed.
Mentor junior students or peers
Show steps
Reinforce your understanding by mentoring junior students or peers. This will allow you to explain concepts and provide guidance, deepening your own knowledge and solidifying your skills.
Browse courses on
Mentoring
Show steps
-
Reach out to junior students or peers who need assistance.
-
Provide guidance on course concepts and assignments.
-
Offer support and encouragement to help them succeed.
Develop a prototype computer vision solution
Show steps
Apply your knowledge by creating a prototype computer vision solution that addresses a real-world problem. This will allow you to practice the entire development lifecycle, from ideation to implementation.
Browse courses on
Prototype Development
Show steps
-
Identify a problem or challenge that can be solved using computer vision.
-
Design a solution architecture and select appropriate Azure services.
-
Develop and implement the prototype.
-
Test and evaluate the prototype.
Participate in computer vision competitions
Show steps
Challenge yourself and gain practical experience by participating in computer vision competitions. This will expose you to real-world problems and help you develop your skills in a competitive environment.
Browse courses on
Kaggle
Show steps
-
Identify a relevant competition that aligns with your interests.
-
Form a team or work individually.
-
Develop and submit your solution to the competition.
Review computer vision concepts
Show steps
Refresh your knowledge of basic computer vision concepts and techniques, such as image processing, feature extraction, and object recognition, to strengthen your foundation for the course.
Browse courses on
Computer Vision
Show steps
Show steps
Show steps
- Review textbook chapters or online resources on computer vision fundamentals.
- Work through practice problems or exercises to reinforce your understanding.
Participate in peer code review sessions
Show steps
Enhance your learning by participating in peer code review sessions. This will allow you to provide and receive feedback on your code, improving its quality and your understanding.
Browse courses on
Collaborative Learning
Show steps
Show steps
Show steps
- Find a study partner or group who is also taking the course.
- Set up regular meetings to review each other's code.
- Provide constructive feedback and suggestions for improvement.
Explore Azure Cognitive Services tutorials
Show steps
Enhance your understanding of Azure Cognitive Services for computer vision by following guided tutorials provided by Microsoft or the community to gain hands-on experience with the platform.
Browse courses on
Azure Cognitive Services
Show steps
Show steps
Show steps
- Choose a tutorial that aligns with your interests or learning goals.
- Follow the instructions and complete the exercises in the tutorial.
- Troubleshoot any issues you encounter during the tutorial.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice image annotation and labeling
Show steps
Sharpen your skills in image annotation and labeling by working on practice datasets. This will enhance your ability to prepare training data for computer vision models.
Show steps
Show steps
Show steps
- Find a dataset that aligns with your interests or project needs.
- Annotate and label images according to the dataset guidelines.
- Review your annotations and make corrections as needed.
Mentor junior students or peers
Show steps
Reinforce your understanding by mentoring junior students or peers. This will allow you to explain concepts and provide guidance, deepening your own knowledge and solidifying your skills.
Browse courses on
Mentoring
Show steps
Show steps
Show steps
- Reach out to junior students or peers who need assistance.
- Provide guidance on course concepts and assignments.
- Offer support and encouragement to help them succeed.
Develop a prototype computer vision solution
Show steps
Apply your knowledge by creating a prototype computer vision solution that addresses a real-world problem. This will allow you to practice the entire development lifecycle, from ideation to implementation.
Browse courses on
Prototype Development
Show steps
Show steps
Show steps
- Identify a problem or challenge that can be solved using computer vision.
- Design a solution architecture and select appropriate Azure services.
- Develop and implement the prototype.
- Test and evaluate the prototype.
Participate in computer vision competitions
Show steps
Challenge yourself and gain practical experience by participating in computer vision competitions. This will expose you to real-world problems and help you develop your skills in a competitive environment.
Browse courses on
Kaggle
Show steps
Show steps
Show steps
- Identify a relevant competition that aligns with your interests.
- Form a team or work individually.
- Develop and submit your solution to the competition.
Career center
Learners who complete Building Computer Vision Solutions with Azure will develop knowledge and skills
that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineer
A Computer Vision Engineer designs, develops, and maintains computer vision systems. This course may be useful for career advancement by providing advanced knowledge and skills in computer vision algorithms, image processing, and deep learning for computer vision.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
An Artificial Intelligence Engineer designs, develops, and deploys AI systems. This course may provide a solid foundation by covering fundamental concepts of computer vision, machine learning, and deep learning, all of which are essential for a successful career as an Artificial Intelligence Engineer.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, builds, and deploys machine learning models to solve real-world problems. This course may be beneficial by providing training in computer vision, machine learning algorithms, and data analysis, all of which are essential skills for a Machine Learning Engineer.
Robotics Engineer
Robotics Engineer
A Robotics Engineer designs, builds, and maintains robots. This course may be helpful by providing knowledge in computer vision, which is essential for robot navigation, object recognition, and obstacle avoidance.
Healthcare Analyst
Healthcare Analyst
A Healthcare Analyst uses data and analytics to improve patient care and healthcare outcomes. This course may be helpful by providing an understanding of computer vision and how it can be used in healthcare applications, such as medical image analysis and disease diagnosis.
Data Analyst
Data Analyst
A Data Analyst collects, interprets, and presents data to help organizations make informed decisions. This course may be useful by providing a solid understanding of computer vision, data analysis techniques, and data visualization, which are valuable skills for a Data Analyst.
Software Engineer
Software Engineer
A Software Engineer designs, builds, deploys, and maintains software solutions and computer applications. This course may help build a strong foundation for this career by providing knowledge and training in problem-solving, developing software applications, and understanding computer vision technology.
Cloud Architect
Cloud Architect
A Cloud Architect designs, builds, and maintains cloud computing solutions. This course may be useful in understanding how to leverage cloud computing services, such as Azure, to implement computer vision solutions.
Data Scientist
Data Scientist
A Data Scientist helps organizations extract actionable insights from vast amounts of data. This course may be useful for those seeking a career as a Data Scientist by providing training in computer vision, data analysis, and machine learning algorithms.
Business Analyst
Business Analyst
A Business Analyst analyzes business processes and identifies opportunities for improvement. This course may be useful by providing an understanding of how computer vision can be used to solve business problems and improve operational efficiency.
Consultant
Consultant
A Consultant provides expert advice and guidance to clients on a variety of topics. This course may be useful for those seeking a career as a Consultant by providing knowledge of computer vision and how it can be applied to solve business problems.
Product Manager
Product Manager
A Product Manager defines and manages the product roadmap to meet customer needs. This course may be beneficial by providing knowledge of computer vision applications and how they can be integrated into products.
UX Designer
UX Designer
A UX Designer creates user interfaces that are both functional and visually appealing. This course may be beneficial by providing knowledge of computer vision and how it can be used to create innovative and user-friendly designs.
Project Manager
Project Manager
A Project Manager plans, executes, and closes projects. This course may be helpful by providing knowledge of computer vision and how it can be used to streamline project management processes and improve project outcomes.
Technical Writer
Technical Writer
A Technical Writer creates and maintains technical documentation. This course may be beneficial by providing knowledge of computer vision and how to effectively communicate complex technical concepts.
For more career information including salaries, visit:
OpenCourser.com/course/99yzrx/building
Reading list
We've selected five 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 Computer Vision Solutions with Azure.
Provides a comprehensive overview of computer vision algorithms and techniques, with a focus on theoretical foundations and practical applications.
Save
Provides a comprehensive overview of computer vision algorithms and techniques, with a focus on image processing, object recognition, and image understanding.
Provides a comprehensive overview of digital image processing techniques, with a focus on image enhancement, restoration, and analysis.
Provides a practical introduction to computer vision using Python and the OpenCV library.
Provides a practical introduction to computer vision using Python, with a focus on image processing, object recognition, and image understanding.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/99yzrx/building
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Effort
4 weeks
Via
Udacity
Instructor
Avkash Chauhan
Language
English
Good to know
Provides an introduction to computer vision concepts, technologies, and applications, making it suitable for learners new to the field
Emphasizes business applications of computer vision, helping learners understand the practical value of these technologies
Involves hands-on labs and interactive materials, reinforcing the practical aspects of computer vision
Utilizes Azure Cognitive Services and APIs, which are industry-standard tools for computer vision
Focuses on building end-to-end computer vision solutions, including deployment and management
Provides a starting point for beginners looking to explore computer vision and its applications
Taught by Avkash Chauhan, who has experience in applying computer vision technologies to business problems
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