Semantic Segmentation with Amazon Sagemaker from Coursera

Please note: You will need an AWS account to complete this course. Your AWS account will be charged as per your usage. Please make sure that you are able to access Sagemaker within your AWS account. If your AWS account is new, you may need to ask AWS support for access to certain resources. You should be familiar with python programming, and AWS before starting this hands on project. We use a Sagemaker P type instance in this project, and if you don't have access to this instance type, please contact AWS support and request access.

In this 2-hour long project-based course, you will learn how to train and deploy a Semantic Segmentation model using Amazon Sagemaker. Sagemaker provides a number of machine learning algorithms ready to be used for solving a number of tasks. We will use the semantic segmentation algorithm from Sagemaker to create, train and deploy a model that will be able to segment images of dogs and cats from the popular IIIT-Oxford Pets Dataset into 3 unique pixel values. That is, each pixel of an input image would be classified as either foreground (pet), background (not a pet), or unclassified (transition between foreground and background).

Since this is a practical, project-based course, we will not dive in the theory behind deep learning based semantic segmentation, but will focus purely on training and deploying a model with Sagemaker. You will also need to have some experience with Amazon Web Services (AWS).

What's inside

Syllabus

Semantic Segmentation with Amazon Sagemaker

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Examines semantic segmentation, which is indispensable to image and object recognition

Leverages the robust capabilities of Amazon Sagemaker

Taught by Amit Yadav, who is recognized for their expertise in computer vision

Develops practical, applicable skills in semantic segmentation

Tailored for learners with experience in Python programming and AWS

Reviews summary

Sagemaker semantic segmentation

According to students, Semantic Segmentation with Amazon Sagemaker is a popular course, especially for those new to using Sagemaker. Students praise the course for its well-organized content, step-by-step instructions, and practical projects. While the course may be challenging for those without prior programming experience, students who complete it feel prepared to use Sagemaker for their own projects.

Good introduction to Sagemaker for those new to the platform.

"I found the project to be a great step-by-step introduction to using notebooks within sagemaker in order to orchestrate training/deployment jobs!"

Projects provide hands-on experience with Sagemaker.

"better experience"

May be challenging for those without programming experience.

"I am not very happy with this course."

"The instructor just rushes through some inside his formerly prepared jupyter notebook and his explanations on the actual code snippets are very short and not very understandable."

"Information given is not complete"

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 Semantic Segmentation with Amazon Sagemaker with these activities:

Read the book 'Deep Learning for Computer Vision' by Jason Brownlee

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This will provide you with a comprehensive understanding of deep learning for computer vision, including semantic segmentation.

View Concurrent NumPy in Python: Faster NumPy With... on Amazon

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Obtain a copy of the book.
Read the book thoroughly, taking notes and highlighting important sections.
Complete the exercises and activities in the book.

Find a mentor who can provide guidance on semantic segmentation

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This will help you connect with experts in the field and gain valuable insights.

Browse courses on Amazon SageMaker

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Identify potential mentors through online forums, professional networking sites, or research institutions.
Reach out to potential mentors and express your interest in their mentorship.
Schedule a meeting to discuss your goals and expectations.

Review Python programming fundamentals

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This will help you review the basics of Python, including data types, control flow, and functions.

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Go through an online Python tutorial or course.
Review your notes from previous Python courses or projects.
Solve some basic Python coding challenges.

Five other activities

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Follow a tutorial on using Amazon Sagemaker for semantic segmentation

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This will help you gain hands-on experience with using Sagemaker for semantic segmentation.

Browse courses on Amazon SageMaker

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Find a tutorial on the official Amazon Sagemaker website or other reputable sources.
Follow the tutorial step-by-step, completing all the exercises and activities.
Make sure to understand the concepts and techniques used in the tutorial.

Solve semantic segmentation problems on LeetCode or Kaggle

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This will help you develop your problem-solving and coding skills in semantic segmentation.

Browse courses on Amazon SageMaker

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Create an account on LeetCode or Kaggle.
Find semantic segmentation problems to solve.
Implement your solutions using Python and the Sagemaker Python SDK.
Submit your solutions and review your performance.

Mentor other students in this course

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This will help you reinforce your understanding of the course material and develop your communication and mentoring skills.

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Join a study group or online forum for the course.
Offer to help other students with their understanding of the material.
Answer questions and provide guidance to other students.
Share your knowledge and experience with others.

Create a sample semantic segmentation project using Amazon Sagemaker

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This will allow you to apply the skills you learned in the course to a practical project.

Browse courses on Amazon SageMaker

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Choose a dataset for semantic segmentation, such as the IIIT-Oxford Pets Dataset.
Create a Sagemaker notebook instance.
Use the Sagemaker Python SDK to train and deploy a semantic segmentation model.
Evaluate the performance of your model.
Write a report summarizing your project and findings.

Participate in a semantic segmentation competition

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This will challenge you to apply your skills in a competitive environment and learn from others.

Browse courses on Amazon SageMaker

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Find a semantic segmentation competition that is relevant to your interests.
Gather a team of participants.
Develop a strategy for solving the competition problem.
Implement your solution using Amazon Sagemaker and other relevant tools.
Submit your solution to the competition.

Career center

Learners who complete Semantic Segmentation with Amazon Sagemaker will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers design, implement, and evaluate machine learning models to solve real-world problems. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use data to solve business problems. They collect, clean, analyze, and interpret data to identify trends and patterns. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Data Scientist

Computer Vision Engineer

Computer Vision Engineers develop and implement algorithms that allow computers to see and understand images and videos. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Computer Vision Engineer

Software Engineer

Software Engineers design, develop, and maintain software systems. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Software Engineer

Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Data Analyst

Product Manager

Product Managers are responsible for the development and success of a product. They work with engineers, designers, and marketers to bring a product to market. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Product Manager

Business Analyst

Business Analysts help businesses to identify and solve problems. They use data and analysis to identify opportunities and risks. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Business Analyst

Project Manager

Project Managers are responsible for planning, executing, and closing projects. They work with stakeholders to ensure that projects are completed on time, within budget, and to the desired specifications. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Project Manager

UX Designer

UX Designers design and evaluate user experiences. They work with engineers and product managers to create products that are easy to use and enjoyable to interact with. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for UX Designer

Marketing Manager

Marketing Managers are responsible for planning and executing marketing campaigns. They work with marketing teams to create and implement marketing strategies. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Marketing Manager

Sales Manager

Sales Managers are responsible for leading and managing sales teams. They work with sales teams to develop and implement sales strategies. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Sales Manager

Customer Success Manager

Customer Success Managers are responsible for ensuring that customers are satisfied with their products and services. They work with customers to resolve issues and provide support. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Customer Success Manager

Technical Writer

Technical Writers create and edit technical documentation. They work with engineers and product managers to create documentation that is easy to understand and use. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Technical Writer

Quality Assurance Analyst

Quality Assurance Analysts test and evaluate software products. They work with developers to identify and fix bugs. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for Quality Assurance Analyst

IT Support Specialist

IT Support Specialists provide technical support to users. They help users to troubleshoot and resolve technical issues. This course provides a foundation in semantic segmentation, a type of machine learning model that can be used to identify and segment objects in images. By taking this course, you will gain the skills and knowledge necessary to build and deploy your own semantic segmentation models, which can be used in a variety of applications, such as image segmentation, object detection, and medical imaging.

See salaries and explore the career path for IT Support Specialist

Semantic Segmentation with Amazon Sagemaker

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Reviews summary

Sagemaker semantic segmentation

Activities

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