Image Classification 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.

Since this is a practical, project-based course, we will not dive in the theory behind deep learning based image classification, 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).

Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

What's inside

Syllabus

Image Classification with Amazon Sagemaker

In this 2-hour long project-based course, you will learn how to train and deploy an image classifier 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 image classification algorithm from Sagemaker to create, train and deploy a model that will be able to classify 37 breeds of dogs and cats from the popular IIIT-Oxford Pets Dataset. Since this is a practical, project-based course, we will not dive in the theory behind deep learning based image classification, 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).

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides hands-on experience with Sagemaker, a valuable platform for machine learning

Focuses on practical applications, allowing learners to immediately apply their newfound knowledge

Targets individuals with prior experience and knowledge in Python programming and AWS

Requires learners to have access to an AWS account and a specific P type instance, which may pose barriers for some

Exclusively available for learners based in the North America region, limiting accessibility for others

Reviews summary

Sagemaker image classification course

Students appreciate this well-structured beginner-friendly project-based course that covers image classification using AWS Sagemaker. Step-by-step guidance, easy-to-understand lectures, and a well-designed project make this course a well-received choice for those new to Sagemaker.

Great for new learners

"This course is very helpful for you to create a warmup code with AWS Sagemaker and image classification."

Hands on learning

"Good project based course"

Easy to follow

"very easy step by step guided project "

Lacks depth

"too simple, did not show the overall accuracy in validation test set and potential way to improve it"

Longer than advertised

"This is Not 2hr course. It's takes 24hr or more."

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 Image Classification with Amazon Sagemaker with these activities:

Review Scikit-Learn Tutorial

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Familiarize yourself with the basics of machine learning and supervised learning using Scikit-Learn, a popular Python library for machine learning.

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Read the official Scikit-Learn user guide or tutorials.
Follow along with a video or interactive tutorial on using Scikit-Learn.
Practice using Scikit-Learn on a simple dataset.

AWS Deep Learning Workshop

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Deepen your knowledge of AWS and Amazon SageMaker by attending a hands-on workshop tailored to machine learning and image classification.

Browse courses on AWS

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Locate and register for an AWS Deep Learning workshop.
Attend the workshop and actively participate in the exercises.
Ask questions and engage with the instructors and other participants.
Follow up with a small-scale project using Amazon SageMaker.

Deep Learning with Python

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Enhance your understanding of deep learning and Python by reading a comprehensive book that covers both theoretical concepts and practical applications.

View Deep Learning with TensorFlow and Keras - Third... on Amazon

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Read the book's chapters on image classification and neural networks.
Work through the practice exercises and examples provided in the book.
Apply the concepts to a small-scale image classification project.

Four other activities

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Create a Presentation on Image Classification

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Solidify your understanding of image classification by creating a presentation that explains the concepts, techniques, and applications of this field.

Browse courses on Image Classification

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Research and gather information on image classification.
Organize your material into a logical and visually appealing presentation.
Practice presenting your material and get feedback from others.

Kaggle Cat vs. Dog Image Classification

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Apply your image classification skills by participating in a Kaggle competition focused on classifying cats and dogs, a common introductory project for deep learning.

Browse courses on Image Classification

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Register for the Kaggle competition and download the dataset.
Train and evaluate a simple image classification model using a library like TensorFlow or PyTorch.
Submit your results to the competition and compare them with others.
Review the discussion forums and learn from other participants.

Deploy an Image Classifier

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Demonstrate your mastery of image classification by deploying a trained model as a web service or API, allowing you to classify images in real-time.

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Choose a deployment platform such as AWS Elastic Beanstalk or Google Cloud Run.
Prepare your model and code for deployment.
Deploy your model and configure the endpoint.
Test and evaluate the deployed model by sending image requests.

Build an Animal Classifier

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Test your skills and apply your knowledge by building a complete animal classifier using techniques covered in the course.

Browse courses on Image Classification

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Define the scope of your project (e.g., types of animals, size of dataset).
Gather and preprocess a dataset of animal images.
Train an image classification model using TensorFlow or PyTorch.
Evaluate the model's performance and make improvements as needed.
Create a user-friendly interface for your classifier.

Career center

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

Data Scientist

Data Scientists help advance their organizations by transforming data into insights. Their job is to analyze complex data with the help of machine learning solutions and build models that can make predictions or automate business processes. Some Data Scientists use Amazon SageMaker to quickly get started on building, training, and deploying machine learning models. This course can help build a foundation for individuals who wish to shift into a Data Science role.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers are responsible for the development and deployment of machine learning models. They work on the full lifecycle of a machine learning project, from data collection and preparation to model training and deployment. Amazon SageMaker helps accelerate the development and deployment of machine learning models. This course can help build a foundation for individuals who wish to shift into a Machine Learning Engineering role.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

Data Analysts use data to solve business problems. They collect, clean, and analyze data to identify trends and patterns. Data Analysts may use Amazon SageMaker to quickly get started on building, training, and deploying machine learning models. This course can help build a foundation for individuals who wish to shift into a Data Analyst role.

See salaries and explore the career path for Data Analyst

Software Engineer

Software Engineers design, develop, and maintain software applications. They may use Amazon SageMaker to quickly get started on building, training, and deploying machine learning models. This course can help build a foundation for individuals who work as Software Engineers and wish to add machine learning into their skillset.

See salaries and explore the career path for Software Engineer

Business Analyst

Business Analysts help organizations improve their performance by analyzing data and identifying opportunities for improvement. They may use Amazon SageMaker to quickly get started on building, training, and deploying machine learning models. This course can help build a foundation for individuals who work as Business Analysts and wish to add machine learning into their skillset to stay ahead in their field.

See salaries and explore the career path for Business Analyst

Product Manager

Product Managers are responsible for the development and launch of new products. They work with engineers, designers, and marketers to bring new products to market. Amazon SageMaker can help Product Managers quickly get started on building, training, and deploying machine learning models to improve their products. This course can help build a foundation for individuals who work as Product Managers and wish to add machine learning into their skillset to stay ahead in their field.

See salaries and explore the career path for Product Manager

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. They may use Amazon SageMaker to quickly get started on building, training, and deploying machine learning models. This course can help build a foundation for individuals who work as Quantitative Analysts and wish to add machine learning into their skillset.

See salaries and explore the career path for Quantitative Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve business problems. They may use Amazon SageMaker to quickly get started on building, training, and deploying machine learning models. This course can help build a foundation for individuals who work as Operations Research Analysts and wish to add machine learning into their skillset.

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Statistician

Statisticians collect, analyze, and interpret data. They may use Amazon SageMaker to quickly get started on building, training, and deploying machine learning models. This course can help build a foundation for individuals who work as Statisticians and wish to add machine learning into their skillset.

See salaries and explore the career path for Statistician

Data Engineer

Data Engineers design, build, and maintain data pipelines. They may use Amazon SageMaker to quickly get started on building, training, and deploying machine learning models. This course can help build a foundation for individuals who work as Data Engineers and wish to add machine learning into their skillset.

See salaries and explore the career path for Data Engineer

Computer Vision Engineer

Computer Vision Engineers develop and implement computer vision algorithms and systems. They may use Amazon SageMaker to quickly get started on building, training, and deploying machine learning models for computer vision tasks. This course can help build a foundation for individuals who wish to shift into a Computer Vision Engineering role.

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Artificial Intelligence Engineer

Artificial Intelligence Engineers design, develop, and implement artificial intelligence systems. They may use Amazon SageMaker to quickly get started on building, training, and deploying machine learning models for artificial intelligence tasks. This course can help build a foundation for individuals who wish to shift into an Artificial Intelligence Engineering role.

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Deep Learning Engineer

Deep Learning Engineers design, develop, and implement deep learning models. They may use Amazon SageMaker to quickly get started on building, training, and deploying machine learning models for deep learning tasks. This course can help build a foundation for individuals who wish to shift into a Deep Learning Engineering role.

See salaries and explore the career path for Deep Learning Engineer

Machine Learning Researcher

Machine Learning Researchers develop new machine learning algorithms and techniques. They may use Amazon SageMaker to quickly get started on building, training, and deploying machine learning models. This course may be useful for individuals who wish to shift into a Machine Learning Research role.

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Image Classification with Amazon Sagemaker

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Reviews summary

Sagemaker image classification course

Activities

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