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Catalin Popa
This is an intermediate project on creating clustering models in Azure Machine Learning Studio. Familiarity with any Web Browser and navigating Windows Desktop is assumed. Some background knowledge on Machine Learning or Cloud computing is beneficial but not required to complete this project. Understanding how platform services in the cloud work and how machine learning algorithms function would be of great help in understanding better what we are executing in this guided project. Some minimal data engineering and data scientist knowledge is required.
Read more
This is an intermediate project on creating clustering models in Azure Machine Learning Studio. Familiarity with any Web Browser and navigating Windows Desktop is assumed. Some background knowledge on Machine Learning or Cloud computing is beneficial but not required to complete this project. Understanding how platform services in the cloud work and how machine learning algorithms function would be of great help in understanding better what we are executing in this guided project. Some minimal data engineering and data scientist knowledge is required.
Read more
This is an intermediate project on creating clustering models in Azure Machine Learning Studio. Familiarity with any Web Browser and navigating Windows Desktop is assumed. Some background knowledge on Machine Learning or Cloud computing is beneficial but not required to complete this project. Understanding how platform services in the cloud work and how machine learning algorithms function would be of great help in understanding better what we are executing in this guided project. Some minimal data engineering and data scientist knowledge is required.
This guided project has the aim to demonstrate how you can create Machine Learning models by using the out-of-the-box solutions that Azure offers, by just using these services as-is, on your own data.
The main focus is on the data and how this is being used by the services.
As this project is based on Azure technologies, an Azure subscription is required. The project also outlines a step where an Azure subscription will be created and for this, the following items are required: a valid phone number, a credit card, and a GitHub or Microsoft account username.
The series of tasks will mainly be carried out using a web browser.
If you enjoy this project, we recommend taking the Microsoft Azure AI Fundamentals AI-900 Exam Prep Specialization: https://www.coursera.org/specializations/microsoft-azure-ai-900-ai-fundamentals
Register for this course and see more details by visiting:
OpenCourser.com/course/fh1xi5/develop
What's inside
Syllabus
Project Overview
By the end of this project, you will have successfully created an Azure account, logged into the Azure Portal, created an Azure Machine Learning Workspace and cluster data from a given data set. You will develop clustering models through a series of tasks which include selecting the appropriate actions in Azure Machine Learning Studio and then assessing and compering different clustering models. The skills learned in this guided project will provide the foundation to understanding and implementing Artificial Intelligence & Machine Learning solutions in Microsoft Azure.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches how to create clustering models by using the out-of-the-box solutions that Azure offers
Assumes some background knowledge on Machine Learning or Cloud computing
Requires an Azure subscription, which may pose a barrier to some students
Focuses on how data is used by services, which may be of interest to data scientists and engineers
Provides hands-on experience through a series of tasks
Develops foundational skills for understanding and implementing AI & Machine Learning in Microsoft Azure
Save this course
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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 Develop Clustering Models with Azure ML Designer with these
activities:
Organize and review course notes
Show steps
Reinforce your understanding by organizing and reviewing notes from class lectures and course readings.
Browse courses on
Machine Learning
Show steps
-
Collect and organize notes from all course materials.
-
Review notes regularly to reinforce key concepts.
-
Summarize and highlight important points.
Attend a study group on clustering
Show steps
Collaborate with peers to discuss clustering techniques, exchange ideas, and enhance your understanding.
Browse courses on
Machine Learning
Show steps
-
Find or create a study group with fellow students.
-
Schedule regular meetings to discuss course materials and work on exercises together.
-
Share insights and perspectives on different clustering algorithms.
Review the basics of Python
Show steps
Reinforce your understanding of Python syntax and data structures to enhance your comprehension of the course material.
Browse courses on
Python
Show steps
-
Revisit online tutorials or documentation on Python basics.
-
Review code examples and practice writing simple Python scripts.
14 other activities
Expand to see all activities and additional details
Show all 17 activities
Complete Azure Machine Learning Studio tutorials
Show steps
Deepen your understanding of Azure Machine Learning Studio's functionalities by following guided tutorials.
Show steps
-
Explore the Azure Machine Learning Studio documentation.
-
Complete the tutorials provided by Microsoft on Azure Machine Learning Studio.
Join a study group or discussion forum
Show steps
Engage with peers to exchange knowledge, clarify concepts, and enhance your comprehension.
Show steps
-
Identify and join online or offline study groups or discussion forums related to Azure Machine Learning.
-
Actively participate in discussions, ask questions, and share your insights.
Azure Machine Learning Studio Exercises
Show steps
Reinforce skills in using Azure Machine Learning Studio through guided exercises.
Browse courses on
Azure Machine Learning Studio
Show steps
-
Create a new Azure Machine Learning workspace
-
Upload a dataset to the workspace
-
Create a clustering model in the workspace
-
Evaluate the performance of the clustering model
Follow guides on data analysis
Show steps
Reinforce your understanding of clustering by following guided tutorials that walk you through data analysis techniques in Azure.
Browse courses on
Machine Learning
Show steps
-
Identify and select relevant tutorials on Azure data analysis.
-
Follow the tutorials step-by-step to analyze sample datasets.
-
Experiment with different data analysis methods and techniques.
Gather resources on clustering algorithms
Show steps
Expand your knowledge by compiling resources on clustering algorithms to supplement your learning.
Show steps
-
Research and identify authoritative sources on clustering algorithms.
-
Categorize and organize the resources into a cohesive collection.
Solve practice problems on clustering
Show steps
Strengthen your understanding by solving practice problems and applying clustering techniques to real-world scenarios.
Show steps
-
Find practice problems on clustering algorithms and techniques.
-
Attempt to solve the problems on your own.
Complete coding exercises on clustering
Show steps
Enhance your coding skills by solving practice exercises that focus specifically on clustering algorithms.
Browse courses on
Machine Learning
Show steps
-
Find online platforms or resources that provide coding exercises.
-
Select exercises that cover different aspects of clustering.
-
Solve the exercises using your preferred programming language.
-
Analyze your results and identify areas for improvement.
Build a simple clustering model in Azure Machine Learning Studio
Show steps
Apply your learning by creating a basic clustering model to solidify your understanding of the process.
Show steps
-
Select and prepare a suitable dataset.
-
Design and implement a clustering model using Azure Machine Learning Studio.
-
Evaluate and refine the model to achieve optimal performance.
Clustering Model Deployment Plan
Show steps
Develop a plan for deploying a clustering model in a production environment.
Browse courses on
Machine Learning Model Deployment
Show steps
-
Identify the target deployment environment
-
Determine the deployment architecture and infrastructure requirements
-
Plan for model monitoring and maintenance
-
Create a deployment timeline and budget
Answer questions or tutor fellow students
Show steps
Reinforce your understanding by sharing your knowledge and assisting others in the learning process.
Show steps
-
Offer assistance to fellow students on online forums or discussion boards related to Azure Machine Learning.
-
Provide clear explanations, share resources, and guide others in their learning.
Develop a case study on clustering
Show steps
Solidify your knowledge by creating a case study that demonstrates how you would apply clustering techniques to a real-world problem.
Browse courses on
Machine Learning
Show steps
-
Identify a relevant problem or scenario.
-
Gather and analyze data related to the problem.
-
Apply clustering techniques to identify patterns and insights.
-
Develop a report or presentation summarizing your findings.
Write a blog post or article on Azure Machine Learning Studio
Show steps
Enhance your understanding by articulating your knowledge in written form and sharing it with a wider audience.
Show steps
-
Choose a specific aspect of Azure Machine Learning Studio to write about.
-
Research and gather information to support your writing.
-
Craft a well-structured and informative article or blog post.
Build a personal project using clustering
Show steps
Apply your clustering knowledge to a personal project that allows you to explore real-world applications.
Browse courses on
Machine Learning
Show steps
-
Brainstorm ideas for a project that aligns with your interests.
-
Gather and preprocess the necessary data for the project.
-
Implement clustering techniques and evaluate different algorithms.
-
Develop a user interface or visualization to present your findings.
Participate in data science competitions
Show steps
Challenge yourself by participating in data science competitions that focus on clustering tasks.
Show steps
-
Identify relevant competitions on websites like Kaggle or DrivenData.
-
Study the competition details and data requirements.
-
Develop and implement your clustering solution.
-
Submit your results and analyze your performance against others.
Organize and review course notes
Show steps
Reinforce your understanding by organizing and reviewing notes from class lectures and course readings.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Collect and organize notes from all course materials.
- Review notes regularly to reinforce key concepts.
- Summarize and highlight important points.
Attend a study group on clustering
Show steps
Collaborate with peers to discuss clustering techniques, exchange ideas, and enhance your understanding.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Find or create a study group with fellow students.
- Schedule regular meetings to discuss course materials and work on exercises together.
- Share insights and perspectives on different clustering algorithms.
Review the basics of Python
Show steps
Reinforce your understanding of Python syntax and data structures to enhance your comprehension of the course material.
Browse courses on
Python
Show steps
Show steps
Show steps
- Revisit online tutorials or documentation on Python basics.
- Review code examples and practice writing simple Python scripts.
14 other activities
Expand to see all activities and additional details
Show all 17 activities
Complete Azure Machine Learning Studio tutorials
Show steps
Deepen your understanding of Azure Machine Learning Studio's functionalities by following guided tutorials.
Show steps
Show steps
Show steps
- Explore the Azure Machine Learning Studio documentation.
- Complete the tutorials provided by Microsoft on Azure Machine Learning Studio.
Join a study group or discussion forum
Show steps
Engage with peers to exchange knowledge, clarify concepts, and enhance your comprehension.
Show steps
Show steps
Show steps
- Identify and join online or offline study groups or discussion forums related to Azure Machine Learning.
- Actively participate in discussions, ask questions, and share your insights.
Azure Machine Learning Studio Exercises
Show steps
Reinforce skills in using Azure Machine Learning Studio through guided exercises.
Browse courses on
Azure Machine Learning Studio
Show steps
Show steps
Show steps
- Create a new Azure Machine Learning workspace
- Upload a dataset to the workspace
- Create a clustering model in the workspace
- Evaluate the performance of the clustering model
Follow guides on data analysis
Show steps
Reinforce your understanding of clustering by following guided tutorials that walk you through data analysis techniques in Azure.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Identify and select relevant tutorials on Azure data analysis.
- Follow the tutorials step-by-step to analyze sample datasets.
- Experiment with different data analysis methods and techniques.
Gather resources on clustering algorithms
Show steps
Expand your knowledge by compiling resources on clustering algorithms to supplement your learning.
Show steps
Show steps
Show steps
- Research and identify authoritative sources on clustering algorithms.
- Categorize and organize the resources into a cohesive collection.
Solve practice problems on clustering
Show steps
Strengthen your understanding by solving practice problems and applying clustering techniques to real-world scenarios.
Show steps
Show steps
Show steps
- Find practice problems on clustering algorithms and techniques.
- Attempt to solve the problems on your own.
Complete coding exercises on clustering
Show steps
Enhance your coding skills by solving practice exercises that focus specifically on clustering algorithms.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Find online platforms or resources that provide coding exercises.
- Select exercises that cover different aspects of clustering.
- Solve the exercises using your preferred programming language.
- Analyze your results and identify areas for improvement.
Build a simple clustering model in Azure Machine Learning Studio
Show steps
Apply your learning by creating a basic clustering model to solidify your understanding of the process.
Show steps
Show steps
Show steps
- Select and prepare a suitable dataset.
- Design and implement a clustering model using Azure Machine Learning Studio.
- Evaluate and refine the model to achieve optimal performance.
Clustering Model Deployment Plan
Show steps
Develop a plan for deploying a clustering model in a production environment.
Browse courses on
Machine Learning Model Deployment
Show steps
Show steps
Show steps
- Identify the target deployment environment
- Determine the deployment architecture and infrastructure requirements
- Plan for model monitoring and maintenance
- Create a deployment timeline and budget
Answer questions or tutor fellow students
Show steps
Reinforce your understanding by sharing your knowledge and assisting others in the learning process.
Show steps
Show steps
Show steps
- Offer assistance to fellow students on online forums or discussion boards related to Azure Machine Learning.
- Provide clear explanations, share resources, and guide others in their learning.
Develop a case study on clustering
Show steps
Solidify your knowledge by creating a case study that demonstrates how you would apply clustering techniques to a real-world problem.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Identify a relevant problem or scenario.
- Gather and analyze data related to the problem.
- Apply clustering techniques to identify patterns and insights.
- Develop a report or presentation summarizing your findings.
Write a blog post or article on Azure Machine Learning Studio
Show steps
Enhance your understanding by articulating your knowledge in written form and sharing it with a wider audience.
Show steps
Show steps
Show steps
- Choose a specific aspect of Azure Machine Learning Studio to write about.
- Research and gather information to support your writing.
- Craft a well-structured and informative article or blog post.
Build a personal project using clustering
Show steps
Apply your clustering knowledge to a personal project that allows you to explore real-world applications.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Brainstorm ideas for a project that aligns with your interests.
- Gather and preprocess the necessary data for the project.
- Implement clustering techniques and evaluate different algorithms.
- Develop a user interface or visualization to present your findings.
Participate in data science competitions
Show steps
Challenge yourself by participating in data science competitions that focus on clustering tasks.
Show steps
Show steps
Show steps
- Identify relevant competitions on websites like Kaggle or DrivenData.
- Study the competition details and data requirements.
- Develop and implement your clustering solution.
- Submit your results and analyze your performance against others.
Career center
Learners who complete Develop Clustering Models with Azure ML Designer will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
The Data Analyst is responsible for collecting, cleaning, and analyzing data to provide insights to businesses. By using the knowledge gained in this course, Data Analysts can create clustering models to identify patterns and trends in data, which can be used to make better decisions. This course is particularly relevant to Data Analysts because it provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models. This course can help Machine Learning Engineers develop clustering models to solve real-world problems. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience will be valuable to Machine Learning Engineers as they work to build and deploy clustering models in the cloud.
Data Scientist
Data Scientist
Data Scientists use data to solve business problems. This course can help Data Scientists develop clustering models to identify patterns and trends in data. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience will be valuable to Data Scientists as they work to solve business problems with data.
Business Analyst
Business Analyst
Business Analysts help businesses make better decisions by providing them with data-driven insights. This course can help Business Analysts develop clustering models to identify patterns and trends in data. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience will be valuable to Business Analysts as they work to provide businesses with data-driven insights.
Statistician
Statistician
Statisticians use data to draw conclusions about the world. This course can help Statisticians develop clustering models to identify patterns and trends in data. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience will be valuable to Statisticians as they work to draw conclusions about the world.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course may be useful for Software Engineers who are interested in developing machine learning models. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience may be valuable to Software Engineers as they work to develop machine learning models.
Computer Scientist
Computer Scientist
Computer Scientists conduct research in the field of computer science. This course may be useful for Computer Scientists who are interested in developing machine learning models. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience may be valuable to Computer Scientists as they work to conduct research in the field of computer science.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines. This course may be useful for Data Engineers who are interested in developing machine learning models. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience may be valuable to Data Engineers as they work to design, build, and maintain data pipelines.
Database Administrator
Database Administrator
Database Administrators maintain databases. This course may be useful for Database Administrators who are interested in developing machine learning models. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience may be valuable to Database Administrators as they work to maintain databases.
Systems Analyst
Systems Analyst
Systems Analysts design, develop, and maintain computer systems. This course may be useful for Systems Analysts who are interested in developing machine learning models. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience may be valuable to Systems Analysts as they work to design, develop, and maintain computer systems.
Web Developer
Web Developer
Web Developers design, develop, and maintain websites. This course may be useful for Web Developers who are interested in developing machine learning models. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience may be valuable to Web Developers as they work to design, develop, and maintain websites.
Mobile Developer
Mobile Developer
Mobile Developers design, develop, and maintain mobile applications. This course may be useful for Mobile Developers who are interested in developing machine learning models. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience may be valuable to Mobile Developers as they work to design, develop, and maintain mobile applications.
Game Developer
Game Developer
Game Developers design, develop, and maintain video games. This course may be useful for Game Developers who are interested in developing machine learning models. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience may be valuable to Game Developers as they work to design, develop, and maintain video games.
UX Designer
UX Designer
UX Designers design the user experience for websites and applications. This course may be useful for UX Designers who are interested in developing machine learning models. The course provides hands-on experience with Azure Machine Learning Studio, a cloud-based platform for developing and deploying machine learning models. This experience may be valuable to UX Designers as they work to design the user experience for websites and applications.
Technical Writer
Technical Writer
Technical Writers write documentation for software and hardware. This course may be useful for Technical Writers who are interested in learning about machine learning. The course provides an overview of machine learning concepts and how they can be applied to real-world problems. This knowledge may be valuable to Technical Writers as they work to write documentation for software and hardware.
For more career information including salaries, visit:
OpenCourser.com/course/fh1xi5/develop
Reading list
We've selected ten 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
Develop Clustering Models with Azure ML Designer.
Provides a comprehensive overview of machine learning. It covers a wide range of topics, including data preparation, model training, and deployment. This book valuable resource for anyone who wants to learn more about machine learning.
Provides a comprehensive overview of statistical learning. It covers a wide range of topics, including data preparation, model training, and deployment. This book valuable resource for anyone who wants to learn more about statistical learning.
Provides a comprehensive overview of pattern recognition and machine learning. It covers a wide range of topics, including data preparation, model training, and deployment. This book valuable resource for anyone who wants to learn more about pattern recognition and machine learning.
Save
Provides a comprehensive overview of machine learning. It covers a wide range of topics, including data preparation, model training, and deployment. This book valuable resource for anyone who wants to learn more about machine learning.
Save
Provides a comprehensive overview of deep learning. It covers a wide range of topics, including data preparation, model training, and deployment. This book valuable resource for anyone who wants to learn more about deep learning.
Provides a comprehensive overview of statistical learning. It covers a wide range of topics, including data preparation, model training, and deployment. This book valuable resource for anyone who wants to learn more about statistical learning.
Provides a comprehensive overview of machine learning with Python. It covers a wide range of topics, including data preparation, model training, and deployment. This book valuable resource for anyone who wants to learn more about machine learning with Python.
Provides a practical guide to deep learning with Python. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks. This book valuable resource for anyone who wants to learn more about deep learning with Python.
Provides a comprehensive overview of reinforcement learning. It covers the basics of reinforcement learning, as well as more advanced topics such as deep reinforcement learning. This book valuable resource for anyone who wants to learn more about reinforcement learning.
Save
Provides a gentle introduction to machine learning. It covers the basics of machine learning, as well as more advanced topics such as deep learning. This book valuable resource for anyone who wants to learn more about machine learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/fh1xi5/develop
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Effort
2 Hours
Level
Intermediate
Via
Coursera
Institution
Microsoft
Instructor
Catalin Popa
Language
English
Good to know
Teaches how to create clustering models by using the out-of-the-box solutions that Azure offers
Assumes some background knowledge on Machine Learning or Cloud computing
Requires an Azure subscription, which may pose a barrier to some students
Focuses on how data is used by services, which may be of interest to data scientists and engineers
Provides hands-on experience through a series of tasks
Develops foundational skills for understanding and implementing AI & Machine Learning in Microsoft Azure
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