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Axel Sirota
Regardless of if you have some hours or some years building models, Azures’s Automated Machine Learning has something to amaze you. This course will teach you how to use it to build the best Machine Learning model for your data in just a few clicks!
Read more
Regardless of if you have some hours or some years building models, Azures’s Automated Machine Learning has something to amaze you. This course will teach you how to use it to build the best Machine Learning model for your data in just a few clicks!
Read more
Regardless of if you have some hours or some years building models, Azures’s Automated Machine Learning has something to amaze you. This course will teach you how to use it to build the best Machine Learning model for your data in just a few clicks!
Building Machine Learning models means iterating multiple times over the best features, the best architectures, the best algorithms, until you get a model that serves your business purpose. In this course, Build Optimal Models with Azure Automated ML, you’ll learn to create the best machine learning model for your own specific data in just a few clicks. First, you’ll explore what Auto ML really is. Next, you’ll discover how to create optimal models both from the UI as well as the SDK. Finally, you’ll learn how to improve our models with more advanced techniques Azure ML offers. When you’re finished with this course, you’ll have the skills and knowledge of Automated Machine Learning needed to build the best Machine Learning model for your data in just a few clicks!
Register for this course and see more details by visiting:
OpenCourser.com/course/4okca3/build
What's inside
Syllabus
Course Overview
Introducing Azure Automated Machine Learning
Creating Optimized Models with Azure Machine Learning Studio
Creating Optimized Models with Azure Machine Learning SDK
Read more
Syllabus
Course Overview
Introducing Azure Automated Machine Learning
Creating Optimized Models with Azure Machine Learning Studio
Creating Optimized Models with Azure Machine Learning SDK
Read more
Final Thoughts
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Focuses on teaching students how to use Azure Machine Learning's automated machine learning capabilities to create optimal models for their specific data
Introduces learners to Azure Machine Learning's automated machine learning capabilities and their applications
Students with either limited or extensive experience in building models may benefit from this course
Students will learn about creating optimal machine learning models using both the UI and SDK interfaces
Covers advanced Azure ML techniques for improving model capabilities, making it suitable for learners seeking to enhance their ML skills
It is unclear whether the course covers deploying and monitoring ML models
Save this course
Save Build Optimal Models with Azure Automated ML to your list so you can find it easily later:
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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 Build Optimal Models with Azure Automated ML with these
activities:
Review Machine Learning concepts
Show steps
Strengthen your foundation in Machine Learning concepts to enhance your understanding of Azure Machine Learning.
Show steps
-
Review notes or textbooks on supervised and unsupervised learning
-
Revisit online resources or video tutorials on Machine Learning algorithms
Explore Microsoft Learn modules on Automated Machine Learning
Show steps
Expand your knowledge and gain practical insights through guided tutorials from Microsoft.
Show steps
-
Visit the Microsoft Learn website
-
Search for and select Azure Automated Machine Learning modules
-
Follow the interactive tutorials to learn about Azure ML concepts
Review Azure Machine Learning
Show steps
Lay a strong knowledge base for the course by going over key concepts related to Azure Machine Learning.
Browse courses on
Azure Machine Learning
Show steps
-
Review documentation on Azure Machine Learning Studio
-
Complete tutorials on building models with Azure Machine Learning SDK
Six other activities
Expand to see all activities and additional details
Show all nine activities
Practice building models with Azure Machine Learning Studio
Show steps
Solidify your understanding of Azure Machine Learning Studio's features by building models.
Browse courses on
Azure Machine Learning Studio
Show steps
-
Create a new model in Azure Machine Learning Studio
-
Select a dataset and features for your model
-
Train and evaluate your model
-
Deploy your model to Azure
Start Automated Machine Learning Experiment
Show steps
Set up your own Automated Machine Learning experiment to practice the concepts taught in the course.
Browse courses on
Machine Learning
Show steps
-
Review the course materials on Automated Machine Learning
-
Choose a dataset to use for your experiment
-
Create an Azure ML workspace
-
Configure and run an Automated Machine Learning experiment
-
Evaluate the results of your experiment
Follow tutorials on advanced techniques in Azure Machine Learning
Show steps
Expand your knowledge of Azure Machine Learning by exploring advanced techniques.
Show steps
-
Find tutorials on Azure Machine Learning's documentation
-
Follow tutorials on feature engineering and model optimization
-
Experiment with different machine learning algorithms
Contribute to open-source projects related to Azure Machine Learning
Show steps
Gain practical experience and contribute to the community by working on real-world projects.
Browse courses on
Open Source Projects
Show steps
-
Find a project on GitHub or another repository
-
Fork the project and create a pull request
-
Collaborate with other contributors to improve the project
Participate in a Kaggle competition using Azure Machine Learning
Show steps
Test your skills against other data scientists and gain practical experience.
Browse courses on
Kaggle Competitions
Show steps
-
Find a relevant competition on Kaggle
-
Set up an Azure Machine Learning workspace
-
Build a model to solve the competition problem
-
Submit your model to Kaggle
Build a machine learning model for an academic project
Show steps
Apply your skills and knowledge to solve a real-world problem using Azure Machine Learning.
Browse courses on
Machine Learning Projects
Show steps
-
Identify a specific problem to solve
-
Gather data to train your model
-
Train and evaluate your model's performance
-
Write a report on your findings
Review Machine Learning concepts
Show steps
Strengthen your foundation in Machine Learning concepts to enhance your understanding of Azure Machine Learning.
Show steps
Show steps
Show steps
- Review notes or textbooks on supervised and unsupervised learning
- Revisit online resources or video tutorials on Machine Learning algorithms
Explore Microsoft Learn modules on Automated Machine Learning
Show steps
Expand your knowledge and gain practical insights through guided tutorials from Microsoft.
Show steps
Show steps
Show steps
- Visit the Microsoft Learn website
- Search for and select Azure Automated Machine Learning modules
- Follow the interactive tutorials to learn about Azure ML concepts
Review Azure Machine Learning
Show steps
Lay a strong knowledge base for the course by going over key concepts related to Azure Machine Learning.
Browse courses on
Azure Machine Learning
Show steps
Show steps
Show steps
- Review documentation on Azure Machine Learning Studio
- Complete tutorials on building models with Azure Machine Learning SDK
Six other activities
Expand to see all activities and additional details
Show all nine activities
Practice building models with Azure Machine Learning Studio
Show steps
Solidify your understanding of Azure Machine Learning Studio's features by building models.
Browse courses on
Azure Machine Learning Studio
Show steps
Show steps
Show steps
- Create a new model in Azure Machine Learning Studio
- Select a dataset and features for your model
- Train and evaluate your model
- Deploy your model to Azure
Start Automated Machine Learning Experiment
Show steps
Set up your own Automated Machine Learning experiment to practice the concepts taught in the course.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Review the course materials on Automated Machine Learning
- Choose a dataset to use for your experiment
- Create an Azure ML workspace
- Configure and run an Automated Machine Learning experiment
- Evaluate the results of your experiment
Follow tutorials on advanced techniques in Azure Machine Learning
Show steps
Expand your knowledge of Azure Machine Learning by exploring advanced techniques.
Show steps
Show steps
Show steps
- Find tutorials on Azure Machine Learning's documentation
- Follow tutorials on feature engineering and model optimization
- Experiment with different machine learning algorithms
Contribute to open-source projects related to Azure Machine Learning
Show steps
Gain practical experience and contribute to the community by working on real-world projects.
Browse courses on
Open Source Projects
Show steps
Show steps
Show steps
- Find a project on GitHub or another repository
- Fork the project and create a pull request
- Collaborate with other contributors to improve the project
Participate in a Kaggle competition using Azure Machine Learning
Show steps
Test your skills against other data scientists and gain practical experience.
Browse courses on
Kaggle Competitions
Show steps
Show steps
Show steps
- Find a relevant competition on Kaggle
- Set up an Azure Machine Learning workspace
- Build a model to solve the competition problem
- Submit your model to Kaggle
Build a machine learning model for an academic project
Show steps
Apply your skills and knowledge to solve a real-world problem using Azure Machine Learning.
Browse courses on
Machine Learning Projects
Show steps
Show steps
Show steps
- Identify a specific problem to solve
- Gather data to train your model
- Train and evaluate your model's performance
- Write a report on your findings
Career center
Learners who complete Build Optimal Models with Azure Automated ML will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist works closely with teams to define problems that can be solved through data analysis. They build models to understand patterns and relationships in the data, and develop solutions to improve business outcomes. This course can be helpful for Data Scientists because it provides them with a solid understanding of Automated Machine Learning, a powerful tool that can help them build better models and improve their productivity.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is responsible for designing, developing, and deploying machine learning models. They work with data scientists to identify the appropriate algorithms and techniques to use, and they develop the code necessary to implement the models. This course can be helpful for Machine Learning Engineers because it provides them with a hands-on understanding of Automated Machine Learning, a tool that can help them automate the process of building and deploying machine learning models.
Data Analyst
Data Analyst
A Data Analyst collects, cleans, and analyzes data to identify trends and patterns. They use this information to make recommendations to businesses on how to improve their operations. This course can be helpful for Data Analysts because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of data analysis and make more accurate predictions.
Business Analyst
Business Analyst
A Business Analyst works with businesses to identify and solve problems. They use data analysis to understand the business's needs and develop solutions that improve efficiency and profitability. This course can be helpful for Business Analysts because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of data analysis and make more accurate recommendations.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. They work with teams to identify the user's needs and develop software that meets those needs. This course may be helpful for Software Engineers because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of developing and maintaining software applications.
Quant
Quant
A Quant is a financial analyst who uses mathematical and statistical models to make investment decisions. They work with data to identify trends and patterns, and they develop models to predict future market behavior. This course may be helpful for Quants because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of developing and maintaining financial models.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and statistical models to solve business problems. They work with data to identify inefficiencies and develop solutions to improve efficiency and profitability. This course may be helpful for Operations Research Analysts because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of developing and maintaining operations research models.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data. They work with data to identify trends and patterns, and they develop models to predict future outcomes. This course may be helpful for Statisticians because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of developing and maintaining statistical models.
Data Engineer
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines. They work with data to ensure that it is accurate, consistent, and accessible. This course may be helpful for Data Engineers because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of developing and maintaining data pipelines.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases. They work with data to ensure that it is secure, reliable, and performant. This course may be helpful for Database Administrators because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of developing and maintaining databases.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst uses data to identify trends and patterns and develop solutions to improve business outcomes. This course may be helpful for Business Intelligence Analysts because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of developing and maintaining business intelligence dashboards and reports.
Market Researcher
Market Researcher
A Market Researcher collects and analyzes data to understand consumer behavior. They work with data to identify trends and patterns, and they develop recommendations for businesses on how to improve their marketing strategies. This course may be helpful for Market Researchers because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of developing and maintaining market research surveys and reports.
Product Manager
Product Manager
A Product Manager is responsible for the development and launch of new products. They work with teams to identify the user's needs and develop products that meet those needs. This course may be helpful for Product Managers because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of developing and maintaining product roadmaps and specifications.
Project Manager
Project Manager
A Project Manager is responsible for the planning, execution, and completion of projects. They work with teams to identify the project's goals and objectives, and they develop plans to achieve those goals. This course may be helpful for Project Managers because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of developing and maintaining project plans and schedules.
Consultant
Consultant
A Consultant provides advice and guidance to businesses on how to improve their operations. They work with businesses to identify problems and develop solutions. This course may be helpful for Consultants because it provides them with a solid understanding of Automated Machine Learning, a tool that can help them automate the process of developing and maintaining consulting reports and presentations.
For more career information including salaries, visit:
OpenCourser.com/course/4okca3/build
Reading list
We've selected 16 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
Build Optimal Models with Azure Automated ML.
A comprehensive introduction to the mathematical foundations of machine learning. Covers topics such as linear algebra, calculus, probability, and optimization. Useful for gaining a deeper understanding of the mathematical concepts used in automated machine learning.
A comprehensive textbook on artificial intelligence, covering various topics including machine learning, natural language processing, and computer vision. Provides a solid foundation for understanding the broader field of AI and its applications.
Save
Provides a comprehensive overview of deep learning, covering the basics of deep learning and how to use Python or R to build and deploy deep learning models. It valuable resource for anyone who wants to learn more about deep learning.
Provides a comprehensive overview of machine learning with Python, covering the basics of machine learning and how to use Python to build and deploy machine learning models. It valuable resource for anyone who wants to learn more about machine learning or Python.
A comprehensive guide to deep learning using the Python programming language. Covers the theoretical foundations, practical implementation, and applications of deep learning. Useful for understanding the advanced concepts and techniques used in automated machine learning.
Provides a solid foundation in machine learning algorithms and techniques. Offers practical examples and case studies, making it suitable for both beginners and experienced practitioners. Useful for gaining a deeper understanding of the concepts underlying automated machine learning.
Provides a comprehensive overview of reinforcement learning, covering the basics of reinforcement learning and how to use Python or R to build and deploy reinforcement learning models. It valuable resource for anyone who wants to learn more about reinforcement learning.
A practical guide to machine learning using popular Python libraries such as Scikit-Learn, Keras, and TensorFlow. Offers hands-on examples and case studies, covering various machine learning tasks. Useful for gaining practical experience in building and deploying machine learning models.
A comprehensive guide to machine learning using the R programming language. Provides a thorough overview of essential concepts, algorithms, and techniques. Useful for gaining a strong foundation in machine learning fundamentals.
A practical guide to machine learning for non-technical professionals. Provides a simplified explanation of machine learning concepts and techniques. Useful for gaining a basic understanding of machine learning and its applications without requiring a strong technical background.
Provides a comprehensive overview of natural language processing with Python, covering the basics of natural language processing and how to use Python to build and deploy natural language processing models. It valuable resource for anyone who wants to learn more about natural language processing.
Provides a gentle introduction to machine learning for beginners, covering the basics of machine learning and how to use Python to build and deploy machine learning models. It valuable resource for anyone who wants to learn more about machine learning.
A beginner-friendly guide to Python programming. Covers essential concepts and practical applications. Useful for gaining a basic understanding of Python, which is the primary language used in Azure Machine Learning.
Provides a comprehensive overview of speech and language processing, covering the basics of speech and language processing and how to use Python or R to build and deploy speech and language processing models. It valuable resource for anyone who wants to learn more about speech and language processing.
Provides a comprehensive overview of machine learning with R, covering the basics of machine learning and how to use R to build and deploy machine learning models. It valuable resource for anyone who wants to learn more about machine learning or R.
Provides a beginner-friendly introduction to machine learning, covering the basics of machine learning and how to use Python or R to build and deploy machine learning models. It 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/4okca3/build
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Time
75 hours
Level
Intermediate
Via
Pluralsight
Instructor
Axel Sirota
Language
English
Good to know
Focuses on teaching students how to use Azure Machine Learning's automated machine learning capabilities to create optimal models for their specific data
Introduces learners to Azure Machine Learning's automated machine learning capabilities and their applications
Students with either limited or extensive experience in building models may benefit from this course
Students will learn about creating optimal machine learning models using both the UI and SDK interfaces
Covers advanced Azure ML techniques for improving model capabilities, making it suitable for learners seeking to enhance their ML skills
It is unclear whether the course covers deploying and monitoring ML models
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