We may earn an affiliate commission when you visit our partners.
How to Use Microsoft Azure ML Studio for Kaggle Competitions
Ikechukwu Nigel Ogbuchi
Ikechukwu Nigel Ogbuchi
In this 90 minutes long project-based course, you will learn how to create a Microsoft Azure ML Studio account, a Kaggle account for competitions and use both of them to build a machine learning model which we will be using to make predictions.
Note: This...
Read more
In this 90 minutes long project-based course, you will learn how to create a Microsoft Azure ML Studio account, a Kaggle account for competitions and use both of them to build a machine learning model which we will be using to make predictions.
Note: This...
Read more
In this 90 minutes long project-based course, you will learn how to create a Microsoft Azure ML Studio account, a Kaggle account for competitions and use both of them to build a machine learning model which we will be using to make predictions.
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/gvht6u/how
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches data science using Microsoft's Azure and Kaggle, which are industry standard
Builds hands-on experience, which is useful in personal growth and development
Appears to focus on a single aspect of machine learning, which may limit the breadth of knowledge acquired by learners
Assumes proficiency in Azure and Kaggle, which may be a barrier to learners who are not familiar with these tools
Targeted towards learners in North America, which may be inconvenient for learners in other regions
May not be suitable for complete beginners in machine learning, as it assumes some prior knowledge
Save this course
Save How to Use Microsoft Azure ML Studio for Kaggle Competitions to your list so you can find it easily later:
Save
Save
Reviews summary
Ml studio for kaggle
This course is well reviewed and well received, especially for users who are located in the North American region. Learners say that it provides a good hands-on experience for building machine learning models for Kaggle competitions.
Great hands-on learning experience.
"Build Machine Learning Models without writing code for Kaggle competitions."
Activities
Coming soon
We're preparing activities for
How to Use Microsoft Azure ML Studio for Kaggle Competitions.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete How to Use Microsoft Azure ML Studio for Kaggle Competitions will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist helps build and develop machine learning models, the core of this course. This course will help you begin to advance your career in this field. The course will get you familiar with Microsoft Azure ML Studio and how to use it for machine learning competitions on Kaggle, a popular platform for such competitions. As you progress in your career, additional courses may cover more complex aspects of machine learning, as well as other software and platforms.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer focuses on building, testing, and deploying machine learning models, skills you will use regularly in this course. After completing this course and others like it, you will have a firm foundation to continue developing your career in machine learning and engineering.
Data Analyst
Data Analyst
Data Analysts build and improve data collection and analysis processes to support decision-making, often in a data-driven context. This course will help you gain familiarity with Microsoft Azure ML Studio and how to develop machine learning models which may be useful to you in this role.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts leverage statistical models to analyze financial data and make trading decisions. This course will help you build a foundation for using machine learning, including the type you will build in this course, in financial trading.
Software Engineer
Software Engineer
Software Engineers design, build, and maintain software systems. The skills and knowledge you will learn in this course may be helpful as you progress in this career, especially if you work on machine learning-related projects.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data systems and infrastructure. This course may be helpful as you begin or progress in this career by introducing you to Microsoft Azure ML Studio, which you may use on the job.
Business Analyst
Business Analyst
Business Analysts analyze business processes and develop solutions to improve efficiency. This course may be helpful to you in this career by introducing you to machine learning, which may be used in the solutions you propose.
Market Researcher
Market Researcher
Market Researchers analyze market trends and customer behavior. This course may be helpful in this career by providing an introduction to machine learning, including building a machine learning model from start to finish.
Financial Analyst
Financial Analyst
Financial Analysts provide advice and guidance on financial matters. This course may be helpful by introducing you to machine learning, which is used in financial analysis in various ways.
Product Manager
Product Manager
Product Managers oversee the development and launch of products. This course may be helpful in this career by introducing you to machine learning, which may be used in developing or improving products.
Consultant
Consultant
Consultants provide advice and guidance on a variety of topics. This course may be helpful if you are interested in consulting in a field related to machine learning, or if you wish to use machine learning to improve your consulting projects.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. This course may be helpful by introducing you to machine learning, which uses statistics in its algorithms and models.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to improve organizational efficiency. This course may be helpful in this career by introducing you to machine learning, which may be used in optimization and modeling.
Actuary
Actuary
Actuaries analyze and manage financial risks. This course may be helpful by providing an introduction to machine learning, which is used in risk assessment and modeling.
Economist
Economist
Economists study and analyze economic data. This course may be helpful by providing an introduction to machine learning, which is used in economic modeling and forecasting.
For more career information including salaries, visit:
OpenCourser.com/course/gvht6u/how
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
How to Use Microsoft Azure ML Studio for Kaggle Competitions.
Provides a comprehensive overview of statistical learning methods, covering topics such as linear regression, logistic regression, decision trees, and support vector machines. It valuable resource for learners who want to gain a deeper understanding of the statistical foundations of machine learning.
Provides a comprehensive overview of machine learning from a Bayesian and optimization perspective. It covers topics such as statistical inference, Bayesian modeling, and optimization methods. It valuable resource for learners who want to gain a deeper understanding of the theoretical foundations of machine learning.
Teaches the fundamental concepts of data science from scratch, covering topics such as data exploration, data cleaning, feature engineering, and modeling. It valuable resource for learners who are new to data science and want to gain a solid foundation in the field.
Provides a hands-on introduction to machine learning using Python. It covers topics such as data preprocessing, model selection, and model evaluation. It valuable resource for learners who want to gain practical experience in machine learning.
Provides a beginner-friendly introduction to machine learning. It covers topics such as the basics of machine learning, data preprocessing, and model training. It valuable resource for learners who are new to machine learning and want to gain a solid foundation.
Provides a comprehensive introduction to machine learning using R. It covers topics such as data preparation, model training, and model evaluation. It valuable resource for learners who want to gain proficiency in using R for machine learning tasks.
Provides a comprehensive introduction to Python for data analysis. It covers topics such as data manipulation, data visualization, and statistical modeling. It valuable resource for learners who want to gain proficiency in using Python for data analysis tasks.
Introduces the core concepts of machine learning using TensorFlow. It covers topics such as neural networks, deep learning, and image processing. It valuable resource for learners who want to explore the field of machine learning using TensorFlow.
Introduces the core concepts of deep learning and provides practical guidance on building and training deep learning models using Python. It covers topics such as convolutional neural networks, recurrent neural networks, and image processing. It valuable resource for learners who want to explore the field of deep learning.
Provides a non-technical introduction to artificial intelligence. It covers topics such as the history of AI, the different types of AI, and the ethical implications of AI. It valuable resource for learners who want to gain a general understanding of AI.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/gvht6u/how
Share
Similar courses
Here are nine courses similar to
How to Use Microsoft Azure ML Studio for Kaggle Competitions.
Create Sales Proposal Presentations with Google Slides
OpenCourser.com/course/ef3veh/create
Create Sales Proposal Presentations with Google Slides
Develop Sales Account Management Plan in Google Sheets
OpenCourser.com/course/3j6lto/develop
Develop Sales Account Management Plan in Google Sheets
Object Detection with Amazon Sagemaker
OpenCourser.com/course/ky7fio/object
Object Detection with Amazon Sagemaker
Image Classification with Amazon Sagemaker
OpenCourser.com/course/7tb8gh/image
Image Classification with Amazon Sagemaker
Working with Azure Data Storage
OpenCourser.com/course/2n0rnz/working
Working with Azure Data Storage
Building Recommendation System Using MXNET on AWS Sagemaker
OpenCourser.com/course/glv1ks/building
Building Recommendation System Using MXNET on AWS...
Using TensorFlow with Amazon Sagemaker
OpenCourser.com/course/3yu0lo/using
Using TensorFlow with Amazon Sagemaker
Track Networking Efforts using Google Analytics
OpenCourser.com/course/ye6tww/track
Track Networking Efforts using Google Analytics
Semantic Segmentation with Amazon Sagemaker
OpenCourser.com/course/l6wi1t/semantic
Semantic Segmentation with Amazon Sagemaker
Time
1 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Ikechukwu Nigel Ogbuchi
Good to know
Teaches data science using Microsoft's Azure and Kaggle, which are industry standard
Builds hands-on experience, which is useful in personal growth and development
Appears to focus on a single aspect of machine learning, which may limit the breadth of knowledge acquired by learners
Assumes proficiency in Azure and Kaggle, which may be a barrier to learners who are not familiar with these tools
Targeted towards learners in North America, which may be inconvenient for learners in other regions
May not be suitable for complete beginners in machine learning, as it assumes some prior knowledge
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser