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Shawn Hainsworth
With technology growing at a rapid speed, keeping up with data is crucial. In this course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, you will learn foundational knowledge of machine learning. First, you will learn the team data science process. Next, you will discover data import, cleansing, and transformation. Finally, you will explore how to deploy and consume predictive web services. By the end of this course, you will know how to create data science experiments using a variety of machine learning algorithms in a visual user interface.
Register for this course and see more details by visiting:
OpenCourser.com/course/5x1kr5/creating
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possible dealbreakers
Develops knowledge of Microsoft Azure foundational concepts and practices
Teaches methods and tools that align closely with what professionals use in industry
Offers hands-on labs and interactive materials, which enhance learning and strengthen knowledge retention
Builds foundational knowledge of machine learning, which is key for success in many industry roles
Covers how to deploy and consume predictive web services, deepening learners' knowledge of the machine learning lifecycle
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Creating & Deploying Microsoft Azure Machine Learning Studio Solutions.
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Career center
Learners who complete Creating & Deploying Microsoft Azure Machine Learning Studio Solutions will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and evaluates machine learning models for various applications. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, provides a hands-on approach to machine learning, enabling aspiring Machine Learning Engineers to gain practical experience in data handling, algorithm selection, and model deployment, which are essential skills for this role.
Data Scientist
Data Scientist
A Data Scientist analyzes and interprets large datasets to identify meaningful trends and patterns, which are utilized to build machine learning models that support business decisions. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, can assist aspiring Data Scientists in building a foundation in key concepts and skills, including data import, cleansing, transformation, and model deployment, which are crucial for success in this role.
Data Analyst
Data Analyst
Data Analysts collect, process, and analyze data to provide insights for decision-making. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, can help aspiring Data Analysts enhance their understanding of data handling and transformation, as well as the application of machine learning algorithms for predictive analytics, which are valuable skills in this field.
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst utilizes data to identify business trends, patterns, and opportunities. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, provides a foundation in data handling and machine learning techniques, which can assist aspiring Business Intelligence Analysts in extracting valuable insights from data and presenting them effectively for informed decision-making.
Market Researcher
Market Researcher
Market Researchers conduct surveys, analyze data, and provide insights to businesses on consumer trends and market opportunities. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, may be helpful for aspiring Market Researchers, as it provides a foundation in data handling and analysis techniques, including machine learning, which can enhance their ability to extract valuable insights from market data.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, may be beneficial for aspiring Quantitative Analysts, as it provides exposure to data handling, transformation, and modeling techniques applicable to financial data analysis.
Risk Analyst
Risk Analyst
Risk Analysts evaluate and mitigate potential risks for businesses and organizations. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, may be beneficial for aspiring Risk Analysts, as it provides a foundation in data handling and analysis techniques, including machine learning, which can enhance their ability to identify, assess, and manage risks effectively.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to improve efficiency and optimize operations within organizations. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, may be relevant for aspiring Operations Research Analysts, as it provides exposure to data handling, modeling, and optimization techniques applicable to operational decision-making.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data systems and infrastructure. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, may be relevant for aspiring Data Engineers, as it provides exposure to data handling, transformation, and modeling techniques, which are essential for building and managing data pipelines.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, may be useful for aspiring Software Engineers who seek to specialize in machine learning or data-driven applications, as it provides a foundation in data handling, modeling, and deployment techniques.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to provide insights and make predictions. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, may be useful for aspiring Statisticians who seek to specialize in machine learning or data science, as it provides a foundation in data handling, modeling, and deployment techniques.
Actuary
Actuary
Actuaries assess and manage financial risks for insurance companies and other financial institutions. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, may be beneficial for aspiring Actuaries, as it provides exposure to data handling and modeling techniques, including machine learning, which can enhance their ability to analyze and quantify risks.
Financial Analyst
Financial Analyst
Financial Analysts evaluate financial data and make recommendations for investment decisions. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, may be beneficial for aspiring Financial Analysts who seek to leverage machine learning techniques for financial data analysis and forecasting, as it provides a foundation in data handling and modeling techniques.
Management Consultant
Management Consultant
Management Consultants analyze business operations and provide recommendations for improvement. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, may be helpful for aspiring Management Consultants who seek to specialize in data-driven consulting, as it provides a foundation in data handling and analysis techniques, including machine learning, which can enhance their ability to identify and address business challenges.
Data Management Analyst
Data Management Analyst
Data Management Analysts develop and implement strategies for managing data within organizations. This course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, may be relevant for aspiring Data Management Analysts, as it provides exposure to data handling, transformation, and modeling techniques, which are essential for effective data management.
For more career information including salaries, visit:
OpenCourser.com/course/5x1kr5/creating
Reading list
We've selected seven 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
Creating & Deploying Microsoft Azure Machine Learning Studio Solutions.
Provides a theoretical foundation for machine learning, covering probabilistic models and algorithms. It's recommended for learners seeking a deeper understanding of the underlying principles.
Offers a comprehensive overview of data science using Python, including machine learning. It's a valuable resource for learners wanting to expand their knowledge beyond the course's scope.
Provides a comprehensive overview of statistical learning methods, including machine learning. It's recommended for learners seeking a strong statistical foundation.
Provides a practical guide to machine learning using Python libraries. It's recommended for learners who prefer a hands-on approach and want to learn about specific tools and techniques.
Save
Offers a comprehensive introduction to deep learning, a subfield of machine learning. It's a valuable resource for learners interested in exploring advanced topics.
Save
Covers data mining techniques and algorithms, providing a solid foundation for understanding the data science process discussed in the course.
Offers a gentle introduction to machine learning using Python, suitable for learners with limited programming experience. It's a good starting point for those new to the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/5x1kr5/creating
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Time
2 hours
Via
Pluralsight
Instructor
Shawn Hainsworth
Good to know
Develops knowledge of Microsoft Azure foundational concepts and practices
Teaches methods and tools that align closely with what professionals use in industry
Offers hands-on labs and interactive materials, which enhance learning and strengthen knowledge retention
Builds foundational knowledge of machine learning, which is key for success in many industry roles
Covers how to deploy and consume predictive web services, deepening learners' knowledge of the machine learning lifecycle
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