Creating & Deploying Microsoft Azure Machine Learning Studio Solutions from Pluralsight

This course will provide an introduction to the power, flexibility and scalability of Azure Machine Learning. You will learn to implement the data science process, to prepare data and integrate data sources for use in machine learning experiments.

Machine Learning and Data Science is an exciting, fast growing field which will provide you with the tools to gain deeper insights from your data. In this course, Creating & Deploying Microsoft Azure Machine Learning Studio Solutions, you'll be Creating & Deploying Microsoft Azure Machine Learning Studio Solutions. First, you’ll explore data import, cleansing, and transformation. Next, you’ll discover training, evaluating and refining Machine Learning Models. Finally, you’ll learn how to deploy and consume Predictive Web Services. When you’re finished with this course, you’ll know how to create data science experiments using a variety of machine learning algorithms using both a visual user interface and code first using Jupyter notebooks and Visual Studio Code.

What's inside

Syllabus

Course Overview

Getting Started with the Azure Machine Learning Studio

Preparing Data and Data Sources

Cleaning, Normalizing and Transforming Raw Data (Feature Engineering)

Training, Evaluating and Refining Machine Learning Models

Automated Machine Learning

Deployment and Machine Learning Pipelines

Wrapping Up

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops expertise in Azure Machine Learning, a growing tool that's relevant in industry

Taught by recognized instructor Shawn Hainsworth

Covers a range of beginner and intermediate topics

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:

Data Scientist

Data Scientists are responsible for collecting, analyzing, and interpreting data to help organizations make informed decisions. This course would be particularly helpful for aspiring Data Scientists, as it provides a comprehensive introduction to the Microsoft Azure Machine Learning Studio, a powerful tool for building and deploying machine learning models. By completing this course, learners will gain the skills and knowledge necessary to prepare data, train and evaluate models, and deploy predictive web services.

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Machine Learning Engineer

Machine Learning Engineers design, develop, and maintain machine learning models. This course would be a valuable asset for aspiring Machine Learning Engineers, as it provides hands-on experience with the Microsoft Azure Machine Learning Studio. Through this course, learners will develop the skills needed to build and deploy machine learning solutions that can solve real-world problems.

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Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. This course would be beneficial for aspiring Data Analysts, as it provides a foundation in data preparation and transformation. By completing this course, learners will gain the skills necessary to prepare data for analysis and visualization.

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Business Intelligence Analyst

Business Intelligence Analysts use data to help businesses make better decisions. This course would be helpful for aspiring Business Intelligence Analysts, as it provides an introduction to machine learning and its applications in business. By completing this course, learners will gain the skills needed to identify and solve business problems using machine learning.

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Software Engineer

Software Engineers design, develop, and maintain software systems. This course may be useful for aspiring Software Engineers who are interested in developing machine learning applications. By completing this course, learners will gain the skills needed to build and deploy machine learning models using the Microsoft Azure Machine Learning Studio.

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Data Engineer

Data Engineers design, build, and maintain data pipelines. This course may be helpful for aspiring Data Engineers who are interested in building and deploying machine learning pipelines. By completing this course, learners will gain the skills needed to prepare data for machine learning models and deploy those models into production.

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Statistician

Statisticians collect, analyze, and interpret data to provide insights and make predictions. This course may be helpful for aspiring Statisticians who are interested in using machine learning to analyze data. By completing this course, learners will gain the skills needed to prepare data for machine learning models and interpret the results of those models.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve business problems. This course may be helpful for aspiring Operations Research Analysts who are interested in using machine learning to solve business problems. By completing this course, learners will gain the skills needed to prepare data for machine learning models and interpret the results of those models.

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Market Research Analyst

Market Research Analysts collect and analyze data to understand consumer behavior and market trends. This course may be helpful for aspiring Market Research Analysts who are interested in using machine learning to analyze market data. By completing this course, learners will gain the skills needed to prepare data for machine learning models and interpret the results of those models.

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Financial Analyst

Financial Analysts use data to make investment decisions. This course may be helpful for aspiring Financial Analysts who are interested in using machine learning to analyze financial data. By completing this course, learners will gain the skills needed to prepare data for machine learning models and interpret the results of those models.

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Actuary

Actuaries use mathematical and statistical techniques to assess risk and uncertainty. This course may be helpful for aspiring Actuaries who are interested in using machine learning to assess risk. By completing this course, learners will gain the skills needed to prepare data for machine learning models and interpret the results of those models.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical techniques to analyze financial data. This course may be helpful for aspiring Quantitative Analysts who are interested in using machine learning to analyze financial data. By completing this course, learners will gain the skills needed to prepare data for machine learning models and interpret the results of those models.

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Risk Analyst

Risk Analysts use data to identify and assess risks. This course may be helpful for aspiring Risk Analysts who are interested in using machine learning to identify and assess risks. By completing this course, learners will gain the skills needed to prepare data for machine learning models and interpret the results of those models.

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Insurance Analyst

Insurance Analysts use data to assess risk and determine insurance premiums. This course may be helpful for aspiring Insurance Analysts who are interested in using machine learning to assess risk. By completing this course, learners will gain the skills needed to prepare data for machine learning models and interpret the results of those models.

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Healthcare Analyst

Healthcare Analysts use data to analyze healthcare trends and improve patient care. This course may be helpful for aspiring Healthcare Analysts who are interested in using machine learning to analyze healthcare data. By completing this course, learners will gain the skills needed to prepare data for machine learning models and interpret the results of those models.

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