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Este proyecto es un curso práctico y efectivo para aprender a crear modelos de ML con Azure Machine Learning Designer. Aprenderás todos los pasos de desarrollo de un modelo y su despliegue en producción en Azure, desde su entrenamiento hasta su consumo desde un software-API de terceros.

Aprenderás desde cero Azure y los fundamentos de Azure Machine Learning. Y acabarás aprendiendo a crear tus propios modelos, evaluarlos y desplegarlos en producción.

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What's inside

Syllabus

Aprendizaje automático sin código: Azure ML Designer
En este curso se aprenderá a generar modelos de Machine Learning con Azure Machine Learning Designer

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Es un curso práctico y efectivo para aprender a crear modelos de ML con Azure Machine Learning Designer
Aprenderás todos los pasos de desarrollo de un modelo y su despliegue en producción en Azure, desde su entrenamiento hasta su consumo desde un software-API de terceros
Aprendarás desde cero Azure y los fundamentos de Azure Machine Learning
Y acabarás aprendiendo a crear tus propios modelos, evaluarlos y desplegarlos en producción
En este curso se aprenderá a generar modelos de Machine Learning con Azure Machine Learning Designer

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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 Aprendizaje automático sin código: Azure ML Designer with these activities:
Re-familiarize yourself with the fundamentals of Azure Machine Learning
Reviewing the basics of Azure Machine Learning will provide a solid foundation for understanding and applying the concepts covered in this course.
Browse courses on Azure Machine Learning
Show steps
  • Review the documentation of Azure Machine Learning
  • Go through online tutorials or training modules on Azure Machine Learning
  • Complete the Azure Machine Learning quickstart tutorial
Revise fundamental concepts of machine learning
Refreshing your knowledge of machine learning fundamentals will strengthen your foundation and enable you to better grasp the advanced concepts covered in this course.
Show steps
  • Review notes or textbooks on machine learning
  • Complete online quizzes or practice exercises
  • Watch introductory videos or tutorials on machine learning
Follow guided tutorials on Azure Machine Learning Designer
Hands-on practice with Azure Machine Learning Designer will enhance your understanding of its capabilities and enable you to apply it effectively in your projects.
Show steps
  • Identify a simple machine learning problem
  • Follow a guided tutorial to create a model using Azure Machine Learning Designer
  • Deploy the model and evaluate its performance
Five other activities
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Discuss and share knowledge with peers
Engaging with peers can provide diverse perspectives, foster collaboration, and enhance your understanding of the course material.
Show steps
  • Join or start a study group
  • Attend virtual or in-person meetups
  • Participate in online discussions or forums
Practice using Azure Machine Learning Designer through online challenges
Engaging in practice drills provides a structured way to improve your skills in using Azure Machine Learning Designer and enhance your problem-solving abilities.
Show steps
  • Identify online challenges or hackathons related to Azure Machine Learning Designer
  • Participate in the challenges and work on solving the problems
  • Review your solutions and learn from others
Create a machine learning model using Azure Machine Learning Designer
Building a model from scratch using Azure Machine Learning Designer will reinforce your understanding of the model development process and provide you with valuable hands-on experience.
Show steps
  • Define the problem and gather data
  • Create and train a model using Azure Machine Learning Designer
  • Evaluate the model's performance
  • Deploy the model
Contribute to open source projects related to Azure Machine Learning Designer
Contributing to open source projects exposes you to real-world challenges, enhances your skills, and deepens your understanding of the Azure Machine Learning Designer ecosystem.
Show steps
  • Identify open source projects related to Azure Machine Learning Designer
  • Review the project's documentation and contribution guidelines
  • Make a contribution to the project
Create a blog post or article on Azure Machine Learning Designer
Creating content helps you synthesize and communicate your knowledge, reinforcing your understanding of Azure Machine Learning Designer and potentially benefiting others.
Show steps
  • Choose a topic related to Azure Machine Learning Designer
  • Research and gather information
  • Write and edit the blog post or article
  • Publish and promote your content

Career center

Learners who complete Aprendizaje automático sin código: Azure ML Designer will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts use large datasets and statistical modeling to gather information. Machine learning is used to analyze large sums of data with the goal of identifying key trends and patterns. A business can use this data to gain insights into their operations and make more informed decisions. This course can help lead to success as a Data Analyst by teaching you how to use Azure ML Designer to create models that identify data patterns.
Market Research Analyst
Market Research Analysts use large datasets and statistical modeling to gather information. Machine learning is used to analyze large sums of data with the goal of identifying key trends and patterns. A business can use this data to gain insights into their operations and make more informed decisions. This course can help lead to success as a Market Research Analyst by teaching you how to use Azure ML Designer to create models that identify data patterns.
Business Analyst
Business Analysts use data to help businesses make better decisions. They analyze data from a variety of sources to identify trends, patterns, and anomalies. This course may be useful for future Business Analysts, as it provides an introduction to machine learning and its applications.
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency of businesses. They analyze data from a variety of sources to identify trends and patterns. This course may be useful for future Operations Research Analysts, as it provides an introduction to machine learning and its applications.
Statistician
Statisticians use data to solve problems and make decisions. They work in a variety of industries, including finance, healthcare, and education. This course may be useful for future Statisticians, as it provides an introduction to machine learning and its applications.
Financial Analyst
Financial Analysts use data to assess the financial health of companies. They analyze data from a variety of sources to identify trends and patterns. This course may be useful for future Financial Analysts, as it provides an introduction to machine learning and its applications.
Risk Analyst
Risk Analysts evaluate the risks that businesses face. They use data to quantify the probability and impact of potential risks. This course may be useful for future Risk Analysts, as it provides an introduction to machine learning and its applications.
Product Manager
Product Managers define the vision for a product and work with engineers and designers to bring it to life. They use data to understand customer needs and track the success of a product. This course may be useful for future Product Managers, as it provides an introduction to machine learning and its applications.
Data Engineer
Data Engineers build and maintain the infrastructure that is used to store and process data. They work with data scientists and software engineers to ensure that data is available in a timely and reliable manner. This course may be useful for future Data Engineers, as it provides an introduction to machine learning and its applications.
Quantitative Analyst
Quantitative Analysts use data to identify investment opportunities. They develop models to predict the future value of stocks, bonds, and other financial instruments. This course may be useful for future Quantitative Analysts, as it provides an introduction to machine learning and its applications.
Actuary
Actuaries use data to assess the financial risks that businesses face. They develop models to predict the probability and impact of potential risks. This course may be useful for future Actuaries, as it provides an introduction to machine learning and its applications.
Software Developer
Software Developers design, build, and implement software applications. They may specialize in a particular area, such as web development, mobile development, or data science. This course may be useful for those wanting to become Software Developers, as it provides an introduction to machine learning and its applications.
Data Scientist
Data Scientists use machine learning to analyze large sets of data in order to identify trends, patterns, and anomalies. They build models that can be used to automate tasks, make predictions, and improve decision-making. This course may be useful for future Data Scientists, as it provides an introduction to machine learning and its applications.
Data Miner
Data Miners use data to identify patterns and trends. They develop models to predict the future behavior of customers, products, and markets. This course may be useful for future Data Miners, as it provides an introduction to machine learning and its applications.
Machine Learning Engineer
Machine Learning Engineers design, build, and implement machine learning models. They work closely with data scientists and software engineers to ensure that models are deployed in a reliable and scalable manner. This course may be useful for future Machine Learning Engineers, as it provides an introduction to machine learning and its applications.

Reading list

We've selected six 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 Aprendizaje automático sin código: Azure ML Designer.
Este libro es una guía completa de Azure Machine Learning. Cubre todos los aspectos de la plataforma, desde la creación y el entrenamiento de modelos hasta el despliegue y la supervisión.
Este libro proporciona una guía de mejores prácticas para utilizar Azure Machine Learning. Cubre temas como el diseño de experimentos, el entrenamiento de modelos y el despliegue de modelos.
Este libro te enseñará a construir y entrenar modelos de redes neuronales profundas utilizando Fastai y PyTorch. Cubre técnicas avanzadas como la transferencia de aprendizaje y la regularización.
Este libro es un libro de texto introductorio sobre el aprendizaje por refuerzo. Cubre los fundamentos del aprendizaje por refuerzo, así como aplicaciones prácticas como el juego y la robótica.
Este libro proporciona una visión general de la inteligencia artificial. Cubre los fundamentos de la IA, así como aplicaciones prácticas como el reconocimiento de imágenes y el procesamiento del lenguaje natural.

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