Production Machine Learning Systems - Español from Coursera

What's inside

Syllabus

Introducción al aprendizaje automático avanzado en Google Cloud

En este módulo, se verá un avance de los temas que se abordan en el curso y cómo usar Qwiklabs para completar cada uno de tus labs con Google Cloud.

Arquitectura de sistemas de AA de producción

En este módulo, se explorará qué más necesita hacer un sistema de AA de producción y cómo satisfacer esas necesidades. Verás cómo tomar decisiones de diseño importantes y de alto nivel en torno al entrenamiento y la entrega del modelo para obtener el perfil de rendimiento correcto para tu modelo.

Diseño de sistemas de AA adaptables

En este módulo, aprenderás a reconocer las formas en que el modelo depende de los datos, a tomar decisiones de ingeniería conscientes con el costo, a determinar cuándo revertir los modelos a versiones anteriores, a depurar las causas del comportamiento observado del modelo y a implementar una canalización que sea inmune a un tipo de dependencia.

Diseño de sistemas de AA de alto rendimiento

En este módulo, identificarás las consideraciones de rendimiento para los modelos de aprendizaje automático. No todos los modelos de aprendizaje automático son idénticos. En el caso de ciertos modelos, el enfoque está en mejorar el rendimiento de E/S y, en el caso de otros, está en obtener una mayor velocidad de procesamiento.

Creación de sistemas híbridos de AA

Comprende las herramientas y los sistemas disponibles, y cuándo debes aprovechar los modelos híbridos de aprendizaje automático.

Resumen

Vínculos a los PDF de todos los módulos

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Especializado en el diseño de sistemas de aprendizaje automático de alto rendimiento y adaptables

Impartido por Google Cloud Training, expertos reconocidos en el campo del aprendizaje automático

Cubre temas esenciales para la implementación de sistemas de aprendizaje automático en producción

Incluye laboratorios prácticos para reforzar los conceptos y habilidades aprendidas

Dirigido a ingenieros, científicos de datos y profesionales de aprendizaje automático que buscan mejorar sus habilidades en el diseño e implementación de sistemas de aprendizaje automático robustos

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 Production Machine Learning Systems - Español with these activities:

Revisión y organización de materiales del curso

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Organiza y revisa los materiales del curso para mejorar la retención y la comprensión.

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Recopila y organiza notas, tareas, cuestionarios y exámenes
Resalta y resume los conceptos clave

Contribuir a proyectos de AA de código abierto

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Contribuye a la comunidad de AA participando en proyectos de código abierto para ampliar tu experiencia y conocimientos.

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Identifica proyectos de AA de código abierto que te interesen
Examina el código, identifica errores y sugiere mejoras
Colabora con otros desarrolladores para implementar cambios

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Career center

Learners who complete Production Machine Learning Systems - Español will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models. This course provides a comprehensive overview of the machine learning lifecycle, from data collection to model deployment. The course covers topics such as model selection, hyperparameter tuning, and model evaluation, which are all essential for building and deploying successful machine learning models. Additionally, the course provides hands-on experience with Google Cloud Platform, which is one of the leading platforms for developing and deploying machine learning models.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

Data Analysts are responsible for collecting, analyzing, and interpreting data to help businesses make informed decisions. This course provides a solid foundation in the principles and practices of machine learning, which is a key skill for Data Analysts. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models. Additionally, the course provides hands-on experience with Google Cloud Platform, which is one of the leading platforms for developing and deploying machine learning models.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists are responsible for collecting, analyzing, and interpreting data to help businesses make informed decisions. This course provides a solid foundation in the principles and practices of machine learning, which is a key skill for Data Scientists. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models. Additionally, the course provides hands-on experience with Google Cloud Platform, which is one of the leading platforms for developing and deploying machine learning models.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers are responsible for designing, developing, and maintaining software applications. This course may be useful for Software Engineers who want to learn more about machine learning and how to apply it to their work. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models. Additionally, the course provides hands-on experience with Google Cloud Platform, which is one of the leading platforms for developing and deploying machine learning models.

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Information Security Analyst

Information Security Analysts are responsible for protecting a business's information systems from unauthorized access or use. This course may be useful for Information Security Analysts who want to learn more about machine learning and how it can be used to improve information security. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models.

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Financial Analyst

Financial Analysts are responsible for analyzing financial data and making recommendations to investors. This course may be useful for Financial Analysts who want to learn more about machine learning and how it can be used to improve investment performance. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models.

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Product Manager

Product Managers are responsible for defining and managing the development of products. This course may be useful for Product Managers who want to learn more about machine learning and how it can be used to improve products. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models.

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Operations Manager

Operations Managers are responsible for overseeing the day-to-day operations of a business. This course may be useful for Operations Managers who want to learn more about machine learning and how it can be used to improve operational efficiency. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models.

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Risk Manager

Risk Managers are responsible for identifying and mitigating risks to a business. This course may be useful for Risk Managers who want to learn more about machine learning and how it can be used to improve risk management. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models.

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Customer Success Manager

Customer Success Managers are responsible for ensuring that customers are satisfied with a company's products or services. This course may be useful for Customer Success Managers who want to learn more about machine learning and how it can be used to improve customer satisfaction. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models.

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Compliance Officer

Compliance Officers are responsible for ensuring that a business complies with all applicable laws and regulations. This course may be useful for Compliance Officers who want to learn more about machine learning and how it can be used to improve compliance. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models.

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Marketing Manager

Marketing Managers are responsible for developing and executing marketing campaigns. This course may be useful for Marketing Managers who want to learn more about machine learning and how it can be used to improve marketing campaigns. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models.

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Data Governance Analyst

Data Governance Analysts are responsible for ensuring that data is used in a consistent and ethical manner. This course may be useful for Data Governance Analysts who want to learn more about machine learning and how it can be used to improve data governance. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models.

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Sales Manager

Sales Managers are responsible for leading and motivating sales teams. This course may be useful for Sales Managers who want to learn more about machine learning and how it can be used to improve sales performance. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models.

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Business Analyst

Business Analysts are responsible for analyzing business needs and recommending solutions to improve efficiency and profitability. This course may be useful for Business Analysts who want to learn more about machine learning and how it can be used to improve business outcomes. The course covers topics such as data preprocessing, model training, and model evaluation, which are all essential for building and deploying successful machine learning models.

See salaries and explore the career path for Business Analyst