Python Essentials for MLOps is a course designed to provide learners with the fundamental Python skills needed to succeed in an MLOps role. This course covers the basics of the Python programming language, including data types, functions, modules and testing techniques. It also covers how to work effectively with data sets and other data science tasks with Pandas and NumPy. Through a series of hands-on exercises, learners will gain practical experience working with Python in the context of an MLOps workflow. By the end of the course, learners will have the necessary skills to write Python scripts for automating common MLOps tasks. This course is ideal for anyone looking to break into the field of MLOps or for experienced MLOps professionals who want to improve their Python skills.
Ofrecido Por
Python Essentials for MLOps
Duke UniversityAcerca de este Curso
11.723 vistas recientes
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
Some experience in working with Python, Git for version control, Docker for containerization and Kubernetes for deployment and scaling.
Aprox. 22 horas para completar
Inglés (English)
Qué aprenderás
Work with logic in Python, assigning variables and using different data structures.
Write, run and debug tests using Pytest to validate your work.
Interact with APIs and SDKs to build command-line tools and HTTP APIs to solve and automate Machine Learning problems.
Habilidades que obtendrás
- Information Engineering
- MLOps
- Machine Learning
- Python Programming
- Test Automation
Fechas límite flexibles
Restablece las fechas límite en función de tus horarios.
Certificado para compartir
Obtén un certificado al finalizar
100 % en línea
Comienza de inmediato y aprende a tu propio ritmo.
Nivel intermedio
Some experience in working with Python, Git for version control, Docker for containerization and Kubernetes for deployment and scaling.
Aprox. 22 horas para completar
Inglés (English)
Ofrecido por
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Testing in Python
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Preguntas Frecuentes
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