{"id":3077,"date":"2026-08-10T09:01:46","date_gmt":"2026-08-10T09:01:46","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-ml-in-production-from-data-scientist-to-ml-engineer-2024-9\/"},"modified":"2026-08-10T09:01:46","modified_gmt":"2026-08-10T09:01:46","slug":"udemy-ml-in-production-from-data-scientist-to-ml-engineer-2024-9","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-ml-in-production-from-data-scientist-to-ml-engineer-2024-9\/","title":{"rendered":"Udemy \u2013 ML in Production: From Data Scientist to ML Engineer 2024-9"},"content":{"rendered":"
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Descriptions<\/h2>\n

ML in Production: From Data Scientist to ML Engineer, This comprehensive course is designed to equip you with the essential skills and knowledge required to transform Machine Learning (ML) models developed in Jupyter notebooks into fully operational, production-ready microservices. As a student of this course, you\u2019ll delve deep into the intricacies of taking an ML model from a mere concept in a notebook to a scalable and efficient application that thrives in a real-world production environment. Throughout the course, you will learn to bridge the gap between data science and software engineering, elevating your ML capabilities from theoretical models to practical applications. The course starts with an introduction to the fundamentals of microservices architecture, setting the stage for understanding how ML models fit into larger software systems.<\/p>\n

You will then learn how to effectively containerize your ML models using Docker, a critical skill in today\u2019s software development landscape. This includes hands-on training on creating Docker images, managing containers, and understanding the principles of container orchestration. API development is another cornerstone of this course. You will be guided through the process of designing and implementing robust APIs that allow your ML models to communicate seamlessly with other applications. This includes practical training on handling API requests and responses, along with ensuring the security and scalability of your APIs. Moreover, the course covers deployment strategies, focusing on practical, real-world challenges. You will engage in setting up continuous integration and continuous delivery (CI\/CD) pipelines, managing version control, and learning the best practices for monitoring and maintaining your models once they are deployed.<\/p>\n

What you\u2019ll learn<\/h3>\n