Download Coursera – MLOps | Machine Learning Operations Specialization 2023-12

Description

MLOps | Machine Learning Operations Specialization, MLOPS machine learning steps and processes course is published by Coursera Academy. This comprehensive course set is perfect for people with programming knowledge, such as software developers, data scientists, and researchers. You’ll gain critical MLOps skills including using Python and Rust, using GitHub Copilot to increase productivity, and using platforms like Amazon SageMaker, Azure ML, and MLflow. You will also learn how to configure large language models (LLMs) using Hugging Face and understand the deployment of stable and efficient binary models in the ONNX format, preparing you for success in the ever-evolving field of MLOps. he does.

Through this series, you can learn skills for different career paths: 1. Data Science – Analyze and interpret complex data sets, develop ML models, implement data management, and make data-driven decisions. 2. Machine learning engineering – designing, building and deploying ML models and systems to solve real-world problems. 3. Architect Cloud ML Solutions – Use cloud platforms such as AWS and Azure to architect and manage ML solutions in a scalable and cost-effective manner. 4. Artificial Intelligence (AI) Product Management – Bridge the gap between business, engineering and data science teams to deliver impactful AI/ML products.

What you will learn

Python principles, MLOps principles and data management for building and deploying ML models in production environments.
Use Amazon/AWS, Azure, MLflow, and Hugging Face services for end-to-end machine learning, pipeline, and API development solutions.
Configure and extend large language models (LLMs) and container models using the ONNX format with Hugging Face.
Design a complete MLOps pipeline with MLflow, manage projects, models and trace system features.

MLOps Machine Learning Operations Specialization course specifications

Publisher: Coursera
teacher : Noah Gift
English language
Training level: advanced
Number of courses: 4
Duration of training: 6 months, including 5 hours of work per week

Chapters of the MLOps Machine Learning Operations Specialization course

Course prerequisites

You should have basic Python programming experience, familiarity with computer science concepts, and a strong foundation in mathematics (especially linear algebra and statistics).