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

Description

MLOPS Machine Learning Operations Specialization, This comprehensive course series is perfect for individuals with programming knowledge such as software developers, data scientists, and researchers. You will gain critical MLOPS skills, including the use of Python and Rust, using GitHub Copilot to increase productivity, and leveraging platforms such as Amazon SageMaker, Azure ML, and MLflow. You will also learn how to fine-tune large language models (LLMs) using Hugging Face and understand the deployment of sustainable and efficient binary embedded models in ONNX format, which will prepare you for success in the constantly evolving field of MLOps. This comprehensive course series is perfect for individuals with programming knowledge such as software developers, data scientists, and researchers.

You will gain critical MLOps skills, including the use of Python and Rust, using GitHub Copilot to increase productivity, and leveraging platforms like Amazon SageMaker, Azure ML, and MLflow. You will also learn how to fine-tune large language models (LLMs) using Hugging Face and understand the deployment of sustainable and efficient binary embedded models in ONNX format, which will prepare you for success in the constantly evolving field of MLOps. Through this series, you will begin to learn skills for a variety of career paths: 1. Data Science – Analyze and interpret complex data sets, develop ML models, apply data management, and drive data-driven decision making. 2. Machine Learning Engineering – Design, build, and deploy ML models and systems to solve real-world problems. 3. Cloud ML Solutions Architect – Leverage cloud platforms like AWS and Azure to architect and manage ML solutions in a scalable, 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

Master Python fundamentals, MLOps principles, and data management to build and deploy ML models in production environments.
Use Amazon SageMaker/AWS, Azure, MLflow, and Hugging Face for end-to-end ML solutions, pipeline building, and API development.
Fine-tune and deploy large language models (LLMs) and containerized models using the ONNX format with Hugging Face.
Design a complete MLOps pipeline with MLflow, management projects, models, and tracking system features.

Uniqueness of the MLOps Machine Learning Operations Expertise

Publisher: Coursera
Teacher: Noah Poison
language English
Level: Expert
Number of courses: 4
Duration: 6 months, 5 hours a week

Content of the MLOps Machine Learning Operations Specialization

MLOps _ Machine Learning Operations Expertise

Requirements

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