Create Machine Learning Models in Microsoft Azure

via Coursera

Overview

Title: Create Machine Learning Models in Microsoft Azure

Description: Machine learning forms the foundation for predictive modeling and artificial intelligence. In this course, you will learn both the underlying concepts and practical skills needed to build models using the most common machine learning tools. The curriculum covers core principles of machine learning, training, evaluation, and deployment of models using Azure. It is designed to prepare you for roles in planning and creating environments for data science workloads on Azure, running data experiments, and training predictive models. Furthermore, you will manage, optimize, and deploy machine learning models into production.

You'll gain hands-on experience with classical machine learning models, exploratory data analysis, and customizing architectures. Course materials include easy-to-understand conceptual content and interactive Jupyter notebooks. Ideal for those with some background in machine learning or strong mathematical skills, this course moves quickly to leverage tools like scikit-learn, TensorFlow, and PyTorch. It also provides familiarity with Azure ML and Azure Databricks, making it a great starting point for further studies in deep learning and neural networks.

This path consists of five courses designed to help you prepare for the Exam DP-100: Designing and Implementing a Data Science Solution on Azure. Passing this certification exam will validate your ability to operate machine learning solutions at cloud scale using Azure. The specialization will leverage your existing Python and machine learning knowledge to cover data ingestion, preparation, model training, deployment, and solution monitoring in Microsoft Azure. Each course aligns with the skills and concepts measured by the exam.

University: Provider: Coursera

Categories: Machine Learning Courses, Microsoft Azure Courses, Deep Learning Courses, TensorFlow Courses, scikit-learn Courses, PyTorch Courses