Course Details
Azure Machine Learning with AzureML SDK: DP-100
Data Science
Created On
September 15, 2023Description
Azure Machine Learning is a robust cloud-based platform provided by Microsoft that empowers data scientists, developers, and organizations to build, train, deploy, and manage machine learning models and AI solutions efficiently. It offers a comprehensive suite of tools and services designed to simplify the end-to-end machine learning lifecycle, from data preparation and model development to deployment and monitoring.
Overview
This course is designed to prepare you for the DP-100 certification exam by providing hands-on experience with Azure Machine Learning using the AzureML SDK. You will learn how to set up a **Machine Learning workspace, create datastores and datasets, run experiments, train models, and automate machine learning workflows**.
Features
- Course material
- Course resources
- Real-world Scenarios
- On demand recorded videos
- Practical exercises
- Quizzes
- Assignments
- Certification Preparation
What you'll learn
- AzureML SDK Mastery
- Datastore and Dataset Proficiency
- Experimentation and Model Training
- Compute Resource Management
- Automation with Pipelines
- Advanced Topics
- Custom Python Script Integration
- Real-world Problem Solving
- Certification Readiness
- Collaborative Project Experience
Prerequisites
Curriculum
- 8 modules
Understanding the AzureML SDK
Setting up Your Development Environment
Creating an AzureML Workspace
Creating and Registering a Datastore
Managing Datastore Access
Creating and Registering Datasets
Working with Datasets in Python
Setting Up Experimentation Environment
Creating and Running Experiments
Monitoring Experiment Runs
Managing Experiment Artifacts
Overview of AzureML Compute
Creating and Managing Compute Clusters
Scaling Compute Resources
Introduction to AzureML Pipelines
Defining and Creating Pipelines
Automating Model Training with Pipelines
Scheduling and Monitoring Pipeline Runs
Custom Environment Configuration
Hyperparameter Tuning
Model Deployment Strategies
Model Interpretability and Explainability
Building and Packaging Python Scripts
Integrating Custom Python Code
Leveraging External Libraries
Debugging and Troubleshooting
Exploring Real-world Machine Learning Use Cases
Analyzing DP-100 Sample Scenarios
Developing End-to-End Solutions
Instructors
Skoliko Faculty
- 8 Modules
- 10 Hours
- Data Science
Login to Purchase the Course