Empower Your Data Science Journey: From Exploration to Certification in Azure Machine Learning
Key Features
? Offers deep dives into key areas such as data preparation, model training, and deployment, ensuring you master each concept.
? Covers all exam objectives in detail, ensuring a thorough understanding of each topic required for the DP-100 certification.
? Includes hands-on labs and practical examples to help you apply theoretical knowledge to real-world scenarios, enhancing your learning experience.
Book Description
Ultimate Azure Data Scientist Associate (DP-100) Certification Guide is your essential resource for achieving the Microsoft Azure Data Scientist Associate certification. This guide covers all exam objectives, helping you design and prepare machine learning solutions, explore data, train models, and manage deployment and retraining processes.
The book starts with the basics and advances through hands-on exercises and real-world projects, to help you gain practical experience with Azure's tools and services. The book features certification-oriented Q&A challenges that mirror the actual exam, with detailed explanations to help you thoroughly grasp each topic. Perfect for aspiring data scientists, IT professionals, and analysts, this comprehensive guide equips you with the expertise to excel in the DP-100 exam and advance your data science career.
What you will learn
? Design and prepare effective machine learning solutions in Microsoft Azure.
? Learn to develop complete machine learning training pipelines, with or without code.
? Explore data, train models, and validate ML pipelines efficiently.
? Deploy, manage, and optimize machine learning models in Azure.
? Utilize Azure's suite of data science tools and services, including Prompt Flow, Model Catalog, and AI Studio.
? Apply real-world data science techniques to business problems.
? Confidently tackle DP-100 certification exam questions and scenarios.
Table of Contents
1. Introduction to Data Science and Azure
2. Setting Up Your Azure Environment
3. Data Ingestion and Storage in Azure
4. Data Transformation and Cleaning
5. Introduction to Machine Learning
6. Azure Machine Learning Studio
7. Model Deployment and Monitoring
8. Embracing AI Revolution Azure
9. Responsible AI and Ethics
10. Big Data Analytics with Azure
11. Real-World Applications and Case Studies
12. Conclusion and Next Steps
Index
