Microsoft - DP-100 Certification Exam Details, Questions and Answers

Certification Provider

Microsoft

Exam

DP-100: Designing and Implementing a Data Science Solution on Azure

Number of questions (in our database)

316

Updated on

01 June 2024

Browse 316 Questions

Topics

Data Preparation and Processing Designing and Implementing Data Science Solutions Business Understanding and Communication Deployment and Monitoring Modeling

Microsoft's DP-100: Designing and Implementing a Data Science Solution on Azure Certification Exam

Exam Details

Microsoft's DP-100 exam is part of the Microsoft Certified: Azure Data Scientist Associate certification. This certification validates your ability to apply Azure's data science techniques and machine learning algorithms to gain insights from your data.

Importance of the DP-100 Exam

The DP-100 exam is an important milestone for any data professional aiming to prove their skills in using Microsoft Azure for data science and machine learning tasks. By passing this exam, you demonstrate to employers that you are capable of designing and implementing data science solutions on one of the most widely utilized cloud platforms in the world.

Technical Details

The exam tests various technical skills, including knowledge of Azure Machine Learning Service and Azure Databricks, and using Python and R for data science tasks. It also evaluates candidate's understanding of how to clean and transform data, and how to implement and run machine learning models using Azure services.

Measured Skills

Setting up an Azure Machine Learning workspace
Running experiments and training models
Optimizing and managing models
Deploying and consuming models

Preparation Advices

To prepare for the Microsoft DP-100 exam, it is recommended to gain hands-on experience with Azure Machine Learning, Python, and R, and to familiarize yourself with techniques for data transformation and model optimization. Microsoft provides online learning paths and practice tests that can help you prepare for the exam.

Exam Topics

Data Preparation and Processing (15% - 20%)
- Preparing data for modeling
- Exploring and transforming data
- Cleaning and validating data
- Handling missing data
- Scaling and normalizing data
- Sampling and partitioning data
- Optimizing data processing
- Implementing data pipelines
Designing and Implementing Data Science Solutions (15% - 25%)
- Identifying business requirements
- Defining data science goals
- Selecting appropriate Azure services
- Designing data storage and processing solutions
- Designing data integration and orchestration solutions
- Designing and implementing machine learning models
- Designing and implementing data visualization solutions
- Designing and implementing big data processing solutions
- Designing and implementing real-time processing solutions
- Designing and implementing AI solutions
Business Understanding and Communication (10% - 15%)
- Understanding business requirements
- Translating business goals into data science solutions
- Communicating findings and insights
- Collaborating with stakeholders
Deployment and Monitoring (15% - 20%)
- Creating and deploying containers
- Creating and deploying web services
- Creating and deploying pipelines
- Monitoring and troubleshooting solutions
- Implementing security and compliance
- Managing and optimizing resources
Modeling (20% - 25%)
- Selecting appropriate models
- Training and evaluating models
- Tuning and optimizing models
- Interpreting and explaining models
- Ensembling and stacking models
- Deploying and managing models
- Monitoring and retraining models