Who should take the DP-100 exam
The Designing and Implementing a Data Science Solution on Azure (beta) DP-100 Exam certification is an internationally-recognized validation that identifies persons who earn it as possessing skilled as a Microsoft Certified Azure Data Scientist Associate. If candidates want significant improvement in career growth needs enhanced knowledge, skills, and talents. The Designing and Implementing a Data Science Solution on Azure (beta) DP-100 Exam certification provides proof of this advanced knowledge and skill. If a candidate has knowledge of associated technologies and skills that are required to pass Designing and Implementing a Data Science Solution on Azure (beta) DP-100 Exam then he should take this exam.
Knowing Associated Certification
The Microsoft DP-100 test is associated with the Microsoft Certified: Azure Data Scientist Associate certificate. It is a recently launched certification by Microsoft trying to impart the knowledge of concepts related to machine learning techniques. As a rule, earners are known to have industry-standard expertise related to evaluation and deployment models for building ML solutions. Apart from grating this noteworthy designation, the Microsoft DP-100 exam will also help the test-taker to gain some ACE college credits.
Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx
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3. Models Management and Optimization (20-25%):
- Usage of Automated Machine Learning for the creation of optimal models: This section requires your skills in retrieving the best models and getting data for Automated ML runs. It also covers competence in defining primary metrics, selecting pre-processing alternatives, and determining the algorithms to be searched. The candidates should be able to use the Automated Machine Learning from Azure ML SDK as well as Automated ML interface within Azure ML studios.
- Usage of model explainers for the interpretation of models: The learners have to demonstrate their competence in choosing model interpreters and generating the features of important data.
- Models management: This objective focuses on trained model registration and monitoring of data drift and model usage.
- Usage of hyperdrive for the tuning of hyperparameters: This domain will evaluate the ability of the applicants to define search space, primary metrics, and early termination alternatives. It also expects their skills in sampling techniques selection and model discovery that require optimal hyper-parameter values.
Microsoft DP-100 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Train and deploy models | 25-30% | - Deploy models
|
| Topic 2: Explore data and run experiments | 20-25% | - Implement pipelines
|
| Topic 3: Design and prepare a machine learning solution | 20-25% | - Design a machine learning solution
|
| Topic 4: Optimize language models for AI applications | 25-30% | - Optimize with Retrieval Augmented Generation
|
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