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Certification Path

The Microsoft Certified Azure Data Scientist Associate Certification includes only one DP-100 Exam.

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Skills measured

Run experiments and train models (20–25%)
Deploy and operationalize machine learning solutions (35–40%)
Manage Azure resources for machine learning (25–30%)
Implement responsible machine learning (5–10%)

Microsoft DP-100 Exam Syllabus Topics:

Topic	Details
Topic 1	Design and prepare a machine learning solution: This topic equips Microsoft Data Scientists with skills to design comprehensive machine learning solutions tailored to business needs. It delves into managing resources and assets in the Azure Machine Learning workspace, offering insights into organizing computational and storage resources effectively.
Topic 2	Explore data, and run experiments: This section focuses on enabling Microsoft Data Scientists to explore datasets and experiment with model configurations effectively. By leveraging automated machine learning, participants explore optimal models and streamline custom model training with notebooks. It evaluates skills in automating hyperparameter tuning to refine models for improved performance.
Topic 3	Optimize language models for AI applications: This advanced topic teaches Microsoft Data Scientists to enhance AI applications by optimizing language models. Skills are developed in preparing models for optimization, prompt engineering, and employing techniques like Prompt Flow and Retrieval Augmented Generation (RAG). Additionally, fine-tuning strategies are explored to maximize model performance.
Topic 4	Train and deploy models: In this topic, Microsoft Data Scientists develop the expertise to execute training scripts and implement efficient training pipelines. Participants learn to manage models effectively and deploy them using Azure services. The focus is on assessing proficiency in training processes, deployment strategies, and lifecycle management of machine learning models to ensure production-ready solutions that align with organizational goals.

Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx

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Microsoft Designing and Implementing a Data Science Solution on Azure Sample Questions:

Question #1

You are authoring a notebook in Azure Machine Learning studio.
You must install packages from the notebook into the currently running kernel. The installation must be limited to the currently running kernel only.
You need to install the packages.
Which magic function should you use?

A. %pip
B. %load
C. !conda
D. !pjp

Reveal Solution Discussion 0

Correct Answer: A 🗳️

Question #2

You are performing clustering by using the K-means algorithm.
You need to define the possible termination conditions.
Which three conditions can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

A. The residual sum of squares (RSS) falls below a threshold.
B. A fixed number of iterations is executed.
C. The sum of distances between centroids reaches a maximum.
D. The residual sum of squares (RSS) rises above a threshold.
E. Centroids do not change between iterations.

Reveal Solution Discussion 0

Correct Answer: A,B,E 🗳️

Explanation: Only visible for BootcampPDF members. You can sign-up / login (it's free).

Question #3

You plan to run a script as an experiment using a Script Run Configuration. The script uses modules from the scipy library as well as several Python packages that are not typically installed in a default conda environment.
You plan to run the experiment on your local workstation for small datasets and scale out the experiment by running it on more powerful remote compute clusters for larger datasets.
You need to ensure that the experiment runs successfully on local and remote compute with the least administrative effort.
What should you do?

A. Create a config. yaml file defining the conda packages that are required and save the file in the experiment folder.
B. Always run the experiment with an Estimator by using the default packages.
C. Do not specify an environment in the run configuration for the experiment. Run the experiment by using the default environment.
D. Create a virtual machine (VM) with the required Python configuration and attach the VM as a compute target. Use this compute target for all experiment runs.
E. Create and register an Environment that includes the required packages. Use this Environment for all experiment runs.

Reveal Solution Discussion 0

Correct Answer: E 🗳️

Explanation: Only visible for BootcampPDF members. You can sign-up / login (it's free).

Question #4

You have a deployment of an Azure OpenAI Service base model. You plan to fine-tune the model.
You need to prepare a file that contains training data for multi-turn chat. Which file encoding method should you use?