DP-100 Certification Content Preparation

Question

Whether "Optimize language models for AI applications" is a part of DP-100 exam ?

Since I see no question related to language models under https://learn.microsoft.com/en-us/credentials/certifications/azure-data-scientist/?practice-assessment-type=certification#certification-practice-for-the-exam.

Also, i see few information that language models (Gen AI) topic will only be available in exams after April 11, 2025. Is that True (or) Gen AI topics are included in the current version of the DP-100 exams.

Kindly reply

Answer 1

Yes they are. As per https://learn.microsoft.com/en-us/credentials/certifications/resources/study-guides/dp-100#optimize-language-models-for-ai-applications-2530

Optimize language models for AI applications (25–30%)

Prepare for model optimization

Select and deploy a language model from the model catalog

Compare language models using benchmarks

Test a deployed language model in the playground

Select an optimization approach

Optimize through prompt engineering and prompt flow

Test prompts with manual evaluation

Define and track prompt variants

Create prompt templates

Define chaining logic with the prompt flow SDK

Use tracing to evaluate your flow

Optimize through Retrieval Augmented Generation (RAG)

Prepare data for RAG, including cleaning, chunking, and embedding

Configure a vector store

Configure an Azure AI Search-based index store

Evaluate your RAG solution

Optimize through fine-tuning

• Prepare data for fine-tuning
• Select an appropriate base model
• Run a fine-tuning job
• Evaluate your fine-tuned model Optimize language models for AI applications (25–30%) Prepare for model optimization
  • Select and deploy a language model from the model catalog
  • Compare language models using benchmarks
  • Test a deployed language model in the playground
  • Select an optimization approach
  Optimize through prompt engineering and prompt flow
  • Test prompts with manual evaluation
  • Define and track prompt variants
  • Create prompt templates
  • Define chaining logic with the prompt flow SDK
  • Use tracing to evaluate your flow
  Optimize through Retrieval Augmented Generation (RAG)
  • Prepare data for RAG, including cleaning, chunking, and embedding
  • Configure a vector store
  • Configure an Azure AI Search-based index store
  • Evaluate your RAG solution
  Optimize through fine-tuning
  • Prepare data for fine-tuning
  • Select an appropriate base model
  • Run a fine-tuning job
  • Evaluate your fine-tuned model

If you review the change log, this has been included prior to 04/11/25

The functional groups are in bold typeface followed by the objectives within each group. The table is a comparison between the previous and current version of the exam skills measured and the third column describes the extent of the changes.

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hth

Marcin