1- Create an Azure AI Search solution

• • Create an Azure AI Search solution
• • Develop a search application

2- Create a custom skill for Azure AI Search

• • Implement a custom skill for Azure AI Search
• • Create a custom text classification skill
• • Create a machine learning custom skill

3- Create a knowledge store with Azure AI Search

• • Create a knowledge store from an Azure AI Search pipeline
• • View data in projections in a knowledge store

4- Implement advanced search features in Azure AI Search

• • Improve the ranking of a document with term boosting
• • Improve the relevance of results by adding scoring profiles
• • Improve an index with analyzers and tokenized terms
• • Enhance an index to include multiple languages
• • Improve search experience by ordering results by distance from a given reference point

5- Search data outside the Azure platform in Azure AI Search using Azure Data Factory

• • Use Azure Data Factory to copy data into an Azure AI Search Index
• • Use the Azure AI Search push API to add to an index from any external data source

6- Maintain an Azure AI Search solution

• • Familiarity with Microsoft Azure
• • Application development experience with C# or Python
• • Experience of building a basic search solution with Azure AI Search. If you've not completed the Create an Azure AI Search solution
  module, you should do so before starting this module.

7- Perform search reranking with semantic ranking in Azure AI Search

• • Describe semantic ranking
• • Set up semantic ranking
• • Perform semantic ranking on an index

8- Perform vector search and retrieval in Azure AI Search

• • Describe vector search
• • Describe embeddings
• • Run vector search queries using the REST API