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LinkedIn - AI Toolkit Essentials for Visual Studio Code 2025-8
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Course content
Sections:
10
•
Activities:
1
•
Resources:
35
- Announcements
- 01 Streamline AI application development with AI Toolkit
- 02 What you need to know
- 01 What is AI Toolkit for VS Code
- 02 Microsoft guidelines for responsible AI app development
- 03 Installing AI Toolkit for Visual Studio Code
- 04 Setting up ONNX models
- 01 Overview of the catalogs
- 02 Authenticating with external providers
- 03 Adding external models to AI Toolkit
- 04 Converting models using ONNX
- 05 Importing ONNX models into AI Toolkit with Model Creator
- 01 Opening playgrounds
- 02 Changing the model parameters
- 03 Comparing models
- 01 What is prompt engineering
- 02 How many Rs are in strawberry
- 03 Building a prompt template
- 04 Running a prompt template
- 01 Overview of bulk run
- 02 Using generated data with bulk run
- 03 Using a custom JSONL file
- 01 Overview of evaluation
- 02 Using evaluation with the default dataset
- 03 Using visualization of data
- 04 Working with the custom dataset
- 05 Adjusting the model with bulk run and evaluation
- 06 Adding a custom evaluator Initial setup
- 07 Adding a custom evaluator Finish and test
- 01 Introduction to fine tuning
- 02 Setting up a machine for local fine tuning
- 03 Starting local fine tuning
- 04 Running the fine tuning
- 05 Testing your fine tuned model
- 01 Where to go from here
- Document