This course focuses on the design and implementation of intelligent troubleshooting agents. You will learn to create AI-powered agents that can diagnose and resolve issues autonomously. The course covers natural language processing, decision-making algorithms, and best practices in AI agent development. By the end of this course, you will be able to: 1. Define, describe, and design the architecture of an intelligent troubleshooting agent. 2. Implement natural language processing techniques for user interaction. 3. Develop decision-making algorithms for problem diagnosis and resolution. 4. Optimize and evaluate the performance of AI-based troubleshooting agents. To be successful in this course, you should have intermediate programming knowledge of Python, plus experience with AI & ML infrastructure and core algorithms and techniques, including approaches using pretrained large-language models (LLMs). Familiarity with statistics is also recommended.
Walkthrough: Coding a troubleshooting agent in Python (Optional)
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Skills You'll Learn
Prompt Engineering, Artificial Intelligence and Machine Learning (AI/ML), Performance Tuning, Natural Language Processing, Generative AI Agents, Test Case, Agentic systems, Debugging, Human Computer Interaction, Machine Learning, Large Language Modeling, Artificial Intelligence, Python Programming
From the lesson
Implementing the troubleshooting agent
Taught By
Microsoft