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Course Outline
Introduction to AI and Its Role in IT Support
- Core AI concepts: machine learning, Natural Language Processing (NLP), and generative AI.
- The impact of AI on transforming technical support workflows.
- Survey of popular AI platforms suitable for IT teams.
Prompt Engineering for Support Scenarios
- Crafting effective prompts for generating support ticket responses.
- Structuring prompts to ensure consistent and accurate AI outputs.
- Iterative refinement of AI-generated answers for improved quality.
AI-Powered Ticket Automation and Incident Management
- Utilising AI to classify and prioritise incoming support tickets.
- Automating the drafting of routine responses using Large Language Models (LLMs).
- Seamlessly integrating AI with existing ticketing systems and workflows.
Automated Generation of Technical Documentation
- Transforming troubleshooting notes into structured documentation.
- Generating step-by-step guides and solution articles with AI assistance.
- Efficiently maintaining and updating knowledge base entries.
Building Internal Knowledge Bases with AI
- Organising support content into easily searchable knowledge bases.
- Using AI to surface relevant articles during the ticket resolution process.
- Managing version control and governance of AI-generated documentation.
Internal Virtual Assistants and Chatbots for IT Support
- Designing conversation flows for chatbots addressing common IT issues.
- Building and testing a support chatbot without requiring coding skills.
- Deploying chatbots to enable employee self-service and handle FAQs.
Predictive Analytics for Fault Detection and Prevention
- Identifying patterns within historical incident data.
- Using AI to detect early warning signs of potential system failures.
- Setting up automated alerts and proactive maintenance triggers.
Information Security and Responsible AI Use
- Data privacy considerations when employing AI in support functions.
- Preventing data leakage and securing AI tool configurations.
- Ethical guidelines and organisational policies for AI usage.
Measuring Impact and Continuous Improvement
- Key metrics for AI-driven support: resolution time and Customer Satisfaction (CSAT).
- Gathering feedback to refine AI responses and documentation quality.
- Developing a roadmap for scaling AI across IT operations.
Capstone Project: End-to-End AI Support Workflow
- Designing an AI-assisted support pipeline for a realistic scenario.
- Constructing documentation and chatbot components for the project.
- Presenting the solution and receiving peer feedback.
Requirements
- Fundamental understanding of IT support workflows and ticketing systems.
- Familiarity with standard office and productivity software.
- No prior experience in AI or programming is required.
Target Audience
- IT support technicians and help desk personnel.
- Systems administrators and network monitoring staff.
- Technology team members responsible for user support and troubleshooting.
- IT professionals seeking to incorporate AI into their daily support routines.
16 Hours
