Short Course
Artificial Intelligence
AI Agents for Productivity
Overview
This comprehensive course is tailored for general non-technical staff looking to enhance their productivity and automation skills using AI agents. By exploring core concepts, real-world applications, and hands-on activities, participants will gain a deep understanding of browser-based AI automation, no-code AI tools, and office productivity assistants. They will learn how to deploy AI agents to automate tasks, streamline workflows, and enhance business efficiency – without any programming knowledge. Additionally, the course examines the ethical considerations and limitations of AI agents, ensuring participants are prepared to responsibly integrate AI tools into their professional environments. Through interactive case studies, a hands-on AI workflow activity, and a collaborative group project, learners will leave with practical skills to leverage AI agents effectively in their daily work.
Who Should Attend
This course is intended for
- General office staff looking to automate repetitive tasks and improve efficiency using AI agents
- Administrative professionals who want to integrate AI tools for workflow automation and task management
- Business users and managers seeking to streamline processes with no-code AI solutions
- Customer service and marketing teams interested in automating emails, content generation, and customer interactions
- Non-technical professionals eager to explore AI-powered automation without programming knowledge
Pre-requisites
- No pre-requisite required
- Participants are required to bring their own laptop PC or MacBook for the practical hands-on portions of the workshop
1 Day
8 Hours
Level
Beginner
What You Will Learn
Understand AI Agent Capabilities and Use Cases
Explain what AI agents are, how they differ from traditional AI tools, and identify suitable use cases across different business functions and industries.
Identify Opportunities for AI Agent Adoption
Evaluate existing work processes to recognize repetitive, time-consuming, or decision-based tasks that can be enhanced or automated using AI agents.
Leverage AI Agents for Task Automation
Use AI agents to automate routine activities such as information gathering, content generation, scheduling, reporting, and customer support to improve productivity.
Implement AI Agents in Workflows Without Programming
Configure and deploy AI agents using no-code or low-code platforms, enabling seamless integration into existing business workflows without requiring software development skills.
Design AI-Driven Solutions for Real-World Scenarios
Develop practical AI agent solutions that address business challenges by combining multiple AI capabilities, tools, and workflow automation techniques.
Apply Best Practices for AI Governance and Responsible Use
Demonstrate an understanding of ethical considerations, data privacy, security, human oversight, and governance principles when deploying AI agents in organizational settings.
Evaluate and Optimize AI Agent Performance
Assess the effectiveness of AI agents by measuring outcomes, identifying areas for improvement, refining prompts and workflows, and ensuring continuous enhancement of AI-driven processes.
Course Outline
Day 1
- Introduction to AI Agents
- Overview of AI agents and their applications
- Types of AI agents (browser-based, app creation, office productivity, desktop automation)
- Case studies of AI-driven automation in business
- Automating Tasks with Browser-Based AI Agents
- Using AI agents for autonomous task execution
- Automating email and marketing campaigns
- AI-driven online purchases and bookings
- Enhancing Productivity with AI Agents
- Office task automation with AI agents
- Document and report generation with AI
- Streamlining workflow with AI-powered automation tools
- AI Automation and Workflow Design
- Setting up an AI-powered workflow
- Designing an AI-driven business automation solution
- Best practices for AI adoption in non-technical roles
Trainers Profile
Victor Tan
Victor Tan brings a remarkably interdisciplinary academic and professional profile to his current role as a PhD scholar in Artificial Intelligence at Murdoch University. He holds multiple advanced degrees from Nanyang Technological University, including a Master of Science in Information Systems.