This unit guides students through practical use of generative AI tools (e.g., Copilot, GitHub Copilot, Tabnine) and associated workflows to support user experience, content, and product development. Students will practice prompt engineering, data grooming, visual asset generation, agent testing, and evaluate model limitations and responsible-AI considerations to prepare for advanced integration and deployment topics in subsequent units.
Learning Objectives
- Analyze the capabilities and limitations of AI assistants and models (including hallucination risks and responsible-AI concerns) to determine appropriate use in team and UX contexts.
- Apply data management and prompt-engineering techniques to produce targeted outputs for visuals, slides, reports, code generation, and personalized user experiences.
- Demonstrate the process of creating, testing, and refining conversational agents and Copilot plugins, including retrieval of domain-specific answers (e.g., HR) and iterative editing for quality.
- Evaluate model selection, underlying architectures (e.g., transformers), and hardware considerations (e.g., DLPs) to inform UX decisions, budgeting, localization, SEO strategies, and career adaptation planning.
Curriculum
- 1 Section
- 50 Lessons
- 30 hours
Expand all sectionsCollapse all sections
- Unit 2 — Applied Generative AI Tools and Workflows50
- 1.1Signing Up for Copilot20 mins
- 1.2Managing Data for Targeted Impact on Outputs20 mins
- 1.3Getting a Visual Assist from GenAI20 mins
- 1.4Working with Data20 mins
- 1.5Designing Slides with Designer20 mins
- 1.6Understanding the Limitations of Copilot in Teams20 mins
- 1.7Retrieving Smart Answers for HR20 mins
- 1.8Understanding Different Models for Change and Transition20 mins
- 1.9Deciding Whether AI Hallucinations Are a Feature or a Bug20 mins
- 1.10Generating Precise Prompts20 mins
- 1.11Exploring an Approach for Creating Visual Assets with AI20 mins
- 1.12Developing White Papers and Reports Using Generative AI20 mins
- 1.13Strategies for SEO Success in the AI Era20 mins
- 1.14Adopting Core Strategies for Localization20 mins
- 1.15Exchanging Ideas20 mins
- 1.16Making Humans More Capable20 mins
- 1.17Changing the Structure of Education20 mins
- 1.18Moving from Information Search to Knowledge Assistants20 mins
- 1.19Getting a Handle on Budgeting20 mins
- 1.20Thinking about Estate Planning20 mins
- 1.21Helping with Syntax20 mins
- 1.22Exploring Tabnine20 mins
- 1.23Chatting with Github Copilot20 mins
- 1.24Generating Code from an SRS20 mins
- 1.25Introducing AI Personalization20 mins
- 1.26Enhancing Brand Building20 mins
- 1.27Benefitting from Conversational AI Chatbots for Customer Service20 mins
- 1.28Testing and Editing Your Agent20 mins
- 1.29Creating a Copilot Plugin20 mins
- 1.30Considering AI Uses20 mins
- 1.31Manicuring the Data20 mins
- 1.32Working with Deep Learning Processors (DLPs)20 mins
- 1.33Understanding Transformers20 mins
- 1.34Joining the Responsible AI Movement20 mins
- 1.35Translating Your Current Skills into AI-Proof Roles20 mins
- 1.36Understanding the Infamous Finger Problem and Other GenAI Quirks20 mins
- 1.37Crafting Effective Prompts for Diverse AI Applications20 mins
- 1.38Keeping Up with the Pace of GenAI Advancements20 mins
- 1.39Touring the User Interface20 mins
- 1.40Taking Copilot for a Test Flight20 mins
- 1.41Adding Data to Prompts20 mins
- 1.42Problem-Solving with AI in Creative Projects20 mins
- 1.43Preparing the Data20 mins
- 1.44Redesigning Slides with Copilot20 mins
- 1.45Harnessing GenAI in Legal20 mins
- 1.46Overcoming Resistance to AI Adoption20 mins
- 1.47Following Practical Steps for Idea Generation with AI20 mins
- 1.48Emailing with Copilot20 mins
- 1.49Enhancing Existing Creative Assets20 mins
- 1.50Crafting Research Designs and Outlines with GenAI20 mins
Instructor
Free
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