No matter what you study, you need to be skilled in current technologies, which may be offered free or at reduced cost at your school. New AI features are being infused into popular software you use every day, making it more user-friendly and powerful.
Productivity and document management software: Word-processing programs, calendars, email clients, Google Drive, Office 365, Dropbox and others.
Collaboration, communication and project management: Zoom, Microsoft Teams, Slack, Google Workspace, Trello, Jira and others.
Data competency: Spreadsheets (Excel, Google Sheets), database programs, data visualization software such as Tableau, Power BI, Venngage, Google Data Studio and others.
Online research: General search engines, custom tools such as Google Scholar and discipline-specific tools available through your library.
Multimedia and Web: Adobe applications, Powerpoint, WordPress, Audacity and cloud-based tools like Canva, Adobe Express and others.
Basic computer systems: Windows, macOS and Linux operating systems and basic programming languages, such as Python, JavaScript or HTML/CSS.
Artificial intelligence is the field of computer science that uses machines to simulate intelligence.
AI tools are now everywhere and many people may interact with them daily without even realizing it. In this environment, it is important to have basic knowledge of how AI tools function and understand various AI terms and acronyms.
Machine Learning (ML): Using algorithms and data to train computers.
Natural language processing: ML focused on understanding and generating human language.
Deep learning: ML that uses neural networks – computer models inspired by the human brain.
Computer vision: ML that enables computers to see and act on visual information.
AI bias: When an AI system produces unfair or inaccurate results because of biased data, design choices, or assumptions made during training.
Training vs. Inference
Generative AI: Using AI to create new text, images, audio and video.
Large language models (LLMs): Computers trained to analyze prompts and generate human-like responses.
LLM implementations: These include ChatGPT, Claude Gemini, Copilot, Perplexity and other special-use LLMs.
Multimodal AI: Computers that can read and generate text, images, audio and video.
Productivity tools: AI-enhanced programs, such as email, word processing, spreadsheets, design programs and virtual assistants like Siri or Alexa.
Prompt engineering: The practice of writing clear, specific instructions (prompts) to get more accurate, useful, or creative responses from AI tools.
Adapted from the Student Guide to Artificial Intelligence (2025), developed by Elon University’s Imagining the Digital Future Center in partnership with American Association of Colleges and Universities. Used with permission under the Creative Commons BY-NC-SA license.
Take a look at frequently asked questions about AI at NIU and available resources.