inaraX

AI Literacy

For beginners — no technical background required

AI Literacy is a starting point for anyone new to AI and technology. The course introduces the basic concepts of AI, how the technology has evolved, and how it has led to the tools we use today. It is designed to help learners build a basic understanding before moving on to more practical or specialized AI skills.

Created by InaraX
Instruction language: English
Premium

No technical background needed · Core AI concepts and prompting · From everyday use to team adoption

Highlights for this program

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Earn a certificate from InaraX

After completion of all courses in the InaraX AI Literacy Certificate path, earn a professional certificate that you can share on social media, LinkedIn, resume, or CV.

What you'll learn

  • ✓Understand what AI is, and how it differs from machine learning and data science
  • ✓Write clear, simple prompts and avoid common prompting mistakes
  • ✓Understand AI's limitations, hallucinations, bias, and privacy considerations
  • ✓Learn how large language models, embeddings, and RAG actually work
  • ✓Apply role-based, context-aware prompting and choose the right AI tool for the job
  • ✓Design and evaluate reliable, human-in-the-loop AI workflows
  • ✓Evaluate AI opportunities, governance, and regulatory considerations
  • ✓Lead AI adoption and communicate AI strategy to stakeholders

Course content

3 levels • 9 modules

  • Module 1: Understanding AILocked
  • Module 2: Prompting FundamentalsLocked
  • Module 3: Limitations, Ethics and PrivacyLocked

Requirements

  • No prior AI or technical experience needed.
  • Helpful (not required): basic comfort using a computer and everyday work tools.

Description

AI Literacy is a level-based program (Associate → Intermediate → Advanced) for anyone who wants a working understanding of AI, regardless of role or background. You'll start with the basics — what AI actually is, how to prompt it well, and where it falls short — then move into how modern AI systems work under the hood (large language models, embeddings, and retrieval), and finish with how to evaluate, govern, and lead AI adoption across a team or organization.

By the end of this course, you will:

  • Explain what AI is and how it differs from machine learning and data science.
  • Write clear, effective prompts and avoid common prompting mistakes.
  • Recognize AI's limitations — hallucinations, bias, and privacy risks — and use it responsibly.
  • Describe how large language models, embeddings, and retrieval (RAG) actually work.
  • Design reliable, human-in-the-loop AI workflows for real work tasks.
  • Evaluate AI opportunities and lead adoption, governance, and strategy across a team or organization.

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