When organisations tell me they can’t afford AI training, I push back. Yes, bespoke programs with external facilitators cost money. But building foundational AI literacy doesn’t require a large budget.

The challenge isn’t finding resources—it’s sorting through the overwhelming number of options to find what’s actually worth your time. I’ve done that sorting for you.

Here are the best free resources for building AI skills in 2024, organised by learning goal.

Understanding AI Fundamentals

Before diving into tools, it helps to understand what AI actually is and how it works. These resources build conceptual understanding without requiring technical background.

Elements of AI (University of Helsinki)

This free online course has been taken by over a million people and remains one of the best introductions to AI concepts. It covers the basics of machine learning, neural networks, and AI applications in accessible language.

Time commitment: About 30 hours Best for: Anyone wanting to understand AI concepts, not just use tools Link: elementsofai.com

Google’s AI Fundamentals

Google offers several free courses through their Skills for Business program. The “Fundamentals of AI” course provides a solid overview of how AI technologies work and their business applications.

Time commitment: 4-6 hours Best for: Business professionals who need enough understanding to make decisions about AI Link: grow.google/intl/en_au/

LinkedIn Learning - AI Foundation Courses

If your organisation has a LinkedIn Learning subscription (many do), there are dozens of AI courses available. The “Artificial Intelligence Foundations” series is particularly good for beginners.

Time commitment: Varies by course Best for: Those who prefer video-based learning Note: Requires LinkedIn Learning access

Learning Prompt Engineering

The skill that matters most for non-technical workers is prompt engineering—getting better outputs from AI tools through better inputs. These resources focus on that practical skill.

OpenAI’s Prompt Engineering Guide

OpenAI publishes documentation on effective prompting strategies. It’s written for their products but the principles apply broadly. This is essential reading for anyone using ChatGPT regularly.

Time commitment: 2-3 hours Best for: Active ChatGPT users who want to improve their results Link: platform.openai.com/docs/guides/prompt-engineering

Learn Prompting

This comprehensive free resource covers prompt engineering from basics through advanced techniques. It includes interactive examples and exercises.

Time commitment: 10-20 hours depending on depth Best for: Those who want thorough understanding of prompting strategies Link: learnprompting.org

YouTube: Practical Prompt Tutorials

Search for prompt engineering tutorials from creators like “All About AI” or “AI Explained.” Video demonstrations can be more accessible than text documentation.

Time commitment: Variable Best for: Visual learners who want to see techniques in action

Role-Specific AI Skills

Generic AI training only goes so far. These resources help people in specific functions build relevant skills.

For Marketers: HubSpot’s AI for Marketers

HubSpot offers free courses on using AI for content creation, social media, and marketing automation. Practical and well-produced.

Time commitment: 4-5 hours Best for: Marketing teams exploring AI applications Link: academy.hubspot.com

For HR Professionals: AHRI and SHRM AI Resources

In Australia, AHRI (Australian HR Institute) provides locally relevant guidance on AI in HR contexts. Globally, the Society for Human Resource Management (SHRM) also provides resources on AI applications in HR, including ethical considerations and implementation guidance.

Time commitment: Variable Best for: HR teams evaluating AI tools Link: shrm.org

For Customer Service: Zendesk AI Training

Zendesk offers free training on implementing AI in customer service contexts. Even if you don’t use Zendesk, the concepts transfer.

Time commitment: 3-4 hours Best for: Customer service leaders

For Project Managers: PMI AI Resources

The Project Management Institute has released resources on AI for project management, including how to manage AI implementation projects.

Time commitment: Variable Best for: Project managers working on AI initiatives

Building Technical Foundations

For those who want deeper technical understanding without becoming data scientists, these resources bridge the gap.

Coursera - Andrew Ng’s Machine Learning Course

This Stanford course taught by Andrew Ng has been taken by millions. It requires more time commitment but provides genuine understanding of how machine learning works.

Time commitment: 50-60 hours Best for: Those willing to invest significant time in foundational understanding Note: Can audit for free

Google Colab Tutorials

Google Colab lets you run Python code in your browser without any setup. Combined with introductory tutorials, it’s a gentle way to start experimenting with AI code.

Time commitment: Variable Best for: Curious learners who want to peek under the hood Link: colab.research.google.com

Kaggle Learn

Kaggle offers free micro-courses on machine learning, Python, and data science. They’re practical, project-based, and designed for beginners.

Time commitment: 5-10 hours per course Best for: Those interested in data science applications Link: kaggle.com/learn

Staying Current

AI moves fast. These resources help you stay informed without drowning in noise.

AI Newsletters Worth Subscribing To

• The Rundown AI: Daily digest of AI news in accessible language
• TLDR AI: Concise daily updates on AI developments
• ImportAI: Weekly newsletter with more depth and analysis

Podcasts

• Practical AI: Focuses on real-world applications
• AI Today: News and interviews with practitioners
• Lex Fridman Podcast: Long-form conversations (when featuring AI researchers)

Following the Right People

On LinkedIn or Twitter/X, follow AI researchers and practitioners, not just influencers. Look for people who share substantive content rather than hype.

Creating a Learning Path

Resources are only useful if you actually use them. Here’s how to structure self-directed AI learning:

Week 1-2: Foundations

• Complete Elements of AI or Google AI Fundamentals
• Read OpenAI’s prompting guide
• Experiment with ChatGPT for basic tasks

Week 3-4: Applied Practice

• Focus on role-specific resources
• Set a goal to use AI for one real work task daily
• Document what works and what doesn’t

Month 2: Deeper Skills

• Work through Learn Prompting
• Explore advanced techniques
• Start sharing knowledge with colleagues

Ongoing: Stay Current

• Subscribe to 1-2 newsletters
• Dedicate 30 minutes weekly to learning updates
• Continuously experiment with new capabilities

Supplementing Free Resources

Free resources have limitations. Consider supplementing with:

Structured cohort learning: Free resources are self-paced. Paid programs with cohorts provide accountability and peer learning.

Hands-on workshops: Reading about AI is different from using it with guidance. Local workshops or TAFE courses can provide this.

Expert coaching: When you’re stuck on specific applications, a few hours with someone experienced can accelerate progress dramatically.

But start with free resources. You can build substantial AI literacy without spending anything.

The Most Important Resource

The most important learning resource isn’t on any of these lists. It’s consistent practice with real work tasks.

All the courses and tutorials in the world won’t build fluency. Using AI tools daily for actual work builds fluency. Everything else is preparation for that practice.

Set aside time each day to experiment. Accept that early attempts will be clumsy. Notice what works and adjust. Ask colleagues what they’ve learned. Keep going.

That’s how AI fluency develops. The resources just help you start.