Start with AI literacy and responsible use, practice effective prompts, build useful workflows, and explore Python, machine learning, and AI engineering without getting lost in the hype.
Same eight-step learning sequence, three different paces. These are introductory plans—not promises of career mastery in a few days.
Explore the foundations, practice a little each day, and complete a small challenge.
Give yourself extra time for repetition, guided videos, and practice.
Build durable skills and select an external course or career pathway.
Check off a step when you can explain or demonstrate it. Progress is saved only in this browser, on this device.
These gateway links open relevant Learn IT Free playlists. No heavy playlist embeds are needed to get started.
Start with the concepts and examples in our AI 101 YouTube course.
▶ Open Playlist on YouTubeConsider practical implications and responsible use before building.
▶ Open Playlist on YouTubeCurated existing channel playlists, selected by relevance. Some are supporting or cross-disciplinary courses rather than stand-alone AI curricula. Select “Watch Here” to play a course without leaving this page; the player loads only on demand.
Only the selected playlist loads. If playback is unavailable, use “Continue on YouTube.” You can mark roadmap milestones complete separately.
Understand essential AI and ML concepts with practical beginner examples.
▶ Continue on YouTube ↗Explore AI, data ethics, privacy, and how technology affects everyday life.
▶ Continue on YouTube ↗Use Python as a foundation for more technical AI workflows.
▶ Continue on YouTube ↗Practice with datasets, visualizations, maps, and real-world questions.
▶ Continue on YouTube ↗Build coding confidence through shorter hands-on exercises.
▶ Continue on YouTube ↗Find external AI education and compare learning versus credential options.
▶ Continue on YouTube ↗Complete one project, write down what you did, and explain the decisions and limitations.
Use an AI assistant to research a topic, verify claims from trustworthy sources, and publish a one-page evidence log.
Design a repeatable prompt-and-review process for a real work task, documenting safeguards and failure cases.
Use a public CSV to ask questions, summarize findings, and explain how you validated the calculations.
Visit the existing Learn IT Free library and search for relevant terms. Counts and results depend on the library catalog.
Try searching for artificial intelligence and filter by format or subject when available.
🔎 Open Free LibraryFree learning access does not always mean a free verified certificate, badge, exam, or credential. Confirm the provider's current terms before enrolling.
Free course access; verify current certificate eligibility and requirements directly with Harvard.
Explore providerFree self-paced modules and achievements; certification exams may require payment.
Explore providerLearning resources and badges vary by offering; check availability and any charges.
Explore providerSome third-party products have optional paid features, limited free usage, or regional restrictions.
Explore model prompting and prototype AI workflows; availability and usage limits vary.
Explore tool →Run Python notebooks in your browser to experiment with AI and data.
Explore tool →Explore model documentation, demos, and educational examples.
Explore tool →Publish projects, validation notes, and reproducible examples.
Explore tool →The skills hub teaches the discipline. Career Tracks guide learners toward role-based outcomes, prerequisites, and portfolios.
Combine Python, data, models, evaluation, and deployment.
Explore Career Tracks →Use AI as an assistant for verified analysis, never a replacement for validation.
Explore Career Tracks →Operate AI-enabled services, workflows, and infrastructure.
Explore Career Tracks →Use AI carefully in investigation and defensive automation.
Explore Career Tracks →Use the roadmap, follow Learn IT Free courses, complete a portfolio project, and explore the career paths that match your interests.