Understand machine learning from the ground up — without writing a single line of code. Use ChatGPT, Claude, Gemini, Perplexity, and Google's Teachable Machine to build, test, and explain ML models. Built for university students and early-career learners with zero technical background. Earn a free certificate to add to your LinkedIn and resume.
4 módulos • 12 lecciones
Understand how AI recognizes what is in a picture, in plain language with no code and no math. Learn how a computer turns a photo into numbers, how it learns patterns from examples, and the core vision tasks: image classification, object detection, face recognition, and OCR. See where computer vision shows up in daily life, why it fails, and how to spot bias. Finish by testing a multimodal chatbot's vision yourself. This course is about recognizing images, not generating them.
Learn Python from zero with a focus on AI and data science. Master the language essentials, then use ChatGPT, Claude, and Gemini as coding tutors while you build real projects with NumPy, pandas, matplotlib, and scikit-learn. Perfect for university students and early-career learners. No prior coding required, and you earn a free certificate to add to your LinkedIn and resume.
Turn raw spreadsheets into polished, interactive dashboards using AI, no coding required. Clean data with Copilot and Power Query, write DAX measures with ChatGPT and Claude, auto-generate insights, and ask your data questions in plain English. Beginner-friendly and 100% free with a certificate of completion.
Bridge the gap between AI curiosity and AI understanding. Discover why linear algebra, calculus, and probability are the three pillars of artificial intelligence, see how each one powers real AI systems like neural networks and LLMs, and get a clear learning path to master them all.
Master the probabilistic foundations of artificial intelligence. Learn probability fundamentals, Bayes' theorem, distributions, expected value, maximum likelihood estimation, and how AI systems handle uncertainty to make predictions.
Master machine learning from the ground up. Learn supervised and unsupervised learning, build models with scikit-learn, and understand the intuition behind algorithms like linear regression, decision trees, and neural networks. Hands-on Python exercises with real datasets.