Stacked AI vs Learn Machine Learning & AI

AI Stack Builder is a visual, hands-on learning app designed to help adults and beginners understand how modern artificial intelligence systems actually work—from the computer basics all the way up to running real AI models. Most AI education jumps straight into coding or abstract math. This app takes a different approach: it teaches the entire AI stack, layer by layer, using clear explanations, interactive maps, and practical system-building exercises. What you’ll learn • How CPUs, GPUs, RAM, and VRAM work together • What operating systems, drivers, and runtimes actually do • How CUDA, libraries, and frameworks fit into the AI stack • How containers and Docker are used in real AI deployments • How models, tokens, embeddings, and inference work • Why things break—and how to reason about common errors Key features Visual Learning Map Progress through a node-based learning map that shows how concepts connect. Each lesson unlocks naturally as you build understanding from the ground up. Stack Builder (Interactive) Assemble AI systems by placing components in the correct order. Learn dependencies, fix broken stacks, and understand why certain setups work—or fail. Short, Focused Lessons Each lesson is designed to be completed in just a few minutes, making it easy to learn consistently without overwhelm. Plain-English Explanations Concepts are explained in clear, practical language—no advanced math required. Built-in Dictionary Look up common AI terms, abbreviations, file types, and tools, all explained in context and linked to where they sit in the stack. Progress Tracking Track completed lessons, learning streaks, and unlocked topics as you advance. Who this app is for • Adults transitioning into tech or AI • Students learning modern computing systems • Developers who want a clearer mental model of AI infrastructure • Anyone curious about how AI software and hardware work together No prior AI experience is required. AI Stack Builder focuses on understanding systems, not hype—helping learners build real intuition for how modern AI is structured and used in practice.

Learn Machine Learning & AI takes you from "what is machine learning" to understanding the algorithms behind modern artificial intelligence — 105 subjects and 2,650 lessons, in pieces short enough to read on a phone. No prior AI experience required. If you can follow basic algebra and a little Python, you can follow this course. WHAT YOU WILL LEARN Machine Learning Foundations — how machine learning differs from traditional programming, the training workflow, test data, overfitting, underfitting, bias and variance, and how models are evaluated. Supervised Learning — linear and logistic regression, decision trees, random forests, support vector machines, k nearest neighbours and naive Bayes, each with the intuition behind it. Unsupervised Learning — k means and hierarchical clustering, dimensionality reduction, principal component analysis and anomaly detection. Deep Learning and Neural Networks — perceptrons, activation functions, backpropagation, convolutional networks for images, recurrent networks and LSTMs for sequences, and an introduction to transformers. Reinforcement Learning — agents, environments, rewards, Q learning and policy based methods, without heavy mathematics. Natural Language Processing — tokenization, embeddings, sentiment analysis, and how large language models are built on these ideas. Tools and Libraries — where Python, TensorFlow, Keras, scikit learn, NumPy, Pandas, H2O, OpenCV and Spark MLlib fit into a real workflow. Applied Machine Learning — healthcare, finance, recommendation systems, fraud detection, computer vision and forecasting. TEST WHAT YOU HAVE LEARNED Over 8,000 quiz questions across all 105 subjects. Ten questions per session, four options each, tied to the chapter you have been reading. Three timed difficulty levels: beginner 30 seconds per question, intermediate 20, expert 10. A session runs 5:00, 3:20 or 1:40. Pass at 70%. Filter by level, by attempted or untried, and by best score, so practice targets the algorithms you have not yet understood. Every attempt is stored. ML INTERVIEW PREPARATION 25 machine learning roles with 100 questions each — 2,500 in total — from junior ML engineer through senior, staff and principal, plus data scientist, applied scientist, MLOps, NLP and computer vision. Timed like a real screening round, scored, and saved so you can retake and compare. STUDY OFFLINE Download any subject for offline reading. Lesson text is stored on the device and stays available with no connection; images still need network. Anything you open is cached automatically. The Downloads screen shows what is saved and lets you cancel, resume or remove a subject. PROGRESS, STREAKS AND CERTIFICATES Mark lessons complete, watch the progress ring fill on every subject, and use the Continue card to return to exactly where you stopped. A daily streak counts every day you study, with an optional reminder that is off by default. Complete a subject and pass its quiz at 70% or above to unlock a certificate you can save and share. BUILT FOR LEARNING ON A PHONE Plain language first, mathematics second — every algorithm is explained in words before any notation appears. Short sections you can finish in a few minutes. Syntax highlighted code with one tap copy. Search across the whole course. Bookmarks and history, light, dark and system themes, adjustable font size, and tablet layouts. WHO IT IS FOR Students who want a second explanation when the lecture did not land. Developers moving into machine learning engineering or data science. Candidates preparing for ML and data science interviews, where the questions are still mostly about fundamentals. Professionals who need to understand what an AI system in their industry is actually doing. No video to buffer. No account required. Open your first lesson today. Questions, corrections or a topic request? Email mail@ehsanur.com — we update the app based on what learners ask for.