Predicting Titanic Survival: Build an AI Web App with PyTorch and Next.js

Have you ever wondered how to take a machine learning model out of a development environment and turn it into a real, interactive web application? This text-based course guides you through the entire process of building a deep learning model and deploying it as a functional web service. You will learn the foundations of neural networks using PyTorch, train a model on the classic Titanic dataset, and connect it to a modern Next.js frontend, gaining hands-on experience with both backend AI logic and frontend web development. What you'll learn: - Understand foundational deep learning concepts, neural network architectures, and data preprocessing techniques. - Train a binary classification model using PyTorch to predict survival probability based on passenger data. - Apply clean Python coding practices, including modern type hints, to structure your machine learning code. - Build a responsive web interface using Next.js to collect user inputs and display predictions. - Connect your PyTorch model to a Next.js API route to handle real-time inference requests. - Practice evaluating your model's performance using standard validation metrics. The course begins with essential terminology and core concepts in deep learning and web development, guiding you step-by-step from data preparation to final application integration. You will work through written explanations, structured code snippets, and practical exercises designed to reinforce your learning. This course is designed for beginners interested in AI and web development; no prior experience with PyTorch or Next.js is required. Start reading today to bridge the gap between data science and web development.