Kickstart Your AI Journey: From Zero to Real-World Projects

Praxisnahes Kursprojekt

Project Description

In this course, you will complete five advanced, hands-on projects designed to apply the concepts and techniques you’ve learned. Each project gives you the chance to build real-world AI and machine learning solutions, strengthen your technical skills, and create a portfolio to showcase to employers.

Project 1: Breast Cancer Prediction
Use machine learning models to classify and predict breast cancer outcomes using the Wisconsin dataset. You’ll preprocess the data, apply classification algorithms, and evaluate the model’s accuracy to help improve early detection.

Project 2: Spam News Detection
Build a system that identifies and classifies spam news or messages. You will apply text preprocessing, feature extraction, and classification models like Naive Bayes or logistic regression to detect spam accurately.

Project 3: Handwritten Digit Recognition
Train a convolutional neural network (CNN) using the LeNet-5 architecture on the MNIST dataset. This project focuses on deep learning techniques to recognize handwritten digits, an essential foundation for computer vision tasks.

Project 4: Automatic License Plate Detection
Apply object detection techniques using TensorFlow and pre-trained models to detect license plates in images. You will handle model configuration, training, evaluation, and apply OCR (Optical Character Recognition) to extract text from detected plates.

Project 5: COVID-19 Detection Using Neural Networks
Develop a deep learning model to detect COVID-19 from medical images. You’ll work with data augmentation, transfer learning, and neural network architectures, then build and deploy a web application using Flask to make predictions in real time.

By completing these projects, you’ll gain valuable, practical experience that goes beyond theory — preparing you for roles in machine learning, AI development, or data science.