Free Udemy Course: Predict Football Scores with Python & Machine Learning

Build an AI That Predicts Football Scores – Plus 6 Hands-On Bonus ProjectsLearn artificial intelligence by creating a full web app that predicts match results — and sharpen your skills with six additional real-world AI projects.The Most Practical and Complete AI Course for Beginners on UdemyTired of theory-heavy tutorials that go nowhere? Want to master AI by doing? Fascinated by football or curious how AI can predict scores ? This course is for you.Your Main Project: An AI That Predicts Match ResultsBuild a machine learning model that predicts match outcomes for Europe’s top five leagues (Premier League, La Liga, Serie A, Bundesliga, Ligue 1) using real data from Kaggle, ESPN, and API-Football. Then deploy it as a real-time Flask web app — just like a real SaaS product.Includes 6 Bonus AI ProjectsBonus 1 – Emotion detection via webcam (Computer Vision)Bonus 2 – Drone and flying object detection (Computer Vision)Bonus 3 – Road object detection (Computer Vision)Bonus 4 – English to French translation (Natural Language Processing)Bonus 5 – Multilingual summarization (Natural Language Processing)Bonus 6 – Pneumonia detection from chest X-rays (Medical AI)Optional Theory ModulesML/DL foundations, CNNs, YOLO, CPU vs GPU/TPU — explained clearly, without jargon.Skills & Topics Covered1. Data Acquisition & OrganizationImport/export CSV, JSON & image files (Kaggle, Google Drive, API-Football)Relational schemas and multi-table joins (fixtures - standings - teamStats)Multilingual datasets setup (XSum and MLSUM for summarization, KDE4 for translation)2. Cleaning & PreprocessingVisual EDA (histograms, boxplots, heatmaps)Detecting and fixing anomalies (outliers, duplicates, encoding issues)Advanced imputation (BayesianRidge, IterativeImputer)Image augmentation (ImageDataGenerator: flip, rotate, zoom)Normalization and standardization (Scikit-learn scalers)Dynamic tokenization and padding (MBart50Tokenizer, MarianTokenizer)3. Feature EngineeringDerived variables (performance ratios, home vs. away gaps, NLP indicators)Categorical encoding (one-hot, label encoding)Feature selection & importance (RandomForest, permutation importance)4. ModelingTraditional supervised learning (Ridge/ElasticNet for score prediction)Convolutional Neural Networks (EfficientNetB0 for pneumonia detection)Seq2Seq Transformers (fine-tuned mBART50 for summarization, MarianMT for translation)Real-time computer vision (YOLOv5/v9 for object, emotion, and drone detection)5. Evaluation & InterpretationRegression: MAE, RMSE, R², MedAEClassification: accuracy, recall, F1, confusion matrixNLP: ROUGE-1/2/L, BLEULearning curves: loss & accuracy (train/val), early stopping6. Optimization & Best PracticesTransfer learning & fine-tuning (freezing, compound scaling, gradient checkpointing)GPU/TPU memory management (adaptive batch size, gradient accumulation)Early stopping and custom callbacks7. Deployment & IntegrationSaving models (Pickle, save_pretrained, Google Drive)REST APIs with Flask (/predict-score, /summary, /translate, /detect-image)Web interfaces (HTML/CSS + animated loader)Real-time processing (OpenCV video streams, live API queries)8. Tools & EnvironmentPython 3 • Google Colab • PyCharm • Pandas • Scikit-learn • TensorFlow/Keras • Hugging Face Transformers • OpenCV • Matplotlib • YOLO • API-FootballBy the end of this course, you’ll be able to:Clean and leverage complex datasetsBuild and evaluate powerful ML models (MAE, RMSE, R²…)Deploy an AI web app with live APIsShowcase 7 high-impact AI projects in your portfolioWho is this for?Python beginners, football & tech enthusiasts, students, freelancers, career changers — anyone who prefers learning by building.Udemy 30-Day Money-Back GuaranteeEnroll with zero risk — full refund if you're not satisfied.Ready to get hands-on?In just a few hours, you’ll:- Build an AI that predicts football scores- Deploy a fully working web application- Add 7 impressive projects to your portfolioJoin now and start building real AI — the practical way!