Python is a powerful and easy-to-learn programming language. Learn why Python is essential, its rapid job growth, and how it can transform your career. Our platform offers a wealth of exercises and projects to help you become proficient in Python.
4hrs average
Learn interactively to consume and create HTTP requests to APIs using Python
5hrs average
Exercises and examples for linear algebra using Python and NumPy, covering topics such as vectors, matrices, and linear transformations.
6hrs average
Learn Object Oriented Programming concepts using Python, from basic to advanced topics. This tutorial covers classes, inheritance, polymorphism, encapsulation, and more. Ideal for beginners and experienced developers looking to deepen their understanding.
1hrs average
Analyze and repair a Python script sabotaged by an internal attacker to recover the original password. Once fixed, validate it and decode a flag using CyberChef.
Discover three key strategies to train more effective deep learning models: reuse pre-trained networks with Transfer Learning, improve generalization with Data Augmentation, and prevent overfitting with Early Stopping. A practical guide for beginners.
2hrs average
In this project, you will learn how to structure a professional Python project focused on analyzing biodiversity and climate data using SQL queries and Python tools like SQLAlchemy and Pandas.
Learn how to use Seaborn to create advanced statistical plots easily. Discover how to visualize and analyze data with this powerful Python library.
1hrs average
Analyze a suspicious script, deduce the criminal's name from clues, and decode a flag using CyberChef.
5hrs average
Build a supervised classification model to predict whether a person will surpass a certain annual income threshold based on demographic data, and develop an interpretative recommendation system that suggests alternative paths to improve their situation.
2hrs average
This project is designed to help you learn and practice data visualization techniques using Matplotlib and Seaborn libraries in Python. The exercises will guide you through creating customizable and elegant charts, from line and bar charts to scatter and pie charts.
Learn how recurrent neural networks enable Deep Learning models to work with sequential data. Discover how they work, their applications in language, time series, and speech recognition, and why they are essential for understanding memory in artificial intelligence.
Learn what recommender systems are, their main types, and the algorithms that make them work. A clear and pedagogical guide for students starting in Machine Learning and Data Science.
Analyze monthly sales data for three products over 20 days using Python. Apply loops, conditionals, and data structures to calculate totals, averages, and trends for better insights.