• AvanzatoLivello di competenza
• 4.0+
• 1406 revisioni

Develop an inventory management system for a retail business using OOP in Python.

• AvanzatoLivello di competenza
• 4.4+
• 1149 revisioni

Step into a data engineers shoes and master data cleaning with PySpark on an e-commerce orders dataset!

• AvanzatoLivello di competenza
• 4.3+
• 779 revisioni

Use PySpark to build an e-commerce forecasting model!

• BasicLivello di competenza
• 4.4+
• 513 revisioni

Use OpenAIs powerful API to enrich and summarize stock market data.

• AvanzatoLivello di competenza
• 4.6+
• 358 revisioni

Help the bank monitoring their fraud detection model and figuring out why its not performing as expected.

• IntermedioLivello di competenza
• 4.3+
• 892 revisioni

Ready to analyze and visualize financial ratios? In this project, you will take on real-world challenges like evaluating the profitability and leverage of companies across industries.

• IntermedioLivello di competenza
• 4.3+
• 3240 revisioni

Apply your importing and cleaning data and data manipulation skills to explore New York City Airbnb data.

• BasicLivello di competenza
• 4.4+
• 1981 revisioni

Create custom Python functions to validate user input!

• BasicLivello di competenza
• 4.1+
• 1162 revisioni

Sharpen your debugging skills to enhance sales data accuracy.

• IntermedioLivello di competenza
• 4.2+
• 1115 revisioni

Query the VatComply API to gather exchange rate information and incorporate into a sales orders dataset!

• BasicLivello di competenza
• 4.2+
• 1767 revisioni

Exploring flight data from NYC using advanced data joining techniques in R.

• IntermedioLivello di competenza
• 3.8+
• 1568 revisioni

Examine flight delays & cancellations to uncover insights.

• IntermedioLivello di competenza
• 4.1+
• 2874 revisioni

Analyze product data for an online sports retail company to optimize revenue.

• BasicLivello di competenza
• 4.2+
• 1892 revisioni

Use a variety of data manipulation techniques to explore different aspects of Legos history.

• IntermedioLivello di competenza
• 4.2+
• 555 revisioni

Use mean-variance optimization to find optimal portfolio weights and then check how well they would have performed.

• IntermedioLivello di competenza
• 4.2+
• 2433 revisioni

Chart electric vehicle charging trends to inform strategic planning.

• IntermedioLivello di competenza
• 4.4+
• 651 revisioni

Explore facial recognition with ML by distinguishing Arnold Schwarzenegger from others using Python and scikit-learn.

• IntermedioLivello di competenza
• 4.0+
• 1266 revisioni

Build models predicting customer churn for Indian telecom customers.

• BasicLivello di competenza
• 4.3+
• 1915 revisioni

Automatically generate keywords for a search engine marketing campaign using Python to send website visitors to the right landing page.

• AvanzatoLivello di competenza
• 4.4+
• 639 revisioni

Use logistic regression to determine which treatment procedure is more effective for kidney stone removal.

• BasicLivello di competenza
• 4.5+
• 1713 revisioni

Use SQL to analyze a database containing information about Transport for London journeys over 12 years!

• IntermedioLivello di competenza
• 3.9+
• 1222 revisioni

Use joining techniques to discover the oldest businesses in the world.

• IntermedioLivello di competenza
• 4.3+
• 515 revisioni

Powering Data for the Department of Energy - Building an ETL Pipeline

• AvanzatoLivello di competenza
• 4.2+
• 706 revisioni

Use deep learning to automate the classification of service desk tickets.

• AvanzatoLivello di competenza
• 4.2+
• 753 revisioni

Explore transportation time series data analysis to uncover patterns and forecast travel costs.

• IntermedioLivello di competenza
• 4.4+
• 1289 revisioni

Analyze online shopping habits: returning vs. new customers using statistics & probability techniques!

• IntermedioLivello di competenza
• 4.3+
• 865 revisioni

Use MLBs Statcast data to compare New York Yankees sluggers Aaron Judge and Giancarlo Stanton.

• IntermedioLivello di competenza
• 4.4+
• 726 revisioni

Generate features from text and numeric variables to predict the popularity of books.

• IntermedioLivello di competenza
• 4.0+
• 798 revisioni

Build an AI-powered inbox assistant to classify your emails using Llama.

• AvanzatoLivello di competenza
• 4.3+
• 412 revisioni

Train a simple reinforcement learning agent in stock trading simulation.