Projekte

• ExperteSchwierigkeitsgrad
• 4.5+
• 431 Wiederholungen

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

• MittelSchwierigkeitsgrad
• 4.2+
• 2.649 Wiederholungen

Perform hypothesis tests to determine if the adverse effects of a pharmaceutical drug are significant!

• BasicSchwierigkeitsgrad
• 4.5+
• 1.870 Wiederholungen

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

• BasicSchwierigkeitsgrad
• 3.9+
• 3.293 Wiederholungen

Sometimes, things that once worked perfectly suddenly hit a snag. Practice your knowledge of DataFrames to find the problem and fix it!

• MittelSchwierigkeitsgrad
• 4.3+
• 1.501 Wiederholungen

Join us at a leading insurance company, where well craft a model to predict customer charges and test it with new client data

• ExperteSchwierigkeitsgrad
• 4.3+
• 843 Wiederholungen

Transcribe customer support audio calls, evaluate sentiment, search in text and identify common entities to improve customer service!

• ExperteSchwierigkeitsgrad
• 4.3+
• 855 Wiederholungen

Use PySpark to build an e-commerce forecasting model!

• MittelSchwierigkeitsgrad
• 4.4+
• 625 Wiederholungen

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

• MittelSchwierigkeitsgrad
• 4.3+
• 2.444 Wiederholungen

Use DataFrames to read and merge employee data from different sources.

• BasicSchwierigkeitsgrad
• 4.3+
• 331 Wiederholungen

Build an educational quiz bot to generate questions and answers to quiz yourself or your students.

• BasicSchwierigkeitsgrad
• 4.2+
• 2.103 Wiederholungen

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

• MittelSchwierigkeitsgrad
• 4.1+
• 1.195 Wiederholungen

Use web scraping and NLP to find the most frequent words in classic literature: Herman Melvilles novel, Moby Dick.

• MittelSchwierigkeitsgrad
• 4.2+
• 3.343 Wiederholungen

Perform a hypothesis test to determine if more goals are scored in womens soccer matches than mens!

• MittelSchwierigkeitsgrad
• 4.4+
• 2.936 Wiederholungen

Extract structured data from unstructured natural language in medical transcriptions using the OpenAI API.

• BasicSchwierigkeitsgrad
• 4.2+
• 1.021 Wiederholungen

Explore a dataset containing a centurys worth of Nobel Laureates. Who won? Who got snubbed?

• MittelSchwierigkeitsgrad
• 4.2+
• 1.280 Wiederholungen

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

• BasicSchwierigkeitsgrad
• 4.3+
• 2.087 Wiederholungen

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

• MittelSchwierigkeitsgrad
• 4.3+
• 1.013 Wiederholungen

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

• MittelSchwierigkeitsgrad
• 4.0+
• 1.357 Wiederholungen

Apply your data manipulation skills to time series data on water levels of the River Thames.

• MittelSchwierigkeitsgrad
• 4.4+
• 1.410 Wiederholungen

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

• MittelSchwierigkeitsgrad
• 4.0+
• 901 Wiederholungen

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

• MittelSchwierigkeitsgrad
• 4.6+
• 302 Wiederholungen

Step into a data scientists role and learn how to make product decisions with A/B testing in Python!

• ExperteSchwierigkeitsgrad
• 4.1+
• 851 Wiederholungen

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

• MittelSchwierigkeitsgrad
• 3.9+
• 1.337 Wiederholungen

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

• MittelSchwierigkeitsgrad
• 4.4+
• 849 Wiederholungen

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

• BasicSchwierigkeitsgrad
• 4.4+
• 327 Wiederholungen

Using OpenAI API for text translation, grammar checking, and pronunciation feedback

• MittelSchwierigkeitsgrad
• 4.1+
• 2.216 Wiederholungen

Use logistic regression to predict whether people will make a claim on their car insurance!

• MittelSchwierigkeitsgrad
• 4.4+
• 429 Wiederholungen

Build a PyTorch-powered traffic prediction system using time-series skills and deep learning to forecast traffic volume.

• MittelSchwierigkeitsgrad
• 4.0+
• 1.377 Wiederholungen

Build models predicting customer churn for Indian telecom customers.

• ExperteSchwierigkeitsgrad
• 4.3+
• 468 Wiederholungen

Train a simple reinforcement learning agent in stock trading simulation.