• IntermedioLivello di competenza
• 3.9+
• 777

Automate e-commerce processes with image classification.

• IntermedioLivello di competenza
• 4.1+
• 775

Review a data analysis workflow for adherence to Python standards and best-practices.

• IntermedioLivello di competenza
• 4.4+
• 745

Clean customer data and use logistic regression to predict whether people will make a claim on their car insurance!

• BasicLivello di competenza
• 4.0+
• 724

Use categorization and ranking techniques to explore 101 years of American baby names.

• AvanzatoLivello di competenza
• 4.2+
• 707

Use your SQL skills to find out how many companies reached a valuation of over $1 billion across different industries between 2019 and 2021!

• AvanzatoLivello di competenza
• 3.6+
• 686

Use LLMs to solve diverse language tasks for a car dealership company.

• IntermedioLivello di competenza
• 3.8+
• 669

Use SQL to analyze a database containing information about Student performance!

• AvanzatoLivello di competenza
• 4.1+
• 637

Identify issues in a manufacturing process using SQL window functions and subqueries

• IntermedioLivello di competenza
• 4.3+
• 628

Develop a multi-input model to classify characters from scanned documents.

• BasicLivello di competenza
• 4.0+
• 615

Conduct a supply chain analysis of the ingredients used in an avocado toast to gain an understanding of the complex supply chain involved.

• IntermedioLivello di competenza
• 4.1+
• 573

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

• IntermedioLivello di competenza
• 4.3+
• 572

Build a machine learning model to predict if a credit card application will get approved.

• IntermedioLivello di competenza
• 4.3+
• 551

Enhance your SQL Skills with hands-on data cleaning in PostgreSQL: perform analyses while working with incorrect data types and missing values.

• IntermedioLivello di competenza
• 4.1+
• 531

Building an image processing pipeline for data augmentation.

• IntermedioLivello di competenza
• 4.1+
• 475

Develop a system that can detect Cyber Threats in your companys network traffic logs using Deep Learning.

• IntermedioLivello di competenza
• 4.1+
• 473

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

• BasicLivello di competenza
• 4.1+
• 473

Use data manipulation and visualization to explore a television broadcast dataset from the Super Bowl.

• IntermedioLivello di competenza
• 4.1+
• 442

Manipulate date and time using Python

• BasicLivello di competenza
• 4.1+
• 438

Develop a new app feature with your Python skills to calculate calories and nutrition values from user input.

• BasicLivello di competenza
• 3.9+
• 428

Analyze UEFA Champions League Soccer Games using Snowflake SQL.

• IntermedioLivello di competenza
• 4.1+
• 385

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

• IntermedioLivello di competenza
• 3.7+
• 381

Use regression and machine learning models to predict daily power consumption based on temporal factors.

• IntermedioLivello di competenza
• 4.3+
• 379

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

• IntermedioLivello di competenza
• 3.6+
• 359

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

• AvanzatoLivello di competenza
• 4.2+
• 357

Use PySpark to build an e-commerce forecasting model!

• BasicLivello di competenza
• 3.7+
• 357

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

• BasicLivello di competenza
• 4.3+
• 350

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

• IntermedioLivello di competenza
• 4.2+
• 347

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

• BasicLivello di competenza
• 4.0+
• 347

Sharpen your debugging skills to enhance sales data accuracy.

• AvanzatoLivello di competenza
• 4.1+
• 341

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