Market Basket Analysis in Python
Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.
Siga videos cortos dirigidos por instructores expertos y luego practique lo que ha aprendido con ejercicios interactivos en su navegador.
Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.
Explora el Control de Versiones de Datos para la gestión de datos en ML. Configura, automatiza y evalúa modelos.
Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.
You will use Net Revenue Management techniques in Excel for a Fast Moving Consumer Goods company.
Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.
Learn how to use Python to analyze customer churn and build a model to predict it.
From customer lifetime value, predicting churn to segmentation - learn and implement Machine Learning use cases for Marketing in Python.
Learn efficient techniques in pandas to optimize your Python code.
Develop the skills you need to clean raw data and transform it into accurate insights.
This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.
Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.
Learn the basics of cash flow valuation, work with human mortality data and build life insurance products in R.
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.
Learn to use the Census API to work with demographic and socioeconomic data.
Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.
Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.
Learn to solve increasingly complex problems using simulations to generate and analyze data.
Learn how to design and implement triggers in SQL Server using real-world examples.
Ensure data consistency by learning how to use transactions and handle errors in concurrent environments.
Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!
In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.
Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.
Learn how to build a model to automatically classify items in a school budget.
Boost your Excel skills with advanced referencing, lookup, and database functions using practical exercises.
Learn how to run big data analysis using Spark and the sparklyr package in R, and explore Spark MLIb in just 4 hours.
Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.
Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.
Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.
Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.