Case Study: Analyzing Customer Churn in Tableau
You will investigate a dataset from a fictitious company called Databel in Tableau, and need to figure out why customers are churning.
You will investigate a dataset from a fictitious company called Databel in Tableau, and need to figure out why customers are churning.
Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!
You will investigate a dataset from a fictitious company called Databel in Excel, and need to figure out why customers are churning.
Learn to use Google Sheets to clean, analyze, and draw insights from data. Discover how to sort, filter, and use VLOOKUP to combine data.
Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.
Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.
Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.
Discover how Marketing Analysts use data to understand customers and drive business growth.
Use Seaborn's sophisticated visualization tools to make beautiful, informative visualizations with ease.
In this course, you will use T-SQL, the flavor of SQL used in Microsoft's SQL Server for data analysis.
Learn to process, transform, and manipulate images at your will.
Prepare for your next coding interviews in Python.
Discover how to make better business decisions by applying practical data frameworks—no coding required.
Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.
Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.
Learn to connect Tableau to different data sources and prepare the data for a smooth analysis.
Take your R skills up a notch by learning to write efficient, reusable functions.
Learn how to clean data with Apache Spark in Python.
Create new features to improve the performance of your Machine Learning models.
Learn to write SQL queries to calculate key metrics that businesses use to measure performance.
Explore the basics of data quality management. Learn the key concepts, dimensions, and techniques for monitoring and improving data quality.
Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.
Data visualization is one of the most desired skills for data analysts. This course allows you to present your findings better using Tableau.
Transform almost any dataset into a tidy format to make analysis easier.
Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.
Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!
Learn how to translate business questions to well-formed analytical questions and select the right analytical solutions.
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.
Gain experience using techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.
Learn how to perform financial analysis in Power BI or apply any existing financial skills using Power BI data visualizations.
Build the foundation you need to think statistically and to speak the language of your data.
Master sampling to get more accurate statistics with less data.
Learn the gritty details that data scientists are spending 70-80% of their time on; data wrangling and feature engineering.
Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.
Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.
R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.
Bash scripting allows you to build analytics pipelines in the cloud and work with data stored across multiple files.
Learn how to blend business, data, and AI, and set goals to drive success with an effectively scalable AI Strategy.
Master time series data manipulation in R, including importing, summarizing and subsetting, with zoo, lubridate and xts.
Master Python testing: Learn methods, create checks, and ensure error-free code with pytest and unittest.
In this course, you'll learn the basics of relational databases and how to interact with them.
Building on your foundational Power Query in Excel knowledge, this intermediate course takes you to the next level of data transformation mastery
Master Azure Management and Governance with our comprehensive course, ideal for data professionals seeking cloud expertise.
Learn about ARIMA models in Python and become an expert in time series analysis.
The Generalized Linear Model course expands your regression toolbox to include logistic and Poisson regression.
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.
Learn how to identify, analyze, remove and impute missing data in Python.
Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.