Data Analysis in Excel
Learn how to analyze data in Excel.
Learn how to analyze data in Excel.
Learn how to analyze data with spreadsheets using functions such as SUM(), AVERAGE(), and VLOOKUP().
Learn the basics of spreadsheets by working with rows, columns, addresses, and ranges.
Expand your spreadsheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.
Explore the world of Pivot Tables within Google Sheets, and learn how to quickly organize thousands of data points with just a few clicks of the mouse.
Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.
Learn the fundamentals of data visualization using spreadsheets.
Learn how to build a graphical dashboard with spreadsheets to track the performance of financial securities.
Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.
Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.
Learn basic business modeling including cash flows, investments, annuities, loan amortization, and more using Sheets.
Learn how to use conditional formatting with your data through built-in options and by creating custom formulas.
Learn how to price options contracts and visualize payout of various options strategies using spreadsheets.
Learn how to build an amortization dashboard in spreadsheets with financial and conditional formulas.
No one enjoys looking at spreadsheets! Bring your data to life. Improve your presentation and learn how to translate technical data into actionable insights.
Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.
Gain an overview of all the skills and tools needed to excel in Natural Language Processing in R.
Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.
Learn how to effectively and efficiently join datasets in tabular format using the Python Pandas library.
In this course, you'll learn how to import and manage financial data in Python using various tools and sources.
Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.
Learn to connect Tableau to different data sources and prepare the data for a smooth analysis.
Improve your Python data importing skills and learn to work with web and API data.
Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.
Learn to develop a set of principles for your data science and software development projects.
R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.
Join two or three tables together into one, combine tables using set theory, and work with subqueries in PostgreSQL.
Learn to use essential bioconductor packages using datasets from virus, fungus, human and plants!
Analyze the relative popularity of programming languages over time based on Stack Overflow data.
Analyze the relative popularity of programming languages over time based on Stack Overflow data.
Use DataFrames to read and merge employee data from different sources.
You will explore the market capitalization of Bitcoin and other cryptocurrencies.
Play bank data scientist and use regression discontinuity to see which debts are worth collecting.