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Learn data types, measures of center, and the basics of mathematical notation, and then progress to common visual methods for quantitative data, measures of spread, and the difference between descriptive and inferential statistics.
Learn about the keys steps of the data analysis process and use cell referencing and menu shortcuts.
Sort and filter data, use text and math functions, split columns and remove duplicates.
Summarize data with aggregation and conditional function and use pivot tables and lookup functions.
Build data visualizations for quantitative and categorical data, create pie, bar, line, scatter, histogram and boxplot charts, and build professional presentations.
Become familiar with business metrics used by business analysts in the area of marketing, sales, growth, engagement and financial analysis, calculate and interpret key performance metrics, and calculate metrics and create plots to visualize metrics in Excel.
Understand the fundamentals of sales and financial forecasting models, and create forecasting models using advanced lookup and data validation tools (INDEX, MATCH, OFFSET) in Excel.
In this project, you will work with a New York Stock Exchange (NYSE) dataset that contains fundamental financial data for 500 companies. You will use spreadsheets to analyze and summarize the data using statistics and data visualizations. You will communicate the key findings in a professional manner. You will also design a dashboard that calculates the financial metrics and auto populates the income statement for each company using data validation and advanced lookup tools within Excel. You will then forecast financial metrics within the Income Statement, based on three scenarios with distinct assumptions for a company of your choice from the NYSE dataset.
Dana is an electrical engineer with a Masters in Computer Science from Georgia Tech. Her work experience includes software development for embedded systems in the Automotive Group at Motorola, where she was awarded a patent for an onboard operating system.
Data Scientist at Nerd Wallet
Josh has been sharing his passion for data for nearly a decade at all levels of university, and as Lead Data Science Instructor at Galvanize. He's used data science for work ranging from cancer research to process automation.
Ruchi is a data scientist with over a decade of experience in research and industry. She received her PhD from University of Illinois at Urbana-Champaign. She has taught at the University level and designs online learning content within the ed-tech industry.
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