Real-world projects from industry experts
With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.
Learn to apply data & statistics specifically for business! In this course, you’ll go from data novice to spreadsheet wizard, calculating and forecasting key financial metrics, even making detailed projections off real-life financial data from the New York Stock Exchange.
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Data literacy is no longer solely expected of analysts & engineers — it’s become a critical skill for anyone who wants to drive decision-making at their company. This practical course is for business professionals looking to add data analysis to their strategy & planning. You’ll dive right into Excel and Google Spreadsheets, manipulating data, calculating key business metrics, and even building financial forecasting models with historical stock-market data.
No experience required.
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.
With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.
On demand help. Receive instant help with your learning directly in the classroom. Stay on track and get unstuck.
Validate your understanding of concepts learned by checking the output and quality of your code in real-time.
Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.
We provide services customized for your needs at every step of your learning journey to ensure your success.
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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.
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.
Descriptive and inferential statistics, how to calculate business metrics, and how to build forecasting models in Excel and Google Spreadsheets.
On average, successful students take 1 month to complete this program.
No. This Course accepts all applicants regardless of experience and specific background.
No prior experience is required, but it is recommended that students are comfortable with basic computer skills, such as managing files, using third-party online programs, and navigating the Internet through an online browser.
The Introduction to Data Analytics for Business course is comprised of content and curriculum to support one project. We estimate that students can complete the program in 1 month.
The project will be reviewed by the Udacity reviewer network and platform. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.
Access to this course runs for the length of time specified in the payment card above. If you do not graduate within that time period, you will continue learning with month to month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our programs.
Please see the Udacity Program Terms of Use and FAQs for policies on enrollment in our programs.
Students should have access to the Internet and a 64 bit computer. There are no additional software and version requirements to complete this program, all coursework and projects can be completed via Student Workspaces in the Udacity online classroom.