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Introduction to Data

Course

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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06Days04Hrs31Min37Sec

  • Estimated time
    25 hours

  • Enroll by
    October 12, 2022

    Get access to classroom immediately on enrollment

  • Prerequisites
    No Experience Required

What You Will Learn

  1. Introduction to Data

    25 hours to complete

    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.

    Prerequisite knowledge

    1. Descriptive Statistics

      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.

      • Spreadsheets: Getting Started

        Learn about the keys steps of the data analysis process and use cell referencing and menu shortcuts.

        • Spreadsheets: Manipulate Data

          Sort and filter data, use text and math functions, split columns and remove duplicates.

          • Spreadsheets: Analyze Data

            Summarize data with aggregation and conditional function and use pivot tables and lookup functions.

            • Spreadsheets: Visualize Data

              Build data visualizations for quantitative and categorical data, create pie, bar, line, scatter, histogram and boxplot charts, and build professional presentations.

              • Metrics

                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.

                • Excel Modelling

                  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.

                  • Course Project: Analyze NYSE Data

                    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.

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                  • 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.

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                    Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.

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                    Validate your understanding of concepts learned by checking the output and quality of your code in real-time.

                  • Flexible learning program

                    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.

                  Course offerings

                  • Class content

                    • Real-world projects
                    • Project reviews
                    • Project feedback from experienced reviewers
                  • Student services

                    • Technical mentor support
                    • Student community

                  Succeed with personalized services.

                  We provide services customized for your needs at every step of your learning journey to ensure your success.

                  Get timely feedback on your projects.

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                  • Practical tips and industry best practices
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                  • 1,400+

                    project reviewers

                  • 2.7M

                    projects reviewed

                  • 88/100

                    reviewer rating

                  • 1.1 hours

                    avg project review turnaround time

                  Mentors available to answer your questions.

                  • Support for all your technical questions
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                  • 1,400+

                    technical mentors

                  • 0.85 hours

                    median response time

                  Learn with the best.

                  Learn with the best.

                  • Dana Sheahan

                    Content Developer

                    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 Bernhard

                    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 Bhanot

                    Instructor

                    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.

                  Introduction to Data

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                  Introduction to Data

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