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Steve Ryan and Sandip Saha Joy

Spreadsheet tools like Excel are an essential tool for working with data - whether for data analytics, business, marketing, or research. This course is designed to give you a basic working knowledge of Excel and how to use it for analyzing data.

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Spreadsheet tools like Excel are an essential tool for working with data - whether for data analytics, business, marketing, or research. This course is designed to give you a basic working knowledge of Excel and how to use it for analyzing data.

This course is suitable for those who are interested in pursuing a career in data analysis or data science, as well as anyone looking to use Excel for data analysis in their own domain. No prior experience with spreadsheets or coding is required - all you need is a device with a modern web browser and the ability to create a Microsoft account to access Excel online at no cost. If you have a desktop version of Excel, you can also easily follow along with the course.

Throughout this course, you'll gain valuable experience working with data sets and spreadsheets. We'll start by introducing you to spreadsheets like Microsoft Excel and Google Sheets, and show you how to load data from multiple formats. From there, you'll learn how to perform basic data wrangling and cleansing tasks using functions, and expand your knowledge of data analysis through the use of filtering, sorting, and pivot tables.

There is a strong focus on practice and applied learning in this course. With each lab, you'll have the opportunity to manipulate data and gain hands-on experience using Excel. You'll learn how to clean and format your data efficiently, and convert it into a pivot table to make it more organized and readable. The final project will allow you to showcase your newly acquired data analysis skills by working with real data sets and spreadsheets.

By the end of this course, you'll have a solid foundation in using Excel for data analysis. You'll have worked with multiple data sets and spreadsheets, and will have the skills and knowledge needed to effectively clean and analyze data without having to learn any code. So let's get started!

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What's inside

Syllabus

Introduction to Data Analysis Using Spreadsheets
In this module, you will learn about the fundamentals of spreadsheet applications, and you will be introduced to the Excel interface and learn how to navigate your way around a worksheet and workbook.
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Getting Started with Using Excel Spreadsheets
In this module you will learn how to perform basic spreadsheet tasks, such as viewing, entering and editing data, and moving, copying and filling data. In addition, you will learn about the fundamentals of formulas, and learn about the most common functions used by a data analyst. Finally, you will learn how to reference data in formulas.
Cleaning & Wrangling Data Using Spreadsheets
In this module, you will learn about the importance of data quality, and you will learn how to import file data in to Excel. You will also learn about the fundamentals of data privacy. In addition, you will learn how to remove duplicate and inaccurate data, and how to remove empty rows in your data. Finally, you will learn how to deal with inconsistencies in your data and how to use the Flash Fill and Text to Columns features to help you manipulate and standardize your data.
Analyzing Data Using Spreadsheets
In this module, you will learn about the fundamentals of analyzing data using a spreadsheet, and learn how to filter and sort data. You will also learn how to use some of the most useful functions for a data analyst, and how to use the VLOOKUP and HLOOKUP reference functions. In addition, you will learn how to create pivot tables in Excel, and use several pivot table features.
Final Project
Great! You have now completed all four modules of this course. In this final module, you will be introduced to a hands-on lab where you will complete a graded assignment for cleaning and preparing data, and then analyzing data using an Excel spreadsheet. This final assignment will be graded by your peers.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides a foundation for learners entering data science or data analysis professions
Offers in-depth coverage of various functions, filtering, and pivot table features
Hands-on labs provide practical experience using Excel spreadsheets
No prior experience with spreadsheets or coding required, making it accessible to beginners
Emphasis on data wrangling and cleansing tasks using functions and features
Instructors have notable experience and expertise in the topic of data analysis

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Reviews summary

Excel basics for data analysis

This course is highly rated by learners and is designed for those with little to no experience with Excel. Through hands-on exercises and peer-reviewed projects, you will gain proficiency in cleaning, filtering, sorting, and analyzing data in Excel. The course covers functions, pivot tables, data visualization, and how to prepare data for analysis, making it a valuable starting point for aspiring data analysts. **Key Features** * **Beginner-friendly:** Assumes no prior knowledge of Excel, making it accessible to learners of all backgrounds. * **Comprehensive:** Covers a wide range of Excel skills essential for data analysis, including data cleaning, visualization, and analysis techniques. * **Hands-on:** Provides ample opportunities to practice Excel skills through interactive labs and assignments, solidifying your understanding. * **Real-world relevance:** The course focuses on practical applications of Excel in the field of data analysis, preparing you for real-world scenarios. * **Peer-reviewed projects:** Allows you to receive feedback on your work from peers, enhancing your learning experience and improving your analytical skills. **Key Takeaways** Upon completing this course, you will be able to: * Clean, filter, and sort data to prepare it for analysis * Use Excel functions and formulas to perform calculations and extract meaningful insights * Create pivot tables and charts to visualize and summarize data * Apply data analysis techniques to solve real-world problems * Communicate your findings effectively using Excel **Who should take this course?** This course is ideal for: * Individuals with no prior Excel experience who want to learn the basics for data analysis * Aspiring data analysts who need a strong foundation in Excel * Professionals who use Excel for data analysis but want to enhance their skills **Prerequisites** No prior knowledge of Excel or data analysis is required. However, basic computer literacy is recommended. **Course Structure** The course is divided into 5 weeks, each covering a specific aspect of Excel for data analysis: * Week 1: Introduction to Excel and Data Analysis * Week 2: Data Cleaning and Preparation * Week 3: Functions and Formulas * Week 4: Pivot Tables and Charts * Week 5: Data Analysis Techniques Each week includes video lessons, hands-on labs, quizzes, and assignments, culminating in a peer-reviewed final project. **Certificate** Upon successful completion of the course, you will receive a certificate from Coursera and IBM, which can be added to your resume or LinkedIn profile to showcase your proficiency in Excel for data analysis.
This course assumes no prior knowledge of Excel, making it accessible to learners of all backgrounds.
"This course assumes no prior knowledge of Excel, making it accessible to learners of all backgrounds."
This course provides ample opportunities to practice Excel skills through hands-on labs and assignments. This is essential for solidifying your understanding and developing proficiency in Excel.
"This course provides ample opportunities to practice Excel skills through hands-on labs and assignments."
"This is essential for solidifying your understanding and developing proficiency in Excel."
This course includes peer-reviewed projects, which allow you to receive feedback on your work from peers. This is a valuable opportunity to improve your analytical skills and learn from others.
"This course includes peer-reviewed projects, which allow you to receive feedback on your work from peers."
"This is a valuable opportunity to improve your analytical skills and learn from others."
This course covers a wide range of Excel functions, including basic math functions, statistical functions, and logical functions. You will learn how to use these functions to perform calculations and extract meaningful insights from your data.
"This course covers a wide range of Excel functions, including basic math functions, statistical functions, and logical functions."
"You will learn how to use these functions to perform calculations and extract meaningful insights from your data."
This course teaches you how to clean data, which is an important step in data analysis. You will learn how to identify and remove errors, inconsistencies, and duplicate data. You will also learn how to use Excel functions to transform data into a format that is more suitable for analysis.
"This course teaches you how to clean data, which is an important step in data analysis."
"You will learn how to identify and remove errors, inconsistencies, and duplicate data."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Excel Basics for Data Analysis with these activities:
Review Basic Math and Statistics Concepts
Strengthens your foundational understanding of mathematical and statistical concepts, which are essential for data analysis and will help you fully grasp the content of this course.
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  • Review your notes or textbooks on basic math concepts such as algebra, calculus, and probability.
  • Go through online resources or tutorials to refresh your knowledge of statistical concepts like mean, median, and standard deviation.
Review Introductory Statistics with Applications
Provides a strong foundation for understanding the concepts covered in this data analysis course and the fundamentals of data analytics.
Show steps
  • Read Chapters 1-3 to gain an understanding of the basics of statistics, data, and sampling.
  • Complete the practice exercises at the end of each chapter to test your understanding.
Participate in Excel Study Group
Provides an opportunity to collaborate with peers, exchange knowledge, and reinforce your understanding of the course material through discussions and problem-solving.
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  • Find a study partner or group who are also enrolled in the course.
  • Meet regularly to discuss course concepts, work on assignments together, and provide mutual support.
  • Engage in peer review of each other's work to provide constructive feedback and improve understanding.
Five other activities
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Begin a Personal Data Analysis Project
Allows you to apply the concepts learned in this course in a practical context, solidifying your understanding and enhancing your data analysis skills.
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  • Identify a dataset that interests you and align with the learning objectives of the course.
  • Develop a research question or hypothesis to guide your analysis.
  • Import the dataset into Excel and explore the data using descriptive statistics and visualization techniques.
  • Conduct analysis to answer your research question or test your hypothesis.
  • Present your findings in a clear and concise manner, highlighting the insights gained from the analysis.
Explore Tutorials on Advanced Excel Functions
Enhances your proficiency in Excel functions beyond the basics covered in the course, enabling you to perform more complex data manipulation and analysis tasks.
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Show steps
  • Search for tutorials on advanced Excel functions such as INDEX, MATCH, and OFFSET.
  • Follow along with the tutorials, practicing the functions on sample datasets.
  • Experiment with the functions in your own Excel workbooks to gain hands-on experience.
Participate in an Excel Data Analysis Competition
Provides a unique opportunity to test your skills against other data enthusiasts, gain recognition for your abilities, and expand your knowledge through exposure to diverse approaches.
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Show steps
  • Identify an Excel data analysis competition that aligns with your interests and skill level.
  • Form a team or work individually to prepare for the competition.
  • Analyze the provided dataset and develop data-driven insights and solutions.
  • Present your findings and compete against other teams for recognition and prizes.
Develop an Excel Tutorial
Solidifies your understanding of Excel and data analysis by requiring you to articulate the concepts in a clear and structured manner, which can also benefit others who are learning.
Show steps
  • Choose a specific Excel function or data analysis technique that you want to focus on.
  • Create a step-by-step tutorial that explains the concept in a clear and concise way.
  • Include screenshots, examples, and practice exercises to illustrate the concepts.
  • Share your tutorial with others through a blog, social media, or other platforms.
Contribute to an Open-Source Excel Project
Allows you to engage with the wider data analysis community, contribute to the development of open-source tools, and gain valuable practical experience.
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  • Identify an open-source Excel project that aligns with your interests and skills.
  • Review the project's documentation and familiarize yourself with its codebase.
  • Identify areas where you can contribute and propose your improvements or new features.
  • Create pull requests to submit your contributions and engage with the project maintainers.

Career center

Learners who complete Excel Basics for Data Analysis will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst examines and interprets data through statistical methods and software to extract meaningful insights. These insights support decision-making in organizations. This course can help build a foundation for a Data Analyst by teaching you how to handle, clean, and analyze data using Excel.
Market Research Analyst
Analyzing data and trends is essential for a Market Research Analyst. This course helps build a foundation for this career by teaching you how to analyze data using Excel. You will learn to clean and format your data efficiently, as well as how to create and use pivot tables for organized and readable data.
Business Analyst
Business Analysts use data to analyze business processes and performance. This course helps build a foundation for this career by teaching you how to use Excel to clean, manipulate, and analyze data. You will learn how to use functions, filter, sort, and create pivot tables to make data more organized and readable.
Financial Analyst
Spreadsheets, particularly Microsoft Excel, are one of the most important tools for financial analysis. In this course, you will learn the basics of using Excel for data analysis, which may help build the foundation for a successful career as a Financial Analyst.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to solve complex problems in various industries. This course may be useful for building a foundation for this career, by teaching you how to use Excel for data analysis.
Financial Planner
Financial Planners help clients plan and manage their finances. This course may be useful for building a foundation for this career, by teaching you the basics of data analysis using Excel.
Auditor
Auditors examine and analyze financial records to ensure accuracy and compliance. This course may be useful for building a foundation for this career, by teaching you the basics of data analysis using Excel.
Budget Analyst
Budget Analysts examine and analyze financial data to develop and manage budgets. This course may be useful for building a foundation for this career, by teaching you the basics of data analysis using Excel.
Investment Analyst
Investment Analysts examine and analyze financial data to make investment recommendations. This course may be useful for building a foundation for this career, by teaching you the basics of data analysis using Excel.
Data Scientist
Data Scientists use their knowledge of data analysis and machine learning to solve complex problems and extract meaningful insights from data. This course may be useful for building a foundation for this career, by teaching you the basics of data analysis using Excel.
Cost Analyst
Cost Analysts examine and analyze financial data to determine the cost of products or services. This course may be useful for building a foundation for this career, by teaching you the basics of data analysis using Excel.
Statistician
Statisticians use mathematical and statistical methods to collect, analyze, interpret, and present data. This course may be useful for building a foundation for this career, by teaching you the basics of data analysis using Excel.
Risk Analyst
Risk Analysts examine and analyze financial data to identify and mitigate risks. This course may be useful for building a foundation for this career, by teaching you the basics of data analysis using Excel.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. This course may be useful for building a foundation for this career, by teaching you the basics of data analysis using Excel.
Actuary
Actuaries use mathematical and statistical methods to assess risk and uncertainty. This course may be useful for building a foundation for this career, by teaching you the basics of data analysis using Excel.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Excel Basics for Data Analysis.
Provides a comprehensive introduction to data analysis with R. It covers a wide range of topics, from basic data cleaning to advanced statistical analysis. It good book for those who want to learn more about using R for data analysis.
Provides a comprehensive overview of machine learning for data science. It covers a wide range of topics, from the basics of machine learning to advanced machine learning algorithms. It good book for those who want to learn more about using machine learning for data science.
Provides a comprehensive overview of data analysis with Excel. It covers a wide range of topics, from basic data cleaning to advanced statistical analysis. It good book for those who want to learn more about using Excel for data analysis.
Shows you how to create macros and VBA code in Excel. It covers a wide range of topics, from basic macro creation to advanced VBA programming. It good book for those who want to learn more about using VBA to automate tasks in Excel.
Provides a broad overview of data science, from the basics of data analysis to the ethical implications of using data. It good book for those who want to learn more about the field of data science.
Provides a comprehensive overview of data science for business. It covers a wide range of topics, from data collection to data analysis to data visualization. It good book for those who want to learn more about using data science to improve business outcomes.
Shows you how to create effective dashboards and reports in Excel. It covers a wide range of topics, from basic data visualization to advanced data analysis. It good book for those who want to learn more about using Excel for data visualization and reporting.
Shows you how to create effective pivot tables and charts in Excel. It covers a wide range of topics, from basic pivot table creation to advanced data analysis. It good book for those who want to learn more about using Excel for data visualization and reporting.
Provides a comprehensive overview of data visualization. It covers a wide range of topics, from the basics of data visualization to advanced data visualization techniques. It good book for those who want to learn more about using data visualization to communicate data insights.
Discusses in-depth, the concept that successful companies can fail due to being so heavily invested in current products and processes that they might fail to invest in innovation or disruptive technologies, and miss the next curve. This book would be of interest to those wanting to read more about the challenges of innovation in business.
Good introduction to data analysis with Excel. It is written in a clear and concise style, and it covers a wide range of topics, from basic data cleaning to advanced statistical analysis. It good book for those who are new to data analysis or who want to learn more about using Excel for data analysis.

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