Learn Excel for data analysis from basic to expert level and be able to apply this practical skill in any field. It explores spreadsheet software’s most relevant features which will help you become an expert as beginner, achieve proficiency as basic user or polish skills and finish learning curve as an intermediate one. All of this while using real-world data together with practical exercises done step-by-step.
Become an Expert in Excel for data analysis by learning its most relevant features.
Achieve Excel for data analysis proficiency and be able to apply it in any field.
Learning Excel is essential for any professional or academic career based on data analysis. It is the most commonly used data analysis software both professionally and academically and it’s a solid foundation before learning any other.
But as learning process can become difficult as complexity grows, this course helps by leading you through step-by-step real-world practical exercises for greater effectiveness.
Content and Overview
This course contains 39 lectures and 6.5 hours of content. It’s designed for all Excel knowledge levels and no previous familiarity is required.
At first, you’ll learn how to use main file types depending on data format and how to protect it when sharing. Then you’ll study how to store data in workbooks containing one or more worksheets and their navigation by identifying cells as intersection points of columns and rows. This can be done quicker when using keyboard short-cuts.
After that, you’ll perform data calculations with formulas and built-in functions, correct any errors in them, and perform input validation when interacting with users. Next, you’ll visualize data with conditional formatting and charts. You’ll organize it interactively with tables and pivot tables which can be sorted and filtered.
Later, you’ll implement scenarios with what-if analysis. You’ll also do data analysis through statistical and probabilistic add-in tools such as identifying trends, deliver descriptive statistics and frequency histograms, evaluate correlation and causation between explained and explanatory variables, and simulate random numbers with pre-defined or user-defined probability distribution functions. Finally, you’ll optimize a formula’s result using solver add-in by defining changing variables and their constraints.
Before starting course please download .XLSX Microsoft Excel file by as additional resources.
In this lecture you can download slides with section lectures’ details and main themes to be covered related to course description (objectives, requirements and instructor profile) and course overview main sections (excel file, formulas and functions, and data analysis).
In this lecture you will learn which are the course objectives, how you will benefit from it, its previous requirements and my profile as instructor.
In this lecture you can download slides with section lectures’ details and main themes to be covered related to Excel file (file options, workbook, worksheet, cell, range and keyboard shortcuts).
In this lecture you will learn main file options (open, save and print) and key protection options (workbook, worksheet and cells).
In this lecture you will learn that a workbook is a spreadsheet file containing several worksheets. You will also study main file types (standard .xlsx, macro-enabled .xlsm and comma-separated values .csv) and ribbons (menu tabs, customize and minimize options).
In this lecture you will learn that a worksheet is composed of a large number of cells where data can be stored, manipulated or displayed. You will also study main worksheet options (insert, rename, move, delete, copy, zoom, split and freeze panes).
In this lecture you will learn that a cell is an intersection point of a vertical column and a horizontal row. You will also learn main column and row options (insert, delete), key cell formats (general, date, number, currency, percentage, accounting, scientific, time and fraction) and general cell references (relative, absolute, mixed, 3-D and external).
In this lecture you will learn that keyboard shortcuts are useful for performing actions more efficiently to increase productivity. You will also study main CTRL, SHIFT and ALT keys’ options (CTRL + a, CTRL + c, CTRL + v, CTRL + x, CTRL + z, CTRL + arrow, SHIFT + arrow, CTRL + SHIFT + arrow, ALT + =, CTRL + d, CTRL + 1), F keys’ alternatives (F1 to F12) and key tips with ALT or F10 (ALT/F10 + n).
Diego Fernandez is author of high-quality online courses and ebooks at Exfinsis for anyone who wants to become an expert in financial data analysis.
His main areas of expertise are financial analysis and data science. Within financial analysis he has focused on computational finance, quantitative finance and trading strategies analysis. Within data science he has concentrated on machine learning, applied statistics and econometrics. For all of this he has become proficient in Microsoft Excel®, R statistical software® and Python programming language® analysis tools.
He has important online business development experience at fast-growing startups and blue-chip companies in several European countries. He has always exceeded expected professional objectives by starting with a comprehensive analysis of business environment and then efficiently executing formulated strategy.
He also achieved outstanding performance in his undergraduate and postgraduate degrees at world-class academic institutions. This outperformance allowed him to become teacher assistant for specialized subjects and constant student leader within study groups.
His motivation is a lifelong passion for financial data analysis which he intends to transmit in all of the courses.