Excel for Data Analysts
The perfect starting point for learning the most common features, charts, and functions of Excel for data analysts. This free course provides a demo and hands on training of the day-to-day features that you'll use on the job.
About the Excel for Data Analysts Course
The perfect starting point for learning the most common features, charts, and functions of Excel for data analysts. This free course provides a demo and hands on training of the day-to-day features that you'll use on the job.
Skill Level
Beginner
Video Length
60 min
Pre-requisites
Basic computer skills
Certificate of Completion
Excel for Data Analysts: Course Content
01. Introduction
Introduction to your instructor and the course content.
02. Common Excel Functions
Learn the common functions to navigate Excel with sheets, sorting, filtering, grouping, hiding, and basic formula usage.
03. Useful Functions
Learn to use the most common functions including sum, sumif, count, countif, min, max, xlookup, vlookup, quartiles, mean, median, mode, and more.
04. Standard Charts and Graphs
Learn to use the most common charts including bar chart, line charts, scatter plots, pie charts, dual axis charts, and Pareto charts.
05. Pivot Tables
Learn to use and navigate Pivot tables with ease.
06. Course Wrap-up
Where to get more information to advance your skills and career.
"I feel like I found a goldmine!"
"I remember my tutor trying to teach me C++. Nightmare. Brandon explaining SQL. Crystal clear."
Your Instructor:
Brandon Southern
Sr. Leader - Head of Analytics: US Prime & North America Stores Marketing at Amazon
Meet Brandon Southern (Sr. Leader at Amazon). Brandon is an expert data analytics and engineering, with over 20 years of experience in software engineering, quality assurance engineering, software release management, data engineering, and analytics. With more than 12 years of leadership experience across these domains, he has interviewed, hired, coached, and elevated professionals like you!
As a Senior Leader of Business Intelligence at Amazon, he leads business analysts and business intelligence engineers. He has a passion for helping others grow and developing world-class analytics solutions and teams, which led him to create Analytics Mentor. In his courses and coaching sessions, he will teach you how to develop the necessary skills to become one of the best professionals in the field of data and analytics. He will also show you how to incorporate the best practices that he has developed after working across multiple engineering roles. With his coaching, you'll develop your resume, prepare for interviews, negotiate for higher salaries, and grow your career. By the end of it, you'll become a world-class analyst and engineer and learn the best practices and skills that almost no other analytics team (even in the top tech companies) are using today!
Frequently Asked Questions
Why should I become a data analyst?
It's totally up to you. But I love this field and being a data analyst unlocks so many job opportunities, income, and flexibility in your work life.
What are the requirements for this course?
You'll need access to a computer or mobile device and you'll need access to the internet to view the course content. You will not need any special software to follow along, but if you would like to perform the course exercises along with me, you'll need a Windows or Mac computer to install Microsoft Excel.
How can your career progress after becoming a data analyst?
You can transition into almost any role. The best data analysts not only understand data, and technical software, but they have an introduction to programming, business operations, and more. Data analysts have the potential to become data engineers, business intelligence engineers, data scientists, product managers, software developers, quality assurance engineers, and more.
How much money can a data analyst make?
In 2023, the median salary for data analyst was approximately $73,000 according to Indeed. However, the salary can go above $500,000 per year depending on how you advance with your education, years of experience, skills, role, title, location, and company that you work for.
