Introduction to Data Analysis Using Excel

share ›
‹ links

Below are the top discussions from Reddit that mention this online Coursera course from Rice University.

Offered by Rice University. The use of Excel is widespread in the industry. It is a very powerful data analysis tool and almost all big and ... Enroll for free.

Reddsera may receive an affiliate commission if you enroll in a paid course after using these buttons to visit Coursera. Thank you for using these buttons to support Reddsera.

Taught by
Sharad Borle
Associate Professor of Management
and 9 more instructors

Offered by
Rice University

Reddit Posts and Comments

0 posts • 6 mentions • top 6 shown below

r/science • comment
2 points • fizbin

This course just started this week, so it's not too late to join and catch up:

(And if you miss it, I'm sure they'll offer it again)

r/datascience • comment
1 points • datascigeek

Get a certificate. It’s not an indication of knowledge that a hiring manager will trust but it usually moves you up the list and HR will be more likely to pass it on as well.

And knowing what to do when is more important than knowing how to do something. You can always google things, but if you don’t know where to start with a data set thats a problem.

Edit: the Coursera one is relatively low cost and reputable.

My local library also offers free Excel training and the University offers one day topical courses for about $100. Check your library digital resources section.

r/dataanalysis • post
5 points • adrian4635
Recommendations for Coursera courses

In May I graduated with my Bachelors in Mathematics and want to pursue a career in data analytics. I took an Intro to Java course while I was in school. I want to do the self taught route using Coursera courses. Which Coursera courses do you recommend? I plan on taking the following courses

SQL - Databases and SQL for Data Science

Tableau - Data Visualization with Tableau Specialization

Excel - Introduction to Data Analysis Using Excel

Python - Python for Everybody Specialization

I want to take Coursera courses because I live in New York and Coursera was given for free for unemployed people. You can check it out here.

r/humanresources • comment
1 points • justacanadian18

I’d recommend to improve! I’ve used it for a bunch of statistical analysis courses like linear regression, confidence intervals, and hypothesis testing, all completely free! Their Introduction to Data Analysis Using Excel would probably really help your excel confidence! This Human Resources Analytics Course from is all about analyzing employee data to gather HR info like drivers of employee engagement, improving safety scores, and testing the validity of your performance reviews. Again totally free, it is next on my list.

As for what made me interested, I was involved in some competitions in high school and always really liked the HR element of the case studies. Stayed pretty involved through university with more competitions, executive on clubs, internships, etc. Always just gravitated towards HR and have liked it!

Feel free to shoot me a direct if you wanna chat more, I know the recent grad world can be a terrifying, lonely place!

r/financialindependence • comment
1 points • Gibson19

100 percent this. Typically a data scientist is gonna have some sort of mathematics background. That's not for everyone. Its why they get paid 6 figures fresh out of college (often Masters/PhD level graduates). But there's still a huge gap between the average business analyst and a data scientist, and its filled by data analysts.

So if you ignore the more advanced aspects like AI/ML, NLP, hell even big data or non relational databases. Understand the core concepts of doing data analysis you'll likely carve a pretty good role for yourself. I've sat on teams of analysts and been a hero for being able to run simple SQL queries.

My curriculum for data analysts would start with a heavy focus in:

  • ETL. Extract/Transform/Load.. essentially prepping the data for analysis

  • Data Visualization. Lots of UI friendly point and click options that you can apply best practices too without advanced statistical modeling.

  • Excel. Not so much because its the ultimate analysis tool. But it can do a lot and can give one a good sense of creative problem solving in both prepping data and running analysis. Lots of novel plugins as well like Fuzzy matching, and the analysis toolpak

Once you're comfortable with those, then you can explore R and Python (numpy, pandas, etc..). Learn how to apply your critical thinking/problem solving to the huge libraries of code that exist in those tools.

A few courses I just quickly snagged from Coursera that would be good for a newbie: