Data Science University

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Do you hate having to clean your data?

Are you tired of wasting weeks of your precious time trying to find errors and typos in your data?

“Data is a lot messier and noisier than people want to acknowledge” – Nate Silver

Having to correct errors and mistakes in your data is a waste of your time and it gets in the way of your analysis and getting your results.

But there are steps you can take not only to clean your data efficiently but also to minimise the errors going into your data in the first place.

When you learn the steps and the essential Excel tools you need to clean your data, you:

• become more productive and save hundreds of hours
• get your results much faster
• keep your boss happy

I have been there.

Every week, while I was working as a medical statistician at one of the largest research hospitals in Europe, somebody would bring me their new project data and give me the tightest deadline to get it analysed. The problem was that I had to clean it first, which took me weeks every time. So I had to develop a system to get the data analysis-ready quickly – and to also teach researchers how to reduce the errors and mistakes in their data before they gave it to me.

This system was fine-tuned over several years of being a statistician, and is what you will be learning in Data Cleaning in Excel For Analysts and Researchers Fast-Track.

What’s included in the course

This course will teach you step by step how to go from recording your data to getting it clean and ready for analysis. No more, no less. Everything is explained in simple language and is perfect for beginners.

1. Welcome and Overview
2. Data Collection
   1. How to import data into Excel … for when you already have data
   2. How to record data on paper … for when you’re just starting out collecting data
   3. How to enter data Manually into Excel … for when you’ve collected your data and you need to transcribe it into Excel
3. Data Cleaning
   1. How to remove Trailing and Leading Spaces ... and all other invisible and non-printing characters, from your entire dataset in just 60 seconds!
   2. How to clean Text Data ... correcting typos and incorrect entries and getting your text data ready for analysis
   3. How to clean Numerical Data ... identifying and correcting poorly formatted numerical data
4. Data Codification and Classification
   1. How to make your data calculations … use formulae to calculate composite variables and prepare it for analysis
   2. How to code your data … get your text data ready for analysis – including transforming it to numerical codes
   3. Data Types ... learn the difference between ratio, interval, ordinal and nominal data to help make better analysis decisions
5. Data Integrity
   1. Prepare your dataset for analysis ... learn how to transform a dataset that’s been created for data storage into one that’s analysis-ready
   2. Check that your numerical data is sensible ... real life has rules, and so does your data – learn how to discover and correct data that is not fit-for-purpose
   3. Remove outliers ... learn how to quickly and easily identify outliers in your data so you can decide whether to include or exclude them from your analysis
6. Work Smarter

   
   

Some Extra Stuff for You:

• Free - Practical Data Cleaning Guide
•  Free - An Excel workbook to help you get a great start
•  Free - A cheatsheet to print out and stick on the wall – a reminder of all the good techniques

Special Bonus worth more than $1800:

• Free - A 12 month DataKleenr licence
•  Free - 100 DataKleenr Credits

Data Cleaning in Excel For Analysts and Researchers Fast-Track is the right course for you if…

• You are starting on your data science journey and want to learn the essential elements of data cleaning
• You are a researcher and want to stop wasting time collecting and cleaning your data so you can focus on doing your research
• Your data will fit in an Excel spreadsheet
• You want a course that takes you from beginning to end with a clear focus, no unnecessary lessons

Data Cleaning in Excel For Analysts and Researchers Fast-Track is NOT the right course for you if…

• You’re a more experienced analyst who is looking to automate their data cleaning within their programming workflow (e.g. in Python, Java or R)
• You work mostly on merging customer datasets within an organisation
• Your data is so large it won’t fit in Excel

Frequently Asked Questions:

How long will it take to complete the course?

There are 5 modules in the course and you have over 8.5 hours of video lessons in the course. All the materials are available for you from the moment you enrol. You will then be able to work through them at your own pace.

How much time will taking the course actually save me?

When I first started analysing data it typically took me about 2 weeks to clean and prepare each dataset.
It now takes me just a couple of hours to clean and get each dataset analysis-ready.

I already use some of these steps/tools you have mentioned. Why should I take the course?
If you spend more than a week cleaning one single data set, you are wasting your time.
Learning the tools, techniques and procedures in this course will enable you to slash the time taken to just a few hours for each dataset.

What is the difference between this course and Data Cleaning In Excel for Analysts and Researchers?

You get ALL the same content in both courses, so you will not be missing out on ANY of the information, but Data Cleaning in Excel Fast-Track is only open for a limited amount of time.

This means the course is available to you for a period of 15 days. Once this period expires, you will not be able to access the course again but if you have a little bit of time over the next couple of weeks and want to save some money, now is your chance.

There is no live component to this course.

Can I ask questions in the course?
Yes, of course. There is a discussion section in the course where you can ask questions and I will also be available by email.

I am a scientist, not a specialist in data, is this course still good for me?

Yes, it is. Everything is explained in simple terms with the assumption that you're just starting out. The videos, slides, cheatsheets, etc. will show you all the steps so you can apply them again and again to your data.