Description
“Who buys training from Brent? A guided data science project.” Work with real data to find out who buys training in this data project. Learn the data science principles and the R code you need as you work this project answering the question of “Who buys training from Brent?”
Meta, eh?
In this thoroughly hands-on training course we’ll go from data in various sources to a working model in two days.
Our workflow will look like:
- Consolidating multiple data sources into single dataset ideal for trying to predict who will buy training.
- Deciding the right sampling strategies, so we can build predictions and test them.
- Building different types of models to see which things influence whether someone will buy training.
- With multiple models on our hands, which one is the best fit with reality? We’ll use evaluation techniques to identify the model that best identifies Brent’s future customers.
- Once we have this info we’ll look at how we can use the model to make some predictions so that Brent can think about his marketing strategies.
This just-in-time learning approach will equip you to handle similar projects and you’ll know the workflow for any other data science project. As well as the guided project materials, you’ll also get a whole heap of extra resources on coding R and doing data science to help you extend your coding and data science skills so that you can go on to do even more projects in future.
So register to hands-on with this nifty and relevant data science challenge!
Prerequisites:
- We will use a prepared environment available via browser to save infrastructure issues but if you want to to do everything on your machine, then you will need to install R, RStudio, and the SQL Server ODBC 13 driver.
- It will also be helpful if you have SQL Server Management Studio or some other interface available that will make it easier to browse a database.
About the instructor: Steph Locke is a Microsoft Data Platform MVP with a decade of business intelligence and data science experience. Having worked in a variety of industries (including finance, utilities, insurance, and cyber-security,) Steph has tackled a wide range of business challenges with data. She has a broad background in the Microsoft Data Platform and Azure. She’s equally conversant with open source tools; from databases like MySQL and PostgreSQL, to analytical languages like R and Python.
This is a live online class. We host it in GoToWebinar, live with Steph Locke on webcam, with a 75-minute lunch break. Audio can come through either your computer audio, or by dialing into a US phone number – headset recommended either way. For more information, check out the Training Logistics PDF for our online classes.
You can watch again later with Instant Replay – after class, you’ll be able to keep re-watching for a year. Brush up on stuff you missed or revisit your favorite topics. It’s the best of both worlds: live training with Steph, plus reminders.
Class dates & times:
- May 10-11, 2018 (Thurs-Fri) online 9:00-5:00 Eastern (14:00-22:00 UTC) (click to see in your own time zone)
Juan Sanchez (verified owner) –
I’ll echo most of what’s been said in the earlier review. Steph is a very knowledgeable subject matter expert. The course delivery and materials were also very good. And I did walk away with a high-level understanding of what is possible with R and Data Science in general. And for my purposes and job role that was probably enough. However, I think 2 days is far too little to try and teach two quite deep subjects for anyone really looking at this as a way to start “doing” data science with R. That is, learning the fundamentals of R from zero I believe would take at least 1.5-2 days. The ecosystem is huge! Next since the course is titled Data Science Fundamentals, I expected a more comprehensive coverage of actual data science fundamentals. Unfortunately, there just wasn’t enough time. Looking through the syllabus listed here, we weren’t able to cover Visualization and Machine Learning fundamentals in any real depth that would help me understand why and which methods we should use to analyze our data much less how to interpret results. At some point the course felt like I was just watching someone code but I didn’t really understand what the outputs meant.
Keith –
I thought the class was enlightening and I enjoyed it primarily because I see how much work one must do to really be worthy of being called a data scientist.
I think with the amount of material we had to cover, a 3 day course length would be ideal with the same amount of material. Hence my 4 star rating.
With that said coming into the course with a basic knowledge of R I was able to follow along and now understand more about the ending processes in Machine Learning which I’ve never seen before. I took this as a fundamentals class and believe that is what I got out of it.
Steph is a friendly instructor and never made me feel embarrassed about my lack of R knowledge, while maintaining her expertise with R
For anyone who takes this course in the future definitely eat your Wheaties and isolate yourself from distractions as you can get a lot out of it if you put into it.
Matt –
Class should really be titled intro to the R language. Data Science was an after thought, and the parts that we went over either didn’t work, or were so haphazard to barely make any sense. Was really expecting a lot more information about the how and whys of Data Science as is indicated in the class name and synopsis. Do I felt like I learned R 101? Yes, but I can get that from a free online course like Data Camp.
Bill C (verified owner) –
I had two goals from two problems. I don’t know R, and started a masters class that requires it, so I wanted a head start. Goal 2 was to learn how to work SQL Server and R together for work.
Goal 1: Absolutely 5 stars! I got what I needed and much more. It was a lot of info needing to digest, but I’m where I need to be for my class.
Goal 2: 3.5 stars. The time allotted to the SQL Server connections and processing wasn’t enough when we ran into issues running some code. I think if the issues weren’t there, the time would have been OK. Average (yes – it’s an R class, how can I not have an average?) – 4.25 stars. BUT – given the various other tidbits and that I think I have what I need to get R and SQL Svr to talk, the extra .75 star is a given. It was great training!