Getting The Most Out Of This Course

...And understanding the Course Layout

I wanted to start with a few bits of information that will help you get the most out of this course. 98% of the course is video-content so please don't take offense to this text-lecture. Some things are just better conveyed through writing.

Modules

The course is structured into Modules. Each module is a main stage in the learning process. In general, the module progression starts off slowly to build your confidence in working with the problem and the code. Module 0 and 1 may seem very slow for some people, but fast for others. Just realize that the pace picks up especially once Module 3 (Data Preparation) hits. The progression follows the Business Science Framework and CRISP-DM steps (which are explained in Module 0).

Directory Structure

Our Course Directory Structure follows CRISP-DM. In the early stages (Module 1), it looks like this:

The directory fills up with our .R files as we go.

Module Overviews (Important Downloadable Content)

Each module begins with a Module Overview TEXT section (read it, it is short) that overviews the module and PROVIDES DOWNLOADABLE CONTENT. The downloadable content are data and scripts that we will read and source, respectively. A snapshot of the directory is shown, which is nice for those that wish to make sure they are following the course code progression.

Regarding coding, I provide only the Scripts that contain the main functions we create along the way. These scripts are to be saved in your "00_Scripts" folder. The scripts are mainly for fast-paced learners that wish to blast through the custom function lectures. The main coding folders, which begin with our folder "0.1_Business_Understanding", are to be created by you via coding alongside me (virtually of course). It is important in your learning to actually recreate what I'm doing. It will also help you once you get to the...

Challenges

Many of the modules contain Challenges, which are somewhat more involved problems that you will need to solve using the knowledge you gained in the module. The module sub-sections also contain Knowledge Checks, which are smaller in scope than Challenges and are typically completed quickly (5-10 minutes).

End of Module Code (Code Checkpoints)

At the end of the Modules I provide the code used (code checkpoint). This is based on feedback from several students that the code will help if you get stuck. Please use it for this reason (and don't cheat by just downloading the code). Recreating the code as you follow through is the best way for learning... period.

Appendixes

I include many useful links, references, and content at the end of the course in a miscellaneous section called Appendixes. Definitely check it out if you want to learn more.

Overall

Overall, the course is large in scope. This is necessary to go into the level of detail that we need to cover my main goals with teaching you:

• How to understand a business problem
• How to tie data science to financial impact
• How to code effectively for data science
• How to use the tidyverse and program with Tidy Eval
• How to implement data science project management frameworks
• How to manage an analysis using an R Project
• How to use H2O, LIME, and various other R packages that are amazingly useful

It's well worth the investment you are or your organization is making. I firmly believe this. In fact, I modeled the course after what I wished I had when I was starting (after I got through the data science basics).

Last, each lecture has a Comments section. If for any reason you have a question, concern, or see an error/omission, please post it there. I am monitoring comments closely.

I hope you enjoy this course. It was extremely fulfilling creating it, and I even learned some things through the process. Now, let's get started!

-Matt Dancho, Founder of Business Science

...and instructor of the DS4B 201-R course!