How do the modules build up?
As I mentioned in the intro video, there are five big modules in this course. They represent the five big types of data sources that you can use to get raw data. These are:
- REAL LIFE DATASETS
- RANDOMLY GENERATED DATASETS
- WEB SCRAPING
- OPEN DATASETS
How do these modules build up?
After creating all modules I realized that the REAL LIFE DATASETS and the RANDOMLY GENERATED DATASETS modules are very similar to each other.
In these, I give you direct access -- basically direct urls -- to my datasets that are located on my servers -- and so for each of these datasets I list three things:
- the structure of the data: where are the different data tables, columns and data points in the given data sets -- what means what -- and so on...
- how to get the data: urls and command line commands -- in other words: what exactly you should do to download the data to your server or computer
- random project/analysis ideas: a few ideas about what you can analyze in these datasets.
So these are the real life and randomly generated datasets.
The other two big modules, the APIs and WEB SCRAPING modules, are also very similar to each other. In these two modules:
- You'll see tutorials that teach you how to use the given concepts: APIs or WEB SCRAPING.
- You'll get all the Jupyter Notebooks that you'll see in my tutorial videos, so you can instantly re-run my code.
- And of course, in these modules, too, I'll list a few analysis and project ideas.
And then the fifth module, the OPEN DATASETS module, is just a list of open datasets, so nothing special.
Oh and one more thing, as I created this course, I've realized that I want to add a few more bonus lectures, so in some modules I talk about how to automate the data-load and a few other things, so you might want to check that out, too. Also, I’ll likely add more and more bonuses to the course over time -- probably new data sources and Q&A sections and so on...
Point is: everything I put into this course is focused on one thing: to help you get access to as much raw data as possible, as easily as possible.
Okay, this is the course curriculum -- now, you can go ahead and discover it by yourself!