Start date: 7 May 2018
End date: 18 June 2018
Price: €200 (if you are in the EU, then because of the EU-regulations, you have to pay the VAT of your country as well - except if you are a business entity with an EU-tax-number.)
The max. number of attendees is 25!
ps. If you are from Hungary, please email me before you register: email@example.com.
The agenda of the 6 weeks
If you enroll, you will receive a data science task via email or video every Monday, Wednesday and Friday for six weeks. One or two days after receiving each task you will get the solution from me: the code base sent in text format and the detailed explanation sent in video format. The tasks:
Monday: I’ll send you the intro videos and you will also set up your own data server (with SQL, Python, pandas, numpy, etc.). I’ll give you free access to my other 1-hour video course and a 2-month coupon for a DigitalOcean data server.
Wednesday: Get the raw data! We will download and transform the raw data of the Send-a-Tree startup.
Friday: Automate the dataload.
Monday: Put everything into SQL. (You will also set up SQL Workbench.)
Wednesday: We will automate the whole SQL import process. And then we will run some exploratory data analyses.
Friday: Create and analyze segments. You will try to give some advice to the hypothetical marketing department based on the data, focusing on the different subsegments: who to target and why! (Basic SQL task)
Monday: A more complicated segmentation task where you also have to run revenue calculations. (Intermediate SQL task)
Wednesday: Let’s take a step back and think a little bit about the most important business metrics. What can help you the most to measure the success of Send-a-Tree? Create the SQL query to get it! (Advanced SQL task)
Friday: Visualize! Once you have created your business metrics, you will want to present them in a meaningful way, so the whole company understands them! (Google Data Studio)
Monday: Funnels! We will generate a basic funnel to measure the purchase process and generate a visual. (Advanced SQL task)
Wednesday: Warm-up task to create a cohort analysis in Python for a smaller data set. (Basic Python task)
Friday: Cohort analysis on our real data set. (Basic Python task)
Monday: Basic predictions with Python. (Intermediate Python task)
Wednesday: We will predict the number of expected registrations -- using two different regression models! (Intermediate Python task)
Friday: We will try to categorize the unknown values in our data table using a powerful statistical concept called classification. (Advanced Python task)
Monday: You will get a new data set from another fictional startup and a final task to test your freshly gained data science knowledge. You will have 4 days to solve this new task, and if you send me your solution, I'll personally evaluate it and give you feedback about it.
Friday: Deadline for the final test task.
Monday: Evaluation of the final test task. Wrap-up.
Tomi Mester is a data analyst and researcher. He worked for Prezi, iZettle and several smaller companies as an analyst/consultant. He’s the author of the Data36 blog where he writes posts and tutorials on a weekly basis about data science, AB-testing, online research and data coding. He’s an O’Reilly author and presenter on conferences like TEDxYouth, Barcelona E-commerce Summit or Data Conf.