Start date: 2 July 2018
End date: 10 August 2018
Price: $347 (In the EU, you have to pay additionally the VAT of your country as well.)
The max. number of attendees is 30!
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.
16 Exciting data science tasks
26 Video solutions (~5 hours in total) with in-depth explanations
16 Code-based solutions, immediately usable
Dedicated class Slack group and the power of networking with fellow students and alumni
1-on-1 call to discuss your career path
Email Support - if you get stuck
+1 free access to another video tutorial on how to install your data server so you have a data environment to practice
(a video from the intro section of the course)
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.