Tomi Mester – Class of November, 2018 – The Junior Data Scientist’s First Month

Tomi Mester – Class of November, 2018 – The Junior Data Scientist’s First Month

100% practical 6-week data science challenge & video course — simulating of being a junior data scientist at a true-to-life startup

Course Curriculum

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:

WEEK #1

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.

WEEK #2

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)

WEEK #3

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)

WEEK #4

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)

WEEK #5

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)

WEEK #6

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.

WEEK #7:

Monday: Evaluation of the final test task. Wrap-up.

Your Instructor