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The Junior Data Scientist's First Month (Class of May, 2018)

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

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Details

Start date: 7 May 2018

End date: 18 June 2018

Price: $347 (In the EU, you have to pay additionally the VAT of your country as well.)

The max. number of attendees is 25! -- SOLD OUT! (If you want to hear first about when you can register again, email me at: hello@data36.com)

ps. If you are from Hungary, please email me before you register: hello@data36.com.

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.

This course is not open for enrollment.

You will get access to these things:

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

Send-A-Tree, the hypothetical startup you will work on

(a video from the intro section of the course)


Your Instructor


Tomi Mester
Tomi Mester

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.


Frequently Asked Questions


How long do I have access to the course?
How does lifetime access sound? After enrolling, you have unlimited access to this course for as long as you like.
What if I am unhappy with the course?
I would never want you to be unhappy! If you are unsatisfied with your purchase, contact me in the first 30 days and I will give you a full refund.
How big is the data set you will work with?
The dataset grows day by day during the course as the new user data flows in. By the end of the course, in total you will work with a data set of 2.5 million lines and around 12 million data points.
What languages will we use in the course?
We will mainly use SQL and Python. And we will also use a little bit of bash. In this course, we won't work with R.
What if I don't know Python, SQL and bash yet?
If you don't know SQL, Python or Bash - or none of them - don't worry, most of the course participants are in the same situation. The point of this whole course is to show you the missing pieces of your current data science knowledge - for some this is less, for others this is more - and make you learn those missing parts via practical exercises. Just so you know, I’ve even had participants who started the course without knowing any of these data languages and they successfully finished it… Of course, they had to work harder than other participants but I think it was definitely worth it for them.
How much time does a task take?
A task will usually take 1 to 3 hours of active work, depending on your current data science knowledge.

This course is not open for enrollment.