Data Science Hobby Project Club

Practice Data Science. Boost Your Data Science Portfolio. Stand Out.

I say this to everyone who wants to get a job in data science:


"Once you have the basic data science skills, you should start working on your first data science hobby projects."

Tomi Mester

Why is it important?


In one sentence: to stand out when it gets to job applications.


If you have ~2-3 hobby projects on your portfolio (and on your GitHub), hiring managers will prefer you above others who don’t.


Why? Because they’ll instantly see that:

  • you can use your skills (e.g. Python, algorithmic thinking, etc.),
  • you are committed,
  • you can solve problems,
  • you are creative,
  • etc.

You will stand out.


Yes, data science hobby projects are great for your DS career!

But it’s hard to get started with hobby projects…

Despite, I keep saying “do hobby projects — do hobby projects — do hobby projects” to everyone, only a few people actually start with it.


I get it. It’s hard to get started for so many reasons.

  • It’s hard to come up with the right project.
  • It’s hard to find available datasets.
  • Sometimes, it’s hard to find motivation, as well.

And even if you have all these, it's hard to take the first step and type that first line of code.

data science hobby project first step

Here’s the solution…

In the last few months, I was working on a brand new product that will help you get done your first few (or more) hobby projects.


It’s a club I call the:

Data Science Hobby Project Club

(I know, I’m not very creative with course names.)


It’s a membership product. And I mean it to be the “Netflix of Data Science Hobby Projects.”


The concept is super simple — in this course, I list a few data science hobby projects (well, I call them challenges) that are the perfect fit for a soon-to-be junior data scientist.


For each of these challenges, you’ll find:

  • A task. A description of what I expect you to do to get started -- and then finish that given hobby project.
  • The dataset. The detailed description (sometimes video tutorials) of how you can get that data.
  • Hints. A few tips if you get stuck.
  • The solution. I'll show you how I’d solve the given task. This means a ~30-45 minute webinar recording where I explain my thinking process -- and of course I'll share the whole codebase (usually in Python, in Jupyter Notebook format) that you can download and review line by line.

Well, the idea is that you read the task description of the given hobby project -- then you download the data -- and then you start to implement your own solution. And then you put your solution into your data science hobby project portfolio.


I chose hobby project ideas that can be done in a reasonable amount of time (with 10-20 work hours), and still look great on your portfolio.

artificial datasets data source course


What sort of hobby projects will you find in the course?

So far, we have 3 different hobby projects in the course (I call them monthly challenges by the way):

  • A real-life data science project. You can analyze the dataset of a real online business.
  • Stock market analysis project. We'll get real (even live) stock market data and you'll have to find correlations between different (real) financial assets.
  • Web scraping. We'll scrape IMDB’s website and calculate the ROIs of different movies.
  • ...

And this is just the beginning.

For the next few months, each month, I'll add a new challenge (a new hobby project), too!


If you decide to participate in these live challenges, as well, after getting the given monthly task, you'll have a few weeks to solve the task by yourself. (In the meantime, I'll publish hints, I'll provide help and support if needed.) And at the end of the month I'll present the solution in a live Zoom call. (The Zoom call will always be recorded -- and it'll be published as the solution video in the course, so you can watch it any time, not just live.)


The live part is valuable because if you participate in it, then:

  • You can send in your solution which I'll give feedback about in email personally.
  • You can discuss the task and your thinking process with your fellow club members in the Slack community.
  • You can participate in the Q&A of the task in the live call and ask your questions…
tomi explaines a data science hobby project

But there's even more...

Get more data!

I know some of you are coming to this course with the desire of working on your own hobby projects. To manage expectations: at this version of the course, we won’t work on your personal hobby projects -- but on the ones that I picked for you. (Sorry.)


Regardless, I want to help you to get started with your own projects, too. For that I created a mini-course called Data Source, that fixes the #1 problem when it gets to data science hobby projects: getting the data.


This learning material will show you how to use APIs, how to do web scraping, how to generate random data for yourself and it lists open data sources, too.


The members of the Data Science Hobby Project Club will also have access to these tutorials.

So to summarize it, as a member:

  • You’ll have access to the 3 currently listed hobby project tasks and solutions (code + webinar recording)
  • You can participate in the upcoming challenges of the next months
  • You can participate (and ask your questions) in the live Zoom calls
  • You can send in your solutions for the monthly challenges to get personal feedback
  • You can communicate with others in the private Slack community.
  • You’ll have access to the Data Source course (and learn how to get data for almost any hobby project)

But most importantly:

  • You’ll improve your data science skills the fun way.
  • You’ll be able to boost your hobby project portfolio -- and your CV.
  • And if you work hard and go through the projects, you’ll stand out when it comes to job applications.

Presenter

hi, I'm Tomi Mester -- a practicing data analyst and researcher since 2012.


I've worked for Prezi, iZettle and several smaller companies as an analyst/consultant.


I'm the author of the Data36 blog where I write articles and tutorials on a weekly basis about data science, A/B-testing, online research and coding.


I'm an O'Reilly author and presenter at TEDxYouth, Barcelona E-commerce Summit and Stockholm Analytics Day.


Check out my intro video. >>

How it works

Important! This is a membership product.


It works similarly to Netflix:

If you register, you'll get instant access to all materials mentioned above:

  • the previous three months' challenges (that are already recorded)
  • the upcoming monthly challenges (the live element of the club)
  • the Data Source mini-course

And you'll have access to these materials as long as you are a member of the club -- so as long as you have an active subscription.

The price of the membership is $39/month. (Plus your country’s VAT if you live in the EU.)


The price is charged automatically on a monthly basis. The subscription can be cancelled any time.


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

Guarantee

I worked (and will keep working) really hard to make this product the best available, and I stand behind it 100%.


I understand that enrolling in a membership product is not always an easy decision, so I made this decision totally risk-free for you: if you request one, I’ll give you a full refund within the first 30 days.

Is this course/club for you?

IMPORTANT! This is not a beginner level course… I don’t want you to struggle with tasks that are not meant for you, so please enroll only if:

  • You are confident with Python, pandas and basic dataviz methods in Python -- and you know how to work in a Python environment.
  • You know how SQL works. You know how to use an SQL manager tool.
  • You are familiar with basic data wrangling methods (e.g. in the command line or in Python, or in any tool you prefer.)

If you still don't know whether it's you, here are a few things that will most definitely qualify you for this course (they are not musts though):

  • you have already finished the Junior Data Scientist First Month course
  • you already have at least one basic Python-based project done (and preferably published on your Github)
  • you are currently working as a junior (or intern) data scientist/analyst but want to learn more (or boost your CV more for your next job application)

If you still don't know, just reach out to me and I'll help you to decide.

Do not enroll:

  • If you don’t know how to set up your own data science environment (e.g. you don’t know how to install new Python libraries or how to use an SQL manager, etc.)
  • If you are not an already confident Python user. (e.g. you are not comfortable with using for loops, if statements, basic pandas functions or basic data visualization methods in Python)
  • If you don’t know basic problem solving methods in data science (e.g. reading error messages, finding answers on Google/StackOverFlow, etc, etc.)

IMPORTANT! As I just said, this is not a beginner level data science course — if you enroll and you get stuck with these very beginner issues above (“I don’t know how to put this data into an SQL table” — “I don’t know how to install pandas'' — “my if statement throws an error”), I’ll keep the right to refund you and unenroll you from the course. (If so, you’ll get back your payment, of course.) In that case, I’ll also point you to the right beginner course that can help you to achieve the level that's required for this course. (And don’t get me wrong, I don’t mean to be rude here. I have online courses for beginners where I’m more than happy to help you if you are a beginner. But in this one — and with the community I build in this course — I’d like to talk about the more complex data science problems: business decisions, complex solutions, how to build a project, how to prototype, etc., etc.)

Registration

Price: $39/month (+ VAT in EU)

The price is charged automatically on a monthly basis. The subscription can be cancelled any time. You'll have access to the course materials as long as you are a member of the club -- so long as you have an active subscription.

If you are from Hungary, please send me an e-mail before you register.

Clicking this button will take you to the check-out page where you can pay safely using your credit card or your Paypal account! (If you are registering from the EU as an individual - in accordance with EU law - you have to pay the applicable VAT of your country, too.)

Frequently Asked Questions

Are there any prerequisites?


Yes! If you’re taking this course, you are probably not an absolute beginner in data science. I'll assume that: 1) You are confident with Python, pandas and basic dataviz methods in Python. 2) You know how to work in a Python environment. 3) You know how SQL works. 4) You know how to use an SQL manager tool. 5) You are familiar with basic data wrangling methods (e.g. in the command line or in any tool you prefer.)


If you don't have these, please go to my tutorials on data36.com -- or finish the Junior Data Scientist's First Month course first.


When does the course start and finish?

Data Science Hobby Project Club is a membership product. You'll have access to the course materials as long as you are a member of the club -- so as long as you have an active subscription. You can cancel any time.


What if I don't have a data science environment in place?


Please set one up following my tutorials on data36.com.


How much time does the course take?


It really, really depends on you. In theory, each challenge takes ~10-15... With one challenge a month it's ~10-15 hours per month, right? But if you want to go deeper... Well, you can go as deep as you just want -- but then the course will take more time. ;-)

How will I be charged?


You will be charged automatically on a recurring monthly basis, starting from the sign-up date. You can cancel at any time.


How long do I have access to the course materials?


As long as you have an active subscription.


Can I pause/cancel my membership/subscription?

Yes. Once you login, click your profile icon, followed by “Manage Subscriptions”. From there you can edit your payment method or cancel your subscription. If you can't find something, email me and I'll do this for you: tomimester@data36.com.


What if I am unhappy with the course?


I would never want you to be unhappy! If you are unsatisfied, contact me in the first 30 days and I will give you a full refund.


Will I get an invoice?


Yes. Individuals can get a receipt in the email. Companies can get an invoice. EU-based companies can get VAT-invoices. Unfortunately, the online school I use (Teachable), doesn't send this out automatically. So if you need any of these please let me know in the email (tomimester@data36.com) and I'll send you the invoice/receipt manually every month. With any questions, write here: (tomimester@data36.com) -- and we will solve your administrative issues!


I want to have this for my whole company!


Happy to hear that! Send me an email to workshop@data36.com and we will sort it out! (I hold 1-day live workshops, too.)