DataLearn is DataHack's workshop track. It aims to provide participants with the opportunity to build and improve their data science skills. We focus on participants which are relatively new to data science, or don’t practice it in their day to day work.
We will provide participants a decent but modest theoretical background and highly practical coding workshops in python, covering various topics and skill levels.
Attending the full track of this program will enable software engineers with little to no data science experience to build models, participate in data science competitions and acquire the basic knowledge needed to explore further on their own.
Additionally, DataHack attendees with the proclaimed goal of learning will enjoy close mentoring, and some extra attention to their needs and to providing them with the best learning experience possible.Got questions? Check out the FAQ!
Pre-Conf, September 25th
Introduction to Machine Learning with Python
A workshop aimed at those new to Python programming or data science, it covers both basic theoretical background and practical skills required to successfully tackle your first data science project!
Sign up here! And the Facebook event is here!
Prerequisites : A pulse and a desire to learn data science :P
Introduction to Deep Learning
Aimed at those with some experience in Python programming for data science, this track will offer a concise theoretical introduction to Deep Learning, as well as hands-on workshops on a popular Python framework for Deep Learning.
Finally, we will put it all to the test by Kaggling together.
Prerequisites: Familiarity with python, basic regression/classification methods, have coded a ML model before (all covered in the Pre-Conf workshop).
Practical Machine Learning with Python
Aimed at those with basic data science & Python knowledge (including graduates of the Pre-Conf track), this track covers best practices, tips & tricks and lots of code to make your models as good as it can be, and avoid common pitfalls. While focusing on the practical hands-on side, we will cover techniques like data cleaning, model evaluation, hyper-parameter tuning, gradient boosting and AutoML. Finally, we will put it all to the test by Kaggling together.
Prerequisites: Familiarity with python, logistic regression and gradient descent (all covered in the Pre-Conf workshop).
How do I sign up for DataLearn 2018?
Simply sign up to DataHack 2018, and choose the "Workshop Track" in the Track field of the registration form.
How do I sign up for a specific track of DataLearn?
You do not need to sigh up for a specific track; you'll choose a track by simply attending its lectures.We will let you know if this will change.
Is it free?
Yes, like everything else in DataHack 2018, our workshop track is also completely free for all participants.
Do I have to have a team to join DataLearn?
No, but we highly encourage you to try and use the DataHack participants Facebook group and the registration system team board to find an existing team to join or other participants to team up with.
Do I have to participate in the main competition to join DataLearn?
No. You can just come for the workshops on Wednesday night, and then hang around as much as you want to work on some fun learning project with some help from our mentors. But don't blame us when we try and convince you to present the cool project you'll end up making!
Can I get a full agenda for the Practical ML track?
18:00 - 19:00 : Preprocessing for ML
19:00 - 20:00 : ML Tuning
20:00 - 20:30 : Dinner
20:30 - 21:30 : Advance Modeling & AutoML
21:30 - 22:00 : Kaggling
Can I get a full agenda for the Deep Learning track?
18:00 - 19:00 : Neural Networks
19:00 - 20:00 : CNNs
20:00 - 20:30 : Dinner
20:30 - 21:30 : AutoML
21:30 - 22:00 : Kaggling
What track should I attend?
Well, you got four options here:
(1) If you have never practiced data science / python before, we strongly suggest you attend the Pre-Conf - Introduction to Machine Learning with Python workshop.
(2) If you have some experience in practicing data science with Python OR fully attended the Pre-Conf workshop and liked what you've seen, and you want to improve your data science practice with up to date industry tips & tricks, then the Practical Machine Learning with Python track is for you.
(3) If you already have experience with practicing machine learning with Python, and you want to use DataHack to dive into Deep Learning, then we suggest you attend the Introduction to Deep Learning track.
(4) Finally, if nothing mentioned so dar fits the bill, then simply signing up to DataHack 2018 is the track for you; You'll still get great personal mentoring and be able to go into any workshop or lecture at the event.