Instructed by Dr. Stylianos Kampakis

Course Description






Agenda






09:30 – 10:00 Registration


10:00 – 12:30 Masterclass


12:30 – 14:00 Lunch


14:00 – 18:00 Masterclass


We will send out the class materials as well as required library 2 weeks before the class, please follow the instruction and get the environment ready before coming to class.
Who should come? 


Data Analyst


Developers and Software engineers


Business Intelligence (BI)


Junior Data Scientist


What will participants need to know or do before starting this course?
The course assumes that students do not know Python or machine learning, but that they do have some familiarity with basic programming concepts or languages. Therefore, experience in Python or Machine Learning is NOT required but will help.

Q&A:
Why should you come to in-person training instead of online?
It allows you to learn from an experienced trainer directly and raise your questions right away also the trainer will be up to the questions on Github after the Bootcamp.
 
The seats are limited to 15 people only, sign up NOW

Testimonial:
“Stylianos brings great enthusiasm to his workshop – his interest in all things AI shines through.” - Tim Gordon, Chief Executive at the Liberal Democrats
"Stylianos’s bespoke workshop allows for in-depth complicated analytical concepts to be understood in a manageable and easy way. Coving the background of the constant changing world of data science and breaking down the key concepts of data science." - Dominik Byrne, Investor, Entrepreneur, Advisor
You can find more testimonials here. 

¹ Dr. Stylianos Kampakis is an expert data scientist (with a decade of experience), member of the Royal Statistical Society, an honorary research fellow at the UCL Centre for Blockchain Technologies and startup consultant living and working in London. A natural polymath, with degrees in Psychology, Artificial Intelligence, Statistics, Economics and a Ph D in Computer Science from University College London he loves using his broad skillset to solve difficult problems. You can learn more about his work at skampakis.com

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