Machine Learning Bootcamp For Developers and Analysts- Predictive Analysis on Python

499 399


Machine Learning  Bootcamp For Developers and Analysts – Predictive Analysis on Python

October 18th, 2018 at Factory Görlitzer Park, Berlin

Instructed by Dr. Stylianos Kampakis

The purpose of this course is to teach how to use Python and machine learning in order to predict sports outcomes. It takes you through all the steps, from collecting data using a web crawler to making profitable bets based on your predicted results.

  • Intro to Python and Pandas.
  • Instructions on how to build a crawler in Python for the purpose of getting stats.
  • Data wrangling.
  • Using machine learning for predictions.

What am I going to get from this course?

1) Design and code a machine learning pipeline in Python for predicting outcomes.

2) Build and use a web crawler in Python to extract the data from online sources.

3) Understand all the concepts and pitfalls of prediction analysis


Module 1: Introduction
Module 2: Python and Pandas primer
Module 3: Data crawling
Module 4: Model testing and metrics
Module 5: Data analysis

Agenda :

  • 09:00 – 10:00 Registration
  • 10:00 – 12:30 Masterclass
  • 12:30 – 14:00 Lunch
  • 14:00 – 17:30 Masterclass
  • 17:30 – 18:00 Sponsor Talks


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 attend?

  • 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.

The seats are limited to 15 people.

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 PhD 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

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