€439.34 – €728.09

Machine Learning Bootcamp on Python- Predictive Analysis (For Developer, BI...

Event Information

Share this event

Date and Time







View Map

Refund Policy

Refund Policy

Refunds up to 30 days before event

Event description



“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.

Machine Learning For Developers and Analysts- Predictive Analysis

Instructed by Dr. Stylianos Kampakis

The purpose of this course is to teach about 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 such as social media

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: Predictive analysis

Agenda :

  • 09:00 – 10:30 Registration

  • 10:30 – 12:30 Masterclass

  • 12:30 - 14:00 Lunch

  • 14:00 – 17:30 Masterclass

  • 17:30 – 18:00 Questions Time

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?

  • Companies which are trying to utilize prediction analysis and prediction model on their products and marketing/sales funnels.

  • Analyst: Companies who would like to offer re-education to their analytics team to their data science team or just upgrade yourself from analyst to data scientist.

  • Developer, who wants to know more about the algorithm or even think about switching to be the data scientist

  • Business Intelligence (BI): You are already familiar with statistics, want to understand better machine learning and prediction

Prerequisites and Target Audience?

What will participants need to know or do before starting this course?

This course is ideal for the analyst, junior data scientist, and BI also developer. A bit of knowledge of Python or machine learning will help you but it is not required. Have some familiarity with basic programming concepts or languages or statistics. Therefore, experience in Python or Machine Learning is not required but will help.

If you are not sure about your level, write us.

What does the price reflect?

The price reflects two things. First, it distills 7+ years of experience in a few hours, providing only the most relevant pieces for decision-makers, without all the jargon and the buzzwords. Secondly, it reflects the consultancy service which participants will get out of the workshop, and which is usually charged at much higher rates.

What are the problem-solving sessions about?

During the problem-solving sessions, we will solve on the blackboard any kind of problem the audience poses. In a previous workshop, for example, one of the problems was "How can we use Twitter data to predict Bitcoin prices?". The solution included the full pipeline (from data collection to data storage), to actually solving the problem and hiring the right people. Feel free to contact me with your problems before the workshop date.

The seats are limited to 12 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 skampakis.com.

Share with friends

Date and Time






View Map

Refund Policy

Refunds up to 30 days before event

Save This Event

Event Saved