Machine Learning For Developers and Analysts- Predictive Analysis
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.
“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
Intro to Python and Pandas.
Instructions on how to build a crawler in Python for the purpose of getting stats.
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
09:30 – 10:00 Registration
10:00 – 12:30 Masterclass
12:30 - 14:00 Lunch
14:00 – 17:30 Masterclass
17:30 – 18:00 Drinks and Networking
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.
The developer and software engineer: 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.
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.