skip to content

 

 

Wednesday 3rd November 2021 to Wednesday 17th November 2021

Background

The Newton Gateway proposes to implement a number of short intensive training courses (2-3 days) in mathematical areas of relevance to individuals in industry, business and government. We envisage that these courses will provide technical training in the subject matter with the emphasis on practical applications of mathematics.

The first training focused on machine learning using Python programming language and took place over 3 days in a hybrid teaching format. The first day of the course, Wednesday 3rd November, took take place physically at the Isaac Newton Institute, followed by 2 virtual sessions on Wednesday 10thand Wednesday 17th November 2021.

Aims and Objectives

This course provided delegates with essential skills in implementing machine learning algorithms for clustering, classification and predictive analytics using Python programming language and its ecosystem of machine learning libraries including (but not limited to) statsmodels, scikit-learn, h2o and SciPy.
 
The course:

  • guided delegates through the requirements of each machine learning method in terms of data pre-processing, feature engineering, data extraction and transformation activities,
  • guided delegates through the process of machine learning application – from data input to model validation and interpretation,
  • introduced the characteristics, structures and applications of suitable clustering, classification and forecasting methods that can be applied to current and future research activities.

It included the following machine learning methods:

  • multiple linear and non-linear regressions for predicting numeric variables,
  • clustering methods, feature selection and customer segmentation: k-Means (different distance calculations and also special treatment of categorical data), Hierarchical Clustering,
  • classification algorithms: generalised linear models using logistic regression, Decision Trees, k-Nearest Neighbours and Naïve Bayes,
  • more advanced ML algorithms for classification and forecasting purposes e.g. Random Forests.

Delegates had practical experience in data processing, quantitative research and data analysis using Python programming language (e.g. pandas, NumPy) – gathered from either professional work or university education/research. Delegates benefited from some knowledge of inferential statistics and principles of data science on the course.
 
This event was of interest to participants from engineering, manufacturing, energy, chemical, finance and business management sectors.
 

Registration and Venue

Registration is now closed.

If you are interested in attending a future training course we are currently in the process of developing our second training course which will focus on Optimisation for Industry, more specifically, for Data Scientists/Machine Learning, and will take place over 3 days in a hybrid teaching format. We plan to hold this as a hybrid event. The first day of the course, Tuesday 3rd May, will take place physically at the Isaac Newton Institute, followed by 2 virtual sessions on Tuesday 10th and Tuesday 17th May 2022.

You can find more information and how to register your interest here.

The training was delivered in collaboration with Mind Project.

 
In collaboration with