Linear and Non-Linear Regression Models with Python - 1-day tutor-led online course
|Mind Project Ltd|
Simon Walkowiak MSc, MBPsS
86-90 Paul Street
View in Google Maps (EC2A 4NE)
1. Course description.
During this 1-day tutor-led online training course you will learn to use Python programming language and its libraries to implement, optimise and evaluate multivariate linear and non-linear regression type models. More specifically, the course will explain the following concepts:
Different types of linear and non-linear regressions presented during this course will be implemented in Python programming language either through custom-made code or with functions and methods available in NumPy, pandas, SciPy, Scikit-Learn, Statsmodels, pyGAM and h2o libraries for Python.
2. Course programme.
This is a 1-day instructor-led online training course with a week-long follow up period. The course will run from 10:00 in the morning to ~15:30 and will include a 45-minute break for lunch between morning and afternoon sessions. Following the course, you will be able to submit your solutions to the homework exercise and you will receive feedback from the tutor.
This training course is tutor-led – all online tutorials are presented live by our expert instructor, you can ask questions, discuss the topic and interact with other learners. You can also email the tutor after the course if you have any questions related to the material presented during the course.
The course will be recorded - you will have access to the video recording of the course and additional resources such as datasets, Python code, academic papers related to the topic of the workshop, and supplementary exercises via Mind Project Learning Platform.
Course dates: Friday, 3rd of December 2021, 10:00-15:30 London (UK) time
Deadline for registrations: Wednesday, 1st of December 2021 @ 17:00 London (UK) time
10:00 - Course welcome and logistics
10:15 - Introduction to linear and non-linear regression models (theory and examples)
11:00 - Multivariate linear regression in practice - Python tutorial
12:00 - Regularised regressions (Ridge, Lasso and Elastic Net) - Python tutorial
12:30 - 13:15 - lunch break
13:15 - Multivariate non-linear regressions and Generalised Additive Models (i.e. polynomial and spline) in practice - Python tutorial
15:15 - 15:30 - discussion and course wrap-up
3. Course pre-requisites and further instructions
4. Your course instructor.
Your instructor for this course will be Simon Walkowiak. Simon is a director at Mind Project Limited and a Ph.D. researcher in Artificial Intelligence at the Bartlett Centre for Advanced Spatial Analysis (University College London) and the Alan Turing Institute in London. Simon holds BSc (First Class Honours) in Psychology with Neuroscience and MSc (Distinction) in Big Data Science. He conducts and manages research projects on implementation and computational optimisation of novel AI approaches applicable to large-scale datasets to predict human behaviour and spatial cognition. Simon is the author of “Big Data Analytics with R” (2016) – a widely used textbook on high-performance computing with R language and its compatibility with the ecosystem of Big Data tools e.g. SQL/NoSQL databases, Spark, Hadoop etc. Apart from research and data management consultancy, during the past several years, Simon has taught at more than 150 in-house or open-to-public statistical training courses in the UK, Europe, Asia and USA. His major clients include organisations from finance and banking (HSBC, RBS, GE Capital, European Central Bank, Credit Suisse etc.), research and academia (GSMA, CERN, UK Data Archive, Agri-Food Biosciences Institute, Newcastle University etc.), health (NHS), and government (Home Office, Ministry of Justice, Government Actuary’s Department etc.).
Should you have any questions please contact Mind Project Ltd at email@example.com or by phone on 0203 322 3786. Please visit the course website at https://www.mindproject.io/product/linear-and-nonlinear-regression-models-python-dec21/.
Intermediate (some prior knowledge)
£120 per person for the whole course (regular fee) or £75 per person - applicable to undergraduate and postgraduate students, representatives of registered charitable organisations and NHS employees only (discounted fee). Additional discounts available for multiple bookings and groups.
Website and registration
Regression Methods, Ordinary least squares (OLS), Generalized liner model (GLM), Generalized least squares (GLS), Linear regression, Heteroskedasticity, Regression discontinuity , Data Mining, Machine learning, Python
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