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Introduction to machine learning and deep learning in Python, online

Monday, 27 January 2025 to Tuesday, 28 January 2025, 10am - 1pm

Apply for this course

This course is a practical introduction to applying machine learning and deep learning algorithms on biological data using the Python programming language. Using a mixture of lectures and hands-on training, the participants will be taken through different steps of data processing, preparation and application of the machine learning techniques to solve various problems, with guidance from expert tutors. By the end of the course, the participants should be able to apply machine learning and deep learning techniques to tabular and image data.

You are required to attend 2 sessions:
  • Monday 27 January, 10:00 - 13:00
  • Tuesday 28 January, 10:00 - 13:00

COURSE FORMAT

Day 1

Theory: Introduction to machine learning, Types of problems that can be resolved with machine learning, Overview of machine learning algorithms

Hands-on: application of machine learning in Python using sklearn library to the publicly available medical dataset (solving classification problem)

Theory: Feature selection algorithms

Hands-on: application of feature selection and machine learning in Python using sklearn library to the publicly available biological dataset (solving regression problem)

Day 2

Theory: Introduction to image analysis with deep learning, Use cases, Image pre-processing

Hands-on: Pre-processing images in Python using Numpy and OpenCV libraries

Theory: Convolutional neural networks (CNNs) using Pytorch

Hands-on: Application of CNNs on an image classification problem (e.g. blood cell type classification)

Hands-on: Model evaluation, Using pre-trained models

COURSE OBJECTIVES

By the end of this course, you will learn:

How to pre-process your data for machine learning and deep learning analysis

How to apply machine learning techniques to address biological questions using example datasets

How to apply deep learning on an example image dataset

How to evaluate and visualise analysis results

what you will need

Basic knowledge and experience of coding in Python including following libraries: scipy, numpy, matplotlib, pandas

Each 3-hour session would consist of a mix of teaching and hands-on training, with a feedback from the tutors and Q&A at the end. You are expected to interact with the instructors and other course participants during the sessions for problem-solving and assignments. The code and worksheets for this course will become available at the first session and can be accessed anytime during and after the course.

Participants are required to have the following software installed on their computers before the course:

List of the Python SciPy libraries required for this tutorial: scipy, numpy, matplotlib, pandas, sklearn, Opencv, Pytorch,

Basic Python courses are available through the Oxford IT Learning Centre (for a registration fee):

Python

Pandas and Numpy 

Any installation questions could be addressed to courses@medsci.ox.ac.uk

Hardware requirements:

It is highly recommended to have access to a microphone and ideally a second screen during the sessions.

PARTICIPANT NUMBERS

25

ATTENDANCE CERTIFICATE ON SURVEY COMPLETION

In order to receive a certificate of attendance, participation in all three sessions is mandatory. Once you have completed the course, you will be sent an email with a link to the overall course feedback survey. When you have filled in and submitted the survey, you will be sent an email with a link to your attendance certificate. Survey results are downloaded and stored anonymously.

feedback from previous sessions

The whole part is really nice, very practical and suitable for beginners
I really liked all the cool graphs and images we generated, that helped me develop an intuitive understanding of what working in ML and DL would be like.
The teaching we received was great! I really appreciated the background information slides

Booking Instructions

Step-by-step guidelines on how to book a Skills Training course.

How to book

Terms & Conditions

These terms and conditions apply to all MSD Skills training courses attendees.

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