CH3CO1: Python, AI and Machine Learning for the Chemical Sciences

Module code: CH3CO1

Module provider: Chemistry; School of Chemistry, Food and Pharmacy

Credits: 20

Level: 6

When you’ll be taught: Semester 1

Module convenor: Dr Mauricio Cafiero , email: m.cafiero@reading.ac.uk

Module co-convenor: Dr James Hallett, email: j.e.hallett@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2025/6

Available to visiting students: Yes

Talis reading list: Yes

Last updated: 24 April 2025

Overview

Module aims and purpose

The aim of this module is to provide students with modern tools to organize, analyse and process data using the python programming language and various AI and machine learning tools.

Module learning outcomes

By the end of the module, it is expected that students will be able to:

1. Parse, sort and analyse data using python code they have developed;
2. Integrate physical and life science python libraries into their own code;
3. Use AI and machine learning tools to analyse data predictively and interpretively.

Module content

Basics of Python: working with numbers, strings, operations, reading and writing to files, Jupyter notebooks.

Python libraries: biopython, matplotlib, numpy, pandas, Psi4, and others.

Machine learning with Python: introduction to main concepts and algorithms (regression metrics, hyperparameters, training approaches, regularisation, random forests, support vector machines, deep neural networks); using LLMs for chemistry

Structure

Teaching and learning methods

• 8 lecture hours AI and Machine learning
• 13 workshop/practical hours machine learning
• 6 lecture hours python
• 12 workshop/practical hours python

Study hours

At least 40 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 40% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Level 3 (i.e. foundation modules for Part 0) and Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Reassessment

Additional costs