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CHEM10240

Academic Year 2026/2027

Coding for the Molecular Sciences (CHEM10240)

Subject:
Chemistry
College:
Science
School:
Chemistry
Level:
1 (Introductory)
Credits:
5
Module Coordinator:
Dr Nadia Elghobashi-Meinhardt
Trimester:
Spring
Mode of Delivery:
Blended
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

This module introduces Python coding as a practical tool for the molecular sciences. Students learn to write and adapt code in the context of chemical and biomolecular problems, including processing experimental data, visualising molecular structures, and modelling simple chemical systems. Programming is presented as a scientific tool that extends what researchers can interpret and communicate. Practical work is carried out in interactive Jupyter notebooks accessible through a web browser.

The module is organised into four thematic blocks:
1) Python fundamentals
Introduction to core programming concepts through examples drawn from the molecular sciences, including variables, data types, loops, conditionals, and functions, allowing students to write simple scripts to automate routine calculations and process data.

2) Scientific data visualisation
Creating clear figures from chemical and biomolecular datasets. Topics include importing data from files, choosing appropriate visualisation methods, and producing high-quality plots for the presentation and interpretation of experimental data.

3) Data handling
Methods for organising, cleaning, and analysing experimental datasets. Students are introduced to statistics, regression, and curve fitting using datasets drawn from chemical and biomolecular science, such as spectroscopy, titrations, kinetics, and thermodynamic measurements.

4) Statistical analysis, and numerical methods with applications in molecular science.
Introduction to numerical approaches used in molecular science, including solving equations numerically, computing derivatives, and integrals from data. Applications include modelling of reaction kinetics and simple simulations of molecules.

The module assumes no prior programming experience and is designed to provide an accessible introduction for students in molecular sciences (chemistry, biology).

About this Module

Learning Outcomes:

On successful completion of this module, students will be able to:

- Write simple Python programs to automate calculations and process scientific data
- Apply core programming concepts to solve problems in molecular sciences
- Import, organise, analyse, and visualise experimental datasets
- Apply and interpret statistical methods, including regression and curve fitting, to chemical and biomolecular data
- Use numerical methods to solve equations and compute derivatives and integrals from data
- Model and simulate simple chemical systems, including reaction kinetics

The United Nations identified seventeen Sustainable Development Goals (SDGs) as core to the 2030 Agenda for Sustainable Development, and UCD contributes in general to SDG 4 Quality Education. Further SDGs explored within this module if relevant are listed below. A scale of 1 - 5 indicates the extent to which the SDG is covered.


 

Student Effort Hours:
Student Effort Type Hours
Lectures

24
Specified Learning Activities

36
Autonomous Student Learning

40
Total

100

Approaches to Teaching and Learning:
Weekly lectures introduce core programming concepts and numerical methods through live coding demonstrations and interactive examples. Students apply these approaches to problems in chemistry and the molecular sciences using Jupyter notebooks in regular exercises completed independently at home. The results are discussed and reviewed in class, and students are encouraged to collaborate with peers. Additionally, each student will produce a project-based notebook over the course of the trimester.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Not applicable to this module.
 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Quizzes/Short Exercises: Four short, in-class quizzes in Brightspace will be given. The best three of four quizzes will be counted toward the final grade. Week 3, Week 5, Week 8, Week 11 Graded No
30
 No
Individual Project: Each student will be required to submit one Jupyter notebook-based project that demonstrates practical coding skills. Week 10 Pass/Fail Grade Scale No
20
 No
Exam (In-person): Final exam will be given at the end of the trimester to assess material learned throughout weeks 1-12. End of trimester
Duration:
2 hr(s)
 Graded No
50
 No

As part of UCD's student support, under the Additional Consideration policy, extensions may be available for the following assessments in the module: Assignment (including essay/poster), Portfolio, Reflective Assignment, Report(s), and Individual Project.


Carry forward of passed components
Yes
 

Resit In Terminal Exam
Summer Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
• Online automated feedback
• Peer review activities

How will my Feedback be Delivered?

Not yet recorded.

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Spring Lecture Offering 1 Week(s) - 20, 21, 23, 24, 25, 26, 29, 30, 32, 33 Mon 14:00 - 15:50
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