JUCo DSRG › Training Curriculum
JUCo DSRG · 2026/2027

Training Curriculum for Research and Data Science

A structured two-semester pathway designed to develop research foundations, computational skills, quantitative analysis, mathematical modelling, applied research, and scientific communication.

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Curriculum at a glance

A coherent research-development pathway

The curriculum connects research methods, data science, quantitative analysis, modelling, independent research, and communication.

18
Training modules
5
Progressive phases
2
Academic semesters
01
Independent research project
Learning pathway

Five stages of development

Each phase builds toward the next, culminating in supervised applied research and professional communication of research findings.

Foundations

Research concepts, ethics, data science, and introductory R.

Data Skills

Data collection, cleaning, exploration, and visualisation.

Modelling

Relationships, regression, mathematical models, and simulation.

Applied Research

Independent research conducted under academic supervision.

Communication

Writing, visualisation, presentations, and conference preparation.

Programme structure

Two semesters, one continuous research pathway

Semester I · Modules 01–13

Foundations, Data and Modelling

Focuses on research foundations, data management, exploratory analysis, statistical analysis, computational skills, and modelling.

Semester II · Modules 14–18

Applied Research and Communication

Focuses on independent applied research and communicating research findings through writing, visualisation, presentations, and conferences.

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18 modules

Curriculum overview

The JUCo DSRG training programme progresses from fundamental research concepts and data science skills to statistical analysis, mathematical modelling, independent research, and scientific communication.

Semester I

Research foundations, data management, exploratory analysis, statistical analysis, and modelling.

Semester II

Independent applied research and communication of findings through writing, visualisation, presentations, and conferences.

Phase I · Foundations

Foundations of Research and Data Science

Research foundations and introductory computational skills.

I
Module Title Competency Duration Semester Facilitators Open
01 Introduction to the Research Group Research Foundations 1 week I All Open
02 The Research Process Research Foundations 1 week I Dr. Mwonge · Dr. Fome Open
03 Introduction to Data Science Research Foundations 1 week I Dr. Leandry · Dr. Ongoro Open
04 Research Ethics and Data Responsibility Research Foundations 1 week I Dr. Mwonge · Dr. Fome Open
05 Introduction to R Computational Skills 2 weeks I Dr. Fome · Dr. Mwonge Open
Phase II · Data

Data Management and Exploratory Analysis

Data collection, preparation, exploration, and visualisation.

II
Module Title Competency Duration Semester Facilitators Open
06 Data Collection and Management Data Skills 1 week I Dr. Ongoro · Dr. Mwonge Open
07 Data Cleaning Data Skills 1 week I Dr. Fome Open
08 Exploratory Data Analysis Data Skills / Quantitative Analysis 2 weeks I Dr. Fome Open
09 Data Visualisation Data Skills / Computational Skills 2 weeks I Dr. Fome Open
Phase III · Modelling

Statistical Analysis and Modelling

Statistical relationships, mathematical models, and simulations.

III
Module Title Competency Duration Semester Facilitators Open
10 Models (Kinds / Types) Quantitative Analysis 1 week I Dr. Fome · Dr. Leandry Open
11 Correlation & Simple Regression Quantitative Analysis 2 weeks I Dr. Mwonge · Dr. Fome Open
12 Mathematical Modelling Quantitative Analysis 2 weeks I Dr. Leandry · Dr. Fome Open
13 Simulation and Scenario Analysis Mathematical & Simulation Modelling 2 weeks I Dr. Leandry · Dr. Fome Open
Phase IV · Applied Research

Independent Research Project

Independent research conducted under supervision.

IV
Module Activity Competency Semester Facilitators
14 Independent Research Project Participants select one of two research strands aligned with the group's research mission. Applied Research II All
Goal

Each participant designs and conducts an independent research project under supervision.

Research Strands

Participants select one of two research strands aligned with the group's research mission.

Supervision Format: One-hour individual supervision sessions every two weeks, plus monthly group meetings.
Phase V · Communication

Scientific Communication

Communicating research findings clearly and professionally.

V
Module Title Competency Duration Semester Facilitators Open
15 Scientific and Technical Writing Applied Research & Communication 1 week II Dr. Leandry · Dr. Mwonge Open
16 Research Visualisation for Communication Poster Design, etc. Applied Research & Communication 1 week II Dr. Fome Open
17 Oral Presentation Skills Applied Research & Communication 1 week II Dr. Leandry · Dr. Mwonge Open
18 Internal Conference Preparation Applied Research & Communication 1 week II Dr. Leandry · Dr. Fome Open
Learning outcomes

What the training pathway develops

The curriculum is structured to progressively develop practical research and quantitative skills.

01

Research Foundations

Understand research processes, ethics, data responsibility, and the role of quantitative methods.

02

Data Science Skills

Develop practical skills in data collection, cleaning, exploration, visualisation, and R.

03

Quantitative Analysis

Apply statistical relationships, regression, mathematical modelling, and simulation approaches.

04

Applied Research

Design and conduct an independent research project under structured academic supervision.

05

Scientific Communication

Communicate research findings through technical writing, visualisation, presentations, and conferences.

06

Research Development

Build an integrated foundation for continued academic, research, and quantitative career development.

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