Practical SQL for Research and Data Science

January 8th, 15th, 22nd, and 29th, 2027

Registration

Contact

courses@transmittingscience.com

Course Overview

The SQL language provides a standardised way to work with structured data across virtually every field, from scientific research to business reporting. Whether you’re querying millions of rows in a data warehouse or building reproducible analysis pipelines, SQL remains the go-to tool for reliable, high-performance data management. It is a key skill used not only in scientific analyses, but also data science, analytics, and engineering.

This course introduces participants to the core concepts and techniques of SQL through practical, hands-on exercises on realistic datasets. By the end of the course, participants will be able to:

write clear, efficient queries to retrieve, combine, and summarise data
work confidently with common database structures and workflows

This course includes a range of activities such as live-coding sessions, interactive quizzes, and practical exercises to work individually or in a group. Active participation and contribution are highly recommended.

Places are limited to 15 participants.

Programme

Databases and relational fundamentals + dataset

What a database is and why relational databases are used
The relational model: tables, keys, and relationships
Introduction to the course dataset

Getting started with SQL

Running queries in SQLite (core tooling and workflow)

Defining and managing tables (DDL)

Create, modify, and delete tables
Define columns and choose appropriate data types

Working with records (DML)

Insert, update, and delete records

Core querying

Retrieve data with SELECT
Compute new columns and expressions
Work with dates

Filtering and ordering

Filter rows and sort results
Deal with missing values

Summarising data

Aggregations (e.g., counts, sums, averages)
Grouping with GROUP BY

Combining data across tables

Join tables (inner, left/right outer, etc.) to merge information

Dates and categorisation

Handling dates in practice
Creating categories (e.g., using CASE)

Advanced querying patterns

Subqueries
Common Table Expressions (CTEs)
Window functions (time permitting)

Using SQL from R (optional, time permitting)

Calling SQL from R for reproducible workflows

Assumed Background

No prior knowledge of SQL is required.
Depending on time, we may also use SQL within R. No prior knowledge of R programming or RStudio is required.

Software

Participants should have their own computer. The course material, datasets, and instructions for the technical setup will be circulated before the course. Code and solutions to exercises will be circulated by the instructor after the course.

Dates & Schedule

Online live sessions on January 8th, 15th, 22nd, and 29th, 2027.

From 11:30 to 15:00 (Madrid time zone).

Total course hours: 22
14 hours of online live lessons, plus 8 hours of independent work on exercises.

This course is equivalent to 1 ECTS (European Credit Transfer System) at the Life Science Zurich Graduate School. The recognition of ECTS by other institutions depends on each university or school.

Format

In the live sessions we will combine online lectures with hands-on computational exercises.

Live sessions will be recorded. However, attendance to the live sessions is required to obtain the course certificate.

This course will be delivered in English.

Instructor

Dr. Nicolas Attalides
Freelance
UK

Registration Fees

Course Fee
Early bird (until September 30th, 2026):
516 €
(412.80 € for Ambassador Institutions)
Regular (after September 30th, 2026):
573 €
(458.40 € for Ambassador Institutions)
Prices include VAT.
After registration you will receive confirmation of your acceptance on the course.
Payment is not required during registration. Check discounts here.
How do I get the Ambassador Institution discount?
Registration