School of Scientific Computing & Informatics · Scientific programming
Databases & SQL for Life-Science Data
Sample registers, experiment records and omics metadata outgrow spreadsheets quickly. This course teaches you to design databases for scientific data and to query them confidently with SQL.
Course overview
Databases & SQL for Life-Science Data covers relational thinking (entities, keys and relationships), the SQL needed to filter, join and aggregate, and the constraints that keep data correct as a project grows.
You model a laboratory sample-tracking system, query public biological databases, and use DuckDB to analyse large tables directly from Parquet and CSV files without loading them into memory.
Learning outcomes
By the end of the course you will be able to:
- Model scientific data as related tables with keys and constraints
- Write SQL queries with joins, grouping and window functions
- Use PostgreSQL, SQLite and DuckDB appropriately
- Query large files and public databases efficiently
- Protect data integrity with constraints, transactions and backups
Skills you will practise
Eligibility and prerequisites
Who can apply
- Students and graduates in any science, engineering, pharmacy, medicine, agriculture, geography or computing programme (B.Sc., B.Tech., B.E., BCA, M.Sc., M.Tech., MCA, PhD)
- Researchers, faculty and working professionals in research, healthcare, biotech, pharma or IT who want to apply computing to science
- Final-year students may apply before their results are declared
Prerequisites
- None; comfort with spreadsheets
Best suited to
- Researchers managing samples and experimental metadata
- Bioinformaticians who query annotation databases
- Students preparing for data roles in biotech
Module-wise syllabus
6 modules. Each pairs instructor-led sessions with a hands-on lab on public data.
Topics
- Tables, keys and relationships
- Normalisation
- Spreadsheet pitfalls
Topics
- SELECT, WHERE and ORDER BY
- Joins
- Grouping and aggregates
Topics
- Window functions
- Common table expressions
- Indexes and query plans
Topics
- DuckDB and columnar files
- Parquet
- SQL from Python and R
Topics
- Constraints and transactions
- Users and permissions
- Backups and audit trails
Topics
- Schema
- Queries
- Documentation
Practical sessions and projects
Capstone project
Build a laboratory database
Model, implement and document a database for a real laboratory workflow, with the queries your colleagues will need.
Assessed on the correctness of the analysis, the quality of the code and the reasoning in the write-up. A pass is required for the certificate.
- Relational thinking
Redesign a spreadsheet of samples and assays as a relational schema.
- Querying with SQL
Answer research questions from a sample and assay database with SQL.
- Advanced SQL
Rank samples within batches and speed up a slow query with an index.
- Analytics at scale
Query a multi-gigabyte variant table directly from Parquet with DuckDB.
- Integrity and operations
Add constraints, roles and an audit table to the sample-tracking database.
- Project: a lab database
Design, build and document a database for a real laboratory workflow.
Software, tools and datasets
Software and tools
All software is free and open source or free for academic use. Recommended computer: 8 GB RAM, 30 GB free disk, Linux, macOS or Windows with WSL2.
Datasets
- Ensembl and UCSC public MySQL/SQL dumps: Querying annotation databases.Ensembl / UCSC Genome Browser
- Simulated laboratory records: Schema design and queries.Course data
Core reading
- Beaulieu A. Learning SQL, 3rd edition. O’Reilly, 2020.
- Raasveldt M, Mühleisen H (2019). DuckDB: an embeddable analytical database. SIGMOD ’19.
Duration, format and fees
- Next cohort
- Dates are sent with your admission offer
- Timetable
- Three evening or weekend sessions a week (IST), plus a lab clinic; intensive and weekend-only schedules on request
- Payment
- Secure online payment link with your admission offer (UPI, cards, net banking). Instalments on request for fees above ₹15,000.
- Refunds
- See the refund and cancellation policy.
Instructor
The instructor for each cohort is named in your admission offer and on this page when the cohort is announced. Vedicgen instructors are selected for hands-on research or industry experience in the subject they teach, and every course is reviewed by a second subject expert.
Questions about who teaches a cohort? [email protected]
Certificate
Learners who complete the course and pass its capstone receive a Vedicgen certificate of completion for Databases & SQL for Life-Science Data, issued by Vivofold, stating the guided hours and skills assessed. Each certificate has a unique ID and QR code that anyone can check.
Apply for Databases & SQL for Life-Science Data
Apply
Send the form below. It takes about five minutes.
Review
An adviser confirms your fit and format within two working days.
Offer
You receive dates, timetable and a secure payment link.
Onboard
Set-up guide, pre-reading and joining links.
Frequently asked questions
In the live cohort, modules are taught in instructor-led sessions with a weekly lab clinic where you work on real public data with help at hand; every session is recorded. The self-paced format uses the same lessons, labs and datasets with mentor review of your capstone. Both formats end with an assessed project reviewed for the code and the science.
A laptop with at least 8 GB of RAM and about 30 GB of free disk space, running Linux, macOS, or Windows with WSL2. Installation instructions are sent before the first session, and lab clinics help with any set-up problems.
Yes. Learners who complete the course and pass its assessment receive a Vedicgen certificate of completion, issued by Vivofold. Every certificate carries a unique ID and a QR code that anyone, including an employer or admissions office, can check on the certificate verification page.
Apply with the form on this page. Live and in-person cohorts run through the year; the dates, timetable and joining details of the next cohort are sent with your admission offer and listed on this page once announced. Self-paced enrolment opens as soon as your application is accepted.
Yes. No course runs longer than four weeks, and the length is customisable: choose the standard schedule, an intensive one- to two-week schedule, weekends only, or a custom timetable. Pick your preference on the application form; colleges and teams can book their own dates.
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