DS108
Introduction to Data Analysis
Faculty
Nikolay Taran
AI & Neuroscience specialist at St. Peter’s School Barcelona
Course length
Duration
Total hours
Credits
Language
Course type
Fee for single course
Fee for degree students
Skills you’ll learn
Overview
The aim of this course is to prepare students for data analysis in real-world scenarios they may encounter in their future careers. The course is project-based; student-led work plays a major role alongside traditional lessons.
The course begins with an introduction to research design, where students learn to recognise biases, hidden assumptions, and sources of noise before any analysis is performed. It then builds a foundation in data analysis, focusing on probability, statistics, and the processing of time-series data from sensors and real systems. Students learn essential techniques such as filtering, segmentation, frequency analysis, and Independent Component Analysis to separate meaningful signals from artefacts. Finally, the course provides a practical introduction to machine learning, demonstrating how clean, well-structured features can be used for classification and prediction.
All analytical work — including preprocessing, visualisation, statistical testing, and modelling — is carried out in Python.
Learning highlights
- Assess the reliability and validity of a dataset or research project
- Design a research project
- Design and conduct a data analysis pipeline
- Preprocess and analyse various types of data
- Explore and interpret multivariate relationships
- Build and evaluate simple machine learning models
Course outline
15 classes
Session 1
Introduction to Research Designs
Session 2
Validity, Reliability, Sampling
Session 3
Experimental Logic & Control
Session 4
Statistics I - Foundations
Session 5
Statistics II - Hypothesis Testing
Session 6
Time Series & Frequency Analysis
Session 7
Preprocessing Techniques
Session 8
Mid-term exam
Session 9
Independent Component Analysis I
Session 10
Independent Component Analysis II
Session 11
Multivariate-relationships
Session 12
Network analysis
Session 13
Machine Learning I
Session 14
Machine Learning II
Session 15
Project presentations
Prerequisites
Basic programming experience.
Intro to Higher Mathematics course.
Methodology
Each class combines a short lecture with a hands-on workshop, where students practise the methods in Python. Students also give brief in-class presentations and work on a small data project using their own dataset, which they present at the end of the three-week course.
Grading
Nikolay graduated as a psychologist with a mention in experimental psychology from the Universitat de Barcelona. He has conducted research in neuroscience as part of his Master’s Degree at the Hospital Clinic de Barcelona, as well as his PhD at the Technion Institute of Technology.
He has published multiple research papers in international journals in the area of the neuroscience of learning disabilities, and specifically the study of human neural networks involved in different cognitive domains.
See full profileApply for this course
Introduction to Data Analysis
by Nikolay Taran
Total hours
45 Hours
Dates
Feb 23 - Mar 13, 2026
Fee for single course
€1500
Fee for degree students
€750
How to secure your spot
Complete the form below to kickstart your application
Schedule your Harbour.Space interview
If successful, get ready to join us on campus
FAQ
Will I receive a certificate after completion?
Yes. Upon completion of the course, you will receive a certificate signed by the director of the program your course belonged to.
Do I need a visa?
This depends on your case. Please check with the Spanish or Thai consulate in your country of residence about visa requirements. We will do our part to provide you with the necessary documents, such as the Certificate of Enrollment.
Can I get a discount?
Yes. The easiest way to enroll in a course at a discounted price is to register for multiple courses. Registering for multiple courses will reduce the cost per individual course. Please ask the Admissions Office for more information about the other kinds of discounts we offer and what you can do to receive one.