Best Data Science Summer & Winter Schools

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Darya Petrashka, data scientist, share her tips on data science training for women in tech.

Data Science has emerged as a transformative field, and its demand continues to soar across industries.

To stay ahead in this dynamic landscape, aspiring data scientists seek immersive learning experiences, and what better way to do so than through specialized summer and winter schools? These programs offer intensive training, networking opportunities, and exposure to real-world applications of data science. In this article, we’ll explore some of the best data science summer and winter schools with open registration that provide invaluable experiences for individuals eager to delve into the world of data science.

Northern Lights Deep Learning School & Conference (NLDL)

Date: 8-12 January 2024

Location: Tromsø, Norway


This 5-day course is built upon tutorials on specific topics on deep learning from perspectives such as Synthetic data, Generative Models, and Explainability. The course further encompasses among others keynote talks as well as special sessions on industry and diversity in AI as part of the NLDL conference program. 

In particular, the winter school will provide a study of several emerging topics of high relevance within advanced deep learning, from a basic understanding of the techniques to the latest state-of-the-art developments in the field. Synthetic data generation for addressing common problems of data scarcity, privacy-preserving data sharing, and bias through case studies, reliability of AI, and generative models will be treated in depth in the form of tutorials, as will high-performance computing. Additional directions within deep learning, complementing those already mentioned, will be covered at the introductory level via a series of keynote talks. In addition, the participants will be exposed to the latest advances and applications in deep learning through oral presentations and poster presentations in the main conference program.

The course will thus consist of 5 full days of the NLDL conference including tutorials, keynote sessions, oral presentations, and poster presentations, as well as practical components.

Fee: Registration fee for winter school and conference together will be 1250 NOK (approximately 100 Euro) for students, 2000 NOK for other academic participants, and 3000 NOK for industry participants.

Registration fee for the conference will be 1000 NOK (approximately 80 Euro) for students, 1750 NOK for other academic participants, and 2750 NOK for industry participants.

Program: https://www.nldl.org/program/winter-school

Registration: https://www.nldl.org/attend/registration 

Deadline: Registration will be closed on 1 January 2024

Oxford Machine Learning Summer School (OxML)

Date: MLx Representation Learning (6–9 July 2024);
MLx Health & Bio (11–14 July 2024)

Location: Oxford, UK


Building on 4 successful years of previous programs, the 2024 initiative will delve into some of the most vital and emerging themes in ML and DL, areas of significant interest within the research community. These encompass statistical and probabilistic ML, representation learning, reinforcement learning, causal inference, computer vision, natural language processing (NLP), geometrical DL, and more.

The 2024 program comprises several specialized schools, each aimed at providing participants with in-depth knowledge and skills. These schools include MLx Fundamentals, MLx Representation Learning, and MLx Health & Bio.

MLx Fundamentals course is offered as an independent course with both theoretical and practical sessions. All OxML participants are encouraged to attend the MLx Fundamentals course to gain a stronger grasp of the advanced topics covered in the July courses. To secure your spot visit: www.oxfordml.school/event-details/mlx-fundamentals 

Fee: Standard (e.g., academics & working professionals): £300 (virtual) and £950 (in-person), full-time students: £150 (virtual) and £550 (in-person).

Program: MLx Representation Learning, MLx Health & Bio

Application: https://docs.google.com/forms/d/e/1FAIpQLSd5a69QQ4_bCfosoZGsasVyX-PkXsGzifAD8fwL2yaUk_342A/viewform

Deadline: Application will be closed on 7 February 2024

11th International School on Deep Learning and the Future of Artificial Intelligence (DeepLearn 2024)

Date: July 15-19, 2024

Location: Porto – Maia, Portugal


DeepLearn 2024 will be a research training event with a global scope aimed at updating participants on the most recent advances in the critical and fast-developing area of deep learning. 

Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, health informatics, recommender systems, etc.

The field is also raising several relevant questions about the robustness of the algorithms, explainability, transparency, and important ethical concerns at the frontier of current knowledge that deserve careful multidisciplinary discussion.

Most deep learning subareas will be displayed, and the main challenges identified through 18 four-hour and a-half courses, 2 keynote lectures, 1 round table, and a few hackathon-type competitions among students, will tackle the most active and promising topics. Renowned academics and industry pioneers will lecture and share their views with the audience. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face-to-face interaction and networking will be the main ingredients of the event. It will be also possible to participate in vivo remotely.

Fee: varies depending on the registration time from 340 € for early registration to 580 € for onsite registration

Program: https://deeplearn.irdta.eu/2024/wp-content/uploads/sites/8/2023/09/call-DeepLearn-2024.pdf 

Registration: https://deeplearn.irdta.eu/2024/registration/ 

Deadline: no specific deadline, the registration can be done onsite as well

Participating in a data science summer or winter school is an excellent way for aspiring data scientists to gain practical skills, network with industry professionals, and stay abreast of the latest developments in the field. Each of the mentioned programs offers a unique blend of academic excellence, hands-on experience, and exposure to real-world applications, making them standout choices for anyone eager to embark on a rewarding journey in data science. As the demand for skilled data scientists continues to rise, these schools provide invaluable opportunities to equip oneself with the necessary tools for success in this ever-evolving field.

About Darya:

Darya Petrashka, data scientist

AWS Community Builder, works as a Data Scientist at SLB. She is passionate about data and its usage for problem-solving. The area of interest includes classical ML and NLP, as well as working with AWS services.

An eternal student, she likes taking part in online schools, courses, and workshops. She shares insights on her Linkedin page and medium blog.


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