Code of Conduct
As all Brainhacks, BrainHack Marseille is
dedicated to providing a harassment-free Brainhack experience for everyone,
regardless of gender, gender identity and expression, sexual orientation, disability, physical appearance,
body size, race, age or religion.
We do not tolerate harassment of event participants in any form.
Sexual language and imagery is not appropriate for any event venue, including talks.
Event participants violating these rules may be sanctioned or expelled from the event.
Register
Registration is open now ...
Deadline is 25th November...
Note that there is a limitation of 80 people on site.
Please register only if you are sure about your presence, as we do not want to waste food.
Lunch and social event are not guaranteed for late registrations.
To register to the event, please click on the button below to fill the form.
Program
Program
- Python for beginners
- Version control using Datalad + BIDS
- ViT (Vision Transformers) - a library combining transformers for image processing
- Edge AI - for an overview of advances in AI and a few demonstrations
- Introduction to Arduino
Wednesday 27th November
09h00-09h45 | Welcome to BrainHack Marseille 2024
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09h45-13h00 | Training session:
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13h00-14h00 | Lunch Break | 14h00-16h30 | Training Session
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16h30-16h55 | Coffee Break | |
16h55-18h10 |
Training Session
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18h10-18h30 | Short projects presentations |
18h30 | BHM social event with a collective intelligence game! | (location: INT, 5th floor) |
Thursday 28th November
09h00-13h00 | Project Work
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13h00-14h00 | Lunch Break |
14h00-18h00 | Project Work
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18h00-19h00 | Round table Discussion
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Friday 29th November
09h00-13h00 | Project Work
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13h00-14h00 | Lunch Break | 14h00-18h00 | Project Work
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Projects
Here you can find all the informations about the event projects.
If you want to submit a project you should follow the link, fill the form, and open a github issue.
Projects can be anything you'd like to work on during the event with other people (coding, discussing a
procedure with coworkers, brainstorming about a new idea), as long as you're ready to minimally organize
this!
WISE: Workflow Improvement by Shifting to python in scientific Endeavors
by Alexandre Lainé & Cyprien Dautrevaux
Have you ever wanted, but lacked the time, to learn Python programming to update your data analyses and perhaps enhance them with new tools? In this era where open science is increasingly promoted, we are offering you the opportunity, over the course of two days, to delve into Python and its free tools. The idea behind this project is primarily collaborative; we aim to share our programming expertise to support you in what can sometimes be a long and challenging learning process. The objective is simple: by the end of these two days, we hope to provide you with a better understanding of Python’s role and value, help you begin transitioning some of your scripts and analysis methods, and offer suggestions to improve your workflows. For this project, no prerequisites or prior documentation are required. We will provide you with an interface and a ready-to-use environment so you can start programming, even from scratch. We look forward to seeing you motivated and eager to join this project. If you have any datasets you'd like to work on, feel free to bring them along, and we’ll be here to guide you. Get ready for coding!
Goals for the BrainHack:Getting use to Python and overall OpenScience, understand the different roles and interests of
Python programming in scientific studies, be proud of your own code.
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A suitable and functioning Python environment (code environment, coding interface …)
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Know where to find informations, and solve code issues
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Know the good practices
https://mattermost.brainhack.org/brainhack/channels/bhg2024_wise-project
What will participants learn?Learn to use the Python language in the broad outlines, to be able to perform your own analyses and scripts (Statistics, Data exploration, Preprocessing, Automation, Machine learning, Regression …)
Data to useFeel free to bring your own datasets, and suggest your own analysis interest.
Number of collaboratorsmore
Credit to collaboratorsAll contributors are listed on the project's README.md file.
Typecoding_methods, pipeline_development
Development status0_concept_no_content
Topicother
ToolsJupyter, other
Programming languagePython
Modalitiesother
Git skills0_no_git_skills
Required skills
This is a project for beginners. No prior knowledge is required.:Team
David Meunier
Research Engineer
Dipankar Bachar
Research Engineer
Matthieu Gilson
Junior Professor
Manuel Mercier
Research Associate
Laurie Mifsud
PhD student
Christelle Zielinski
Data Analysis Engineer
Hugo Dary
Research Engineer
Marie Bourzeix
PhD student
Shailesh Appukuttan
Postdoc
Giorgio Marinato
Postdoc
Cyprien Dautrevaux
PhD student
Alexandre Lainé
PhD student