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Foundations of Machine Learning in Python

NeurotechEU

Course designed for advanced learners interested in understanding the foundations of Machine Learning in Python.

General: The course consists of 15 lectures (ca. 1-2 hours each) and 15 exercise sheets (for ca. 6 hours of programming each).

Institution: High-Performance Computing and Analytics Lab, University of Bonn

 

Introduction to Neurodata Without Borders (NWB) for Python Users II

NWB Core Development Team

The Neurodata Without Borders: Neurophysiology project (NWB:N, https://www.nwb.org/) is an effort to standardize the description and storage of neurophysiology data and metadata. NWB enables data sharing and reuse and reduces the energy barrier to applying data analytics both within and across labs. Several laboratories, including the Allen Institute for Brain Science, have wholeheartedly adopted NWB.

 
INCF TrainingSpace

Preprocessing Data in EEGLAB

Swartz Center for Computational Neuroscience

EEGLAB is an interactive MATLAB toolbox for processing continuous and event-related EEG, MEG, and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data.

 

FAIR Approaches for Neuroimaging Research

INCF

Over the last three decades, neuroimaging research has seen large strides in the scale, diversity, and complexity of studies, the open availability of data and methodological resources, the quality of instrumentation and multimodal studies, and the number of researchers and consortia. The awareness of rigor and reproducibility has increased with the advent of funding mandates, and with the work done by national and international brain initiatives.

 

INCF Assembly 2022 - Day 1 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 day 1. 

VIEW THE PROGRAM

 
INCF TrainingSpace

INCF Assembly 2023 - Lightning Talks (Day 2)

INCF

This course consists of several lightning talks from the second day of INCF's Neuroinformatics Assembly 2023. Covering a wide range of topics, these brief talks provide snapshots of various neuroinformatic efforts such as brain-computer interface standards, dealing with multimodal animal MRI datasets, distributed data management, and several more. 

 

Reproducible Science (Including Git, Docker, and Binder)

Krembil Centre for Neuroinformatics

This course consists of two workshops which focus on the need for reproducibility in science, particularly under the umbrella roadmap of FAIR scienctific principles. The tutorials also provide an introduction to some of the most commonly used open-source scientific tools, including Git, GitHub, Google Colab, Binder, Docker, and the programming languages Python and R. 

 

FAIR Approaches for Neuroimaging Research

INCF

Over the last three decades, neuroimaging research has seen large strides in the scale, diversity, and complexity of studies, the open availability of data and methodological resources, the quality of instrumentation and multimodal studies, and the number of researchers and consortia. The awareness of rigor and reproducibility has increased with the advent of funding mandates, and with the work done by national and international brain initiatives.

 
INCF TrainingSpace

Session 5: Infrastructure for Sensitive Data

INCF

This course consists of a three-part session from the second day of INCF's Neuroinformatics Assembly 2023. The lessons describe various on-going efforts within the fields of neuroinformatics and clinical neuroscience to adjust to the increasingly vast volumes of brain data being collected and stored.

 

INCF Assembly 2022 - Training Day 2

INCF

This course contains sessions from the second day of INCF's Neuroinformatics Assembly 2022.

 

INCF Assembly 2022 - Day 1 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 day 1. 

VIEW THE PROGRAM

 
INCF TrainingSpace

Session 8: FAIR Data: The Role of Journals

INCF

Most neuroscience journals request authors to make their data publicly available in appropriate repositories. The requirements and policies put forward by journals vary, and the services provided for different types of data also differ considerably across repositories.

 

INCF Assembly 2022 - Day 3 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 Day 3. 

VIEW THE PROGRAM

 
INCF TrainingSpace

Session 5: Infrastructure for Sensitive Data

INCF

This course consists of a three-part session from the second day of INCF's Neuroinformatics Assembly 2023. The lessons describe various on-going efforts within the fields of neuroinformatics and clinical neuroscience to adjust to the increasingly vast volumes of brain data being collected and stored.

 
INCF TrainingSpace

INCF Assembly 2023 - Lightning Talks (Day 1)

INCF

This course consists of three lessons, each corresponding to a lightning talk given at the first day of INCF's Neuroinformatics Assembly 2023. By following along these brief talks, you will hear about topics such as open source tools for computer vision, tools for the integration of various MRI dataset formats, as well as international data governance. 

 

Introduction to Neurodata Without Borders (NWB) for MATLAB Users I

NWB Core Development Team

The Neurodata Without Borders: Neurophysiology project (NWB, https://www.nwb.org/) is an effort to standardize the description and storage of neurophysiology data and metadata. NWB enables data sharing and reuse and reduces the energy-barrier to applying data analytics both within and across labs. Several laboratories, including the Allen Institute for Brain Science, have wholeheartedly adopted NWB.

 

Module 3: Computational Models

Mike X. Cohen

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and F-I curves. The MATLAB code introduces live scripts and functions.

 

Publishing

This course is currently under construction but will coming soon.  It will give an overview of the world of scientific publishing, spanning from traditional formats, to open to access, to open, interactive, reproducible, and 'living' publications with modifiable and executable code.

 

Programming

A number of programming languages are ubiquitous in modern neuroscience and are key to the competence, freedom, and creativity necessary in neuroscience research. This course offers lectures on the fundamentals of data science and specific neuroinformatic tools used in the investigation of brain data. Attendees of this course will be learn about the programming languages Python, R, and MATLAB, as well as their associated packages and software environments. 

 

INCF Short Course: Introduction to Neuroinformatics

INCF

The emergence of data-intensive science creates a demand for neuroscience educators worldwide to deliver better neuroinformatics education and training in order to raise a generation of modern neuroscientists with FAIR capabilities, awareness of the value of standards and best practices, knowledge in dealing with big datasets, and the ability to integrate knowledge over multiple scales and methods.