General outline
Contents
General outline¶
Within this course we will explore basics of the intersection between neuroscience & artificial intelligence, specifically focusing on their respective fundamentals regarding theory, implementation and analyzes, as well as adjacent topics concerning Neuro-Data-Science. To do so, we will follow a “learning by doing” approach in a tripartite manner. Starting from a basic introduction (Block I), we will run actual experiments/analyzes (Block II) planned and conducted by you, as well as communicate/present the obtained results (Block III). Thus, we actively seek out realistic examples and workflows that mimic the lifecycle of real-world projects, trying to present you with both a respective overview and hands-on experience.
When and where do we meet?¶
As this won’t be a “classic” course that entails weekly lectures/assignments, etc. but instead utilizes a different outline that is oriented along the research process, we will have sessions with varying content (situated within three main blocks: introduction/background, project execution, project finalization) every now and then. Combined with a strong focus on project work and direct supervision, we will organize meetings as we go with all participants. Thus, please watch out for E-Mails/Discord notifications!
In the beginning we will meet in PEG 5.129 and check how well this works for us!
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Schedule¶
Please see below for our current optimistic schedule. Depending on our progress, potential problems and different forms of learning, content and times might change a bit. Each lecture will be divided into several parts separated by a 5-10 minute break and might constitute a transition from basic to advanced concepts, theoretic to practical sessions and individual to group work. The different parts are roughly indicated in the schedule below like this:
🗓 - important information on date & time
💡 - input from the instructor
👩🏽🏫👨🏻🏫 - instructor presents content
🥼 - research project work
🧑🏽💻🧑🏾💻 - work on demo data
🧑🏿🔬👩🏻🔬 - work on own research project
🖥️ - computational work outside course hours
✍🏽 - writing outside course hours
📖 - reading outside course hours
Please click on a given topic either within the table below or the ToC on the left to get to the respective materials.
Date (day/month/year) 🗓 |
Topics 💡👩🏽🏫👨🏻🏫 |
Project related work 🥼🧑🏿🔬👩🏻🔬 |
tasks for subsequent meeting 🖥️✍🏽📖 |
|---|---|---|---|
12/04/2022 |
General introduction - course information, overview & outline |
not applicable |
re-cap Python lectures, install software, start going through the Neuroscience intro materials |
20/04/2022 |
Neuroscience I - intro/Q&A/hands-on concerning neuroimaging methods 🧑🏽💻🧑🏾💻 |
start thinking about projects that might interest you and what neuroimaging method could be suitable for the respective ideas |
have all accounts and software ready, continue going through the Neuroscience intro materials |
27/04/2022 |
Neuroscience II - intro/Q&A/hands-on concerning neuroimaging methods 🧑🏽💻🧑🏾💻 |
start thinking about projects that might interest you and what neuroimaging method could be suitable for the respective ideas |
have all accounts and software ready, continue going through the Neuroscience intro materials |
03/05/2022 |
Neuro-Data-Science - data standardization, version control & project management 🧑🏽💻🧑🏾💻 |
continue to think about projects that might interest you and start your open lab notebook |
evaluate and check your setup concerning software, accounts and integrations, continue going through the Neuroscience intro materials & check Neuro-Data-Science aspects further |
10/05/2022 |
Linear algebra - equations, vectors, matrices & projections 🧑🏽💻🧑🏾💻 |
continue to think about projects that might interest you and continue your open lab notebook |
continue going through the Neuroscience intro materials, Neuro-Data-Science aspects & Linear algebra |
17/05/2022 |
Machine learning I - basics, core concepts & definitions 🧑🏽💻🧑🏾💻 |
||
24/05/2022 |
Machine learning II - “Shallow learning” 🧑🏽💻🧑🏾💻 |
||
tba |
Machine learning III - “Deep learning” 🧑🏽💻🧑🏾💻 |