(N = # assignments, M = #class participation exercises)
| Week # | Assignment # | Description | Optional Reading | Due Date | Points |
1 |
1/N*EC% | ||||
1 |
Wk1_Reading 1 | COGS108 - python and jupyter tutorials, data science tools | |||
1 |
Wk1_Reading 2 | Neural data science tutorials (github - original 138 page) | |||
2 |
Week 2 Lecture 3 survey/quiz | Fill in what you wrote in class- no research online pre-lecture survey/quiz - required as part of participation points but not graded on correctness, do your best and do not research answers, you can leave answers blank if needed or fill in something like "unsure" or "do not know" |
Wed, 4/12 | 1/M*20% | |
2 |
Wk2_Reading 3 | MNE tutorial - at minimum introduction, installation pages | |||
2 |
Wk2_Reading 4 | NLTK overview, installation, choose several examples | |||
2 |
Assignment 0 (on datahub) | Getting your system working with datahub | Fri, 4/15 | 1/N*EC% | |
2 |
Paper - assigned R1 | R1-Ezer and Whitaker - 2019 - Data science for the scientific life cycle | Fri, 4/21 | ||
3 |
|||||
3 |
Assignment 1 (on datahub) | Tues, 4/25 at 11:59pm | 8% | ||
| 3 | Reading quiz 1 | Fri 4/28 at 11:59pm | 5% | ||
| 4 | Reading 2 Assigned | R2-Paninski_and_Cunningham_2018_Neural_data science_accelerating_the_experiment | Fri 5/5 at 11:59pm | ||
| 4 | Assignment 2 (on datahub) | LISC | Tue 5/9 at 11:59pm (extended) |
8% | |
| 4 | Quiz Week1-2- lecture quiz (canvas) | A short quiz on the lecture materials for the first two weeks. | Tue 5/9 at 11:59pm (extended) | 1/M*20% | |
| 5 | Reading quiz 2 | Due to the timing of putting up the quiz and that there are other assignments to complete we will provide a week to complete it, so please complete by next monday. | Tue 5/9 at 11:59pm (extended) |
5% | |
| 6 | Lecture 11 Survey/quiz (before) | Questions you answered before the lecture about classical statistics | Friday 5/12 at 11:59pm | 1/M*20% | |
| 7 | Lecture 11 Survey/quiz (after) | Questions you answered after the lecture at home about classical statistics | Friday 5/12 at 11:59pm | 1/M*20% | |
| 7 | Assignment 3 (on datahub) | Correlations | 8% | ||
| 7 | Quiz week 3 lectures (canvas) | A short quiz on the lecture materials for the third week | Tuesday 5/23 at 11:59pm | 1/M*20% | |
| 7 | Mid-quarter check-in | Required, a check-in to go along with the grade check-in to see how things are going, and for some feedback. Part of class participation credit. Won't take more than a few minutes | Tuesday 5/23 at 11:59pm | 1/M*20% | |
| 7 | Reading 3 | Variability in the analysis of a single neuroimaging dataset by many teams |
Thursday 5/25 at 11:59pm | 5% | |
| 7 | Mid-quarter grade check-in | Required, a check-in to ensure that you have turned in all you need to and things are progressing smoothly. | Tuesday 5/23 at 11:59pm | 1/M*20% | |
| 8 | Wk8_Reading1-examples Wk8_Reading1.2-documentation |
Documentation for PySurfer - go through, download and complete the examples from basic visualization and any interesting in between examples, and defnitely go through how to save images, present views of the brain, and possibly display animations, also recommended you go through the detailed documentation link, which is actually fairly short. | Saturday 5/27 |
-- | |
| 8 | Wk8_Reading2 | NiBabel documentation installation and getting started sections, and any sections you see in the A4 assignment. | Saturday 5/27 | -- | |
| 8 | Previous project review | Please review the prior quarter projects as we went over in class. Review the two projects your group selects as individuals then come together as a group and coordinate. Each group submits one. | Tuesday 5/23 at 11:59pm | TBA | |
| 8 | Project proposal | We are going to start with a project proposal where you will describe your project idea, hypothesis, proposed data, and answer some other questions so we can give you feedback and guide you to a successful outcome | TBA | ||
| 8 | Class Report | Answering questions/workshop to enhance student learning outcome |
Sunday 6/4 at 11:59pm |
TBA | |
| 9 | Data checkpoint | Saturday 6/3 at 11:59pm | TBA | ||
| 9 | |||||
| 10 | EDA checkpoint | TBA | |||
| 10 | Reading quiz 4 (canvas) | The Virtuous Cycle of a Data Ecosystem, by Brad Voytek PhD | Sunday 6/11 at 11:59pm | 5% | |
| 10 | |||||
| 10 | |||||
| FINALS | Final project due |
This will be the final report, data, etc all due to the github repository (includes the video or a link to the video) |
Extended to Friday 6/16 at 11:59pm |
TBA | |
| FINALS |
TUTORIAL HERE |
Mouse v. human cells, allensdk TUTORIAL HERE |
Saturday 6/17 at 11:59pm | 8% | |
| FINALS | Lecture quiz week 4-5 (canvas) | 2 required, 1 extra credit (choose any of the 3 as extra credit) | Sunday 6/18 at 11:59pm | TBA 1/M*20% | |
| FINALS | Lecture quiz week 6-7, (canvas) | 2 required, 1 extra credit (choose any of the 3 as extra credit) | Sunday 6/18 at 11:59pm | TBA 1/M*20% | |
| FINALS | Lecture quizzes week 8-10 (canvas) | 2 required, 1 extra credit (choose any of the 3 as extra credit) | Sunday 6/18 at 11:59pm | TBA 1/M*20% | |
| FINALS |
login/password listed in final module and in announcement |
Each video presentation you review and fill out the form completely gets you an additional 0.5% bonus to your grade. If over 90% of the class completes at least ONE video review fully, I'll add a 1% bonus to the overall grade for everyone! | Sunday 6/18 at 11:59pm | 0.5% bonus per review, 1% overall bonus if over 90% of students do at least 1 | |
| FINALS | (Optional) Group feedback form | This is an opportunity to provide feedback for your group members. If some people did not contribute or everybody contributed. Since it is the timing it is and you had many deadlines this week this is optional, but we will take it into account during grading | Sunday 6/18 at 11:59pm |