Instructors
Nikhil [email protected]
Pierre-Etienne [email protected]
This crash course is aimed at absolute beginners in scientific programming in general and in python in particular. It is intended for entering doctoral students in neuroscience and psychology.
The goal of this class is to enable students to successfully partake in more advanced classes (like Math Tools) and to give a practical introduction to data science.
The bootcamp is organized in 10 sessions (morning: 10-12, afternoon: 1:30-3:30) that will run August 26th-30st in Meyer 760. Sessions build on each other and use neuroscience-based examples and data.
Course Learning Objectives
- Draw useful conclusions from data using computation
- Use a scientific programming environment fluently
- Translate, ask and answer basic neuroscience / psychology questions in this environment
Installation Instructions
- anaconda, choose python 3.7
- we will be using jupyterlab (installed with anaconda)
Day 1: Welcome!
- Introduction, installation, and using python as a scientific calculator
- Numpy, vectorization, and randomness through simulation.
Day 2: What can a population of IT neurons encode?
- Matrix indexing, computing simple statistics, data aggregation and plotting
- Data Analysis 1: Single neuron tuning and correlation analysis of neural populations
Day 3: How are categories represented in MT/LIP?
- More advanced use of indexing, plotting, and functions
- Data Analysis 2: Quantifying cateogry tuning in a neural population
Day 4: What are the statistics that describe V1 populations?
- Using programming as a simulation tool
- Data Analysis 3: Understanding correlations in spike trains
Day 5: Putting it all together
- Relatively Advanced Topic 1 (per request)
- Relatively Advanced Topic 2 (per request)