Data analyses in Python#
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
Date (day/month/year) 🗓 |
Topic 💡 👨🏻🏫 |
Assignment & deadline 🖥️ ✍🏽📖 |
|---|---|---|
20/01/2022 |
Data analyses I - data handling 💡 👨🏻🏫 🧑🏽💻🧑🏾💻 🧑🏿🔬👩🏻🔬 |
26/01/2022 - 11:59 PM EST 🖥️ ✍🏽📖 |
27/01/2022 |
Data analyses II - statistics 💡 👨🏻🏫 🧑🏽💻🧑🏾💻 🧑🏿🔬👩🏻🔬 |
02/01/2022 - 11:59 PM EST 🖥️ ✍🏽📖 |
03/01/2022 |
Data analyses III - visualization 💡 👨🏻🏫 🧑🏽💻🧑🏾💻 🧑🏿🔬👩🏻🔬 |
09/02/2022 - 11:59 PM EST 🖥️ ✍🏽📖 |
10/02/2022 |
Project discussion, Q&A 💡 👨🏻🏫 🧑🏽💻🧑🏾💻 |
not applicable |