Data analyses in Python
Contents
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 |