Data Science for Urban Mobility

Notes:

Exercises will be available weekly during the practical sessions, and they are for learning and practicing the knowledge acquired during the lectures.
We will have two graded assignments.

Week 1, Tutorial 1: Introduction to Python and Initiation to Data Science
- Screencast record
- Initial document we started with:
  - Lab notebook in zip and pdf
- Final document we got by the end of the session:
  - Lab notebook in zip and pdf
Week 2, Tutorial 2: Databases, Data Preparation, and Preprocessing
- Screencast record
- Lab notebook in zip and pdf
  - Please make sure you worked out the material!
  - For the next lab, we except everyone has the database functional!
Week 3, Tutorial 3: Spatial Data
- Screencast record
- Lab notebook in zip and pdf
  - Please make sure you worked out the material!
  - For the next lab, we except you are familiar with Pandas and Matplotlib!
Week 4, Tutorial 4: Bayesian Inference
- Screencast record
- Lab notebook in zip
- Extra materials on data pre-processing and plotting (shown in the lab) zip

Assignment 1:
- Assignment 1 - pdf
- Assignment 1 - notebook
- Data
  - Deadline: 2021.04.13 Wednesday 14:00:00.000 EEST

Solutions for this task can not be submitted at the moment.

Week 5, Tutorial 5: Machine Learning
- Screencast record
- Lab notebook in zip
- Extra materials on plotting and CRS conversion (started in the lab) zip
Week 6, Holiday
Week 7, Tutorial 6: Spatial Data Analysis
- Screencast record
- Lab notebook in zip

Solutions for this task can not be submitted at the moment.

Week 8, Tutorial 7: Data Visualization and Recap session (Questions and Answers)
- Data Visualization using GeoPandas:
  - Simple example using shape-files
  - Example of multiple layers on the same plot
  - Lab initial notebook in zip
  - Screencast record
  - Lab final notebook in zip
  - Spatial data additional examples in zip
  - Line intersection example in zip
  - Nearest shape example in zip

Data Science for Urban Mobility 2021/22 spring