Data Science for Urban Mobility
Exercises & Assignments:
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:
- Final document we got by the end of the session:
- 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
Sellele ülesandele ei saa hetkel lahendusi esitada.
- 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
- Assignment 2:
- Assignment 2 - pdf
- Dataset Link
- Data NYC Taxi Zones
- Dataset Documentation
- Deadline: Latest 2021.05.03 Tuesday 23:59:00.000 EEST
Sellele ülesandele ei saa hetkel lahendusi esitada.
- 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 Visualization using GeoPandas: