HANDS-ON

The following hands on exercises are modified version of the ones proposed in L. Igual and S. Seguí, Introduction to Data Science: A Python approach to concepts, techniques and applications, Undergraduate topics in Computer Science Series, Springer, 2017

If you are willing to use your own computer three possibilities are available

1. A self contained environment using Docker. Follow two steps (requires advanced technical skills):

  1. Prepare your execution environment, see instructions here
  2. Test your environment, see instructions here

2. Using a self contained Data Science environment Follow two steps (requires medium technical skills):

  1. Download Anaconda according to the characteristics of your machine and OS.
  2. Install Anaconda following the instructions according to your OS (Windows, MacOS).

3. Online nothing to install (basic technical skills, recommended):

  1. Create a temporal account on https://notebooks.azure.com
  2. Ready to work 🙂

Understanding data collections content: a quantitative vision

  1. First steps into data analytics [Let us be Holmes and find the murderer]

Some of the following hands on will be done in Python. So here a memento of the language [PDF]

  1. Getting started with the data science ecosystem [HO-1]
  2. Exploring data collections using descriptive statistics [HO-2]

Prediction using artificial intelligence techniques

  1. Unsupervised learning light version [HO-3]
  • Comparing clustering algorithms long version [HO-4]

2. Supervised learning

3. Statistical inference

4. Network Analysis