Dear Data

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1. The flow of data science

   1. Introduction [markdown, markup]
   2. A hasty tour inside R [images, markdown, markup]
   3. dplyr: a grammar of data manipulation [images, markdown, markup]
   4. ggplot2: a grammar of data visualization [markdown, markup]
   5. Data Challenge: The Elo method in chess [markdown, markup]
   6. Modelling: find a good explanation for your data [markdown, markup]
   7. Demo – Life expectancy change over time [markdown, markup]
   8. Data Challenge – Life expectancy change over time for each continent [markdown, markup]
   9. Communication [markup]

2. Network Science

   • Basics
     1. Introduction [images, markdown, markup]
     2. Graph basics [images, markdown, markup]
     3. igraph: network analysis [markdown, markup]
     4. tidygraph and ggraph: tidy network analysis and visualization [markdown, markup]
   • Local analysis
     1. Centrality: usual suspects [markdown, markup]
     2. Centrality: recursive methods [graphs, markdown, markup]
     3. Data Challenge: A dolphin social network [markdown, markup]
     4. Power measures [markdown, markup]
     5. Data Challenge: Power and centrality in the European natural gas market [markdown, markup]
     6. Signed networks [markdown, markup]
     7. Similarity and heterogeneity [markdown, markup]
     8. Data Challenge: Interdisciplinarity and autarchy in science [markdown, markup]
   • Group analysis
     1. Community detection and clustering [markdown, markup]
     2. Data Challenge: Cluster Italian soccer teams in performance classes [markdown, markup]
     3. Data Challenge: Detect the most dangerous terrorists of Madrid train bombing [markdown, markup]
   • Global analysis
     1. Network models [markdown, markup]
     2. Connectivity and resilience [markdown, markup]
     3. Data Challenge: Attack the Madrid train bombing terror network [markdown, markup]
     4. Geodesic distances and small worlds [markdown, markup]
     5. Power laws and scale-free networks [markdown, markup]
     6. Assortativity [markdown, markup]
     7. Motifs [markdown, markup]
     8. Data Challenge: global analysis of a network [markdown, markup]
     9. Epidemics on networks [markdown, markup]

3. Text mining

   1. The tidy text format [markdown, markup]
   2. Sentiment analysis [markdown, markup]
   3. Analyzing word and document frequency [markdown, markup]
   4. Relationships between words: n-grams and correlations [markdown, markup]
   5. Converting to and from non-tidy formats [markdown, markup]
   6. Topic modeling [markdown, markup]
   7. Demo – Mining financial articles [markdown, markup]
   8. Demo – The great library heist [markdown, markup]
   9. Demo – Comparing Twitter archives [markdown, markup, data]