CONTENT

1. Introduction [General Lecture Description
ENSE 3 Smart-* programs: [PDF] YouTube session-1 YouTube-session-2
EGI Industry 4.0 program Smart Analytics Course: [PDF] YouTube-session
a. Data-centric sciences: principles and common aspects
b. Digital data collections: characteristics and properties
c. Data science: big data, data analytics algorithms & tools

2. Designing experiments
[ENSE 3 Smart-* programs: [PDF] YouTube session-1 YouTube session-2
EGI Industry 4.0 program Smart Analytics Course: [PDF] YouTube session
a. Data Science Pipeline
b. Exploring and preparing data collections for building corpora

3. Data Analytics Methods

3.1 Descriptive statistics

a. Preparing data sets
b. Explanatory data analysis
c. Estimation

3.2 Statistical inferenceĀ 
a. The frequentist approach
b. Measuring the variability in estimates
c. Testing hypothesis

3.3 Unsupervised learning: clustering

3.4 Network Science: dealing with graphs [PDF]