Administrative information

Introduction to what a data is
- Why Data is important (1 min)
- Data, Information, Knowledge (1 min)
- A possible definition for Data (1 min)
- Quantitative vs Qualitative Data (1 min)
- Quantitative vs Qualitative Analysis (1 min)
The stage of Data Analysis
- The Data Analysis process (5 min)
- Defining the question (2 min)
- Collecting and Extracting the Data (2 min)
- Cleaning and Transforming the Data (2 min)
- Analyzing the Data (2 min)
- Share the results (2 min)
Recent Trends in Data Mining
- Data Mining and Common Uses (1 min)
- Data Mining & Machine Learning (1 min)
- Data & Patterns (1 min)
- Data Mining techniques (1min)
- Data Mining Recent Applications (1 min)
- CRISP-DM (CRoss Industry Standard Process for Data Mining) methodology (1 min)
CRISP-DM (CRoss Industry Standard Process for Data Mining) methodology
- Introduction (2 min)
- Business Understanding (1 min)
- Data Understanding (1 min)
- Data Preparation (1 min)
- Modeling (1 min)
- Evaluation (1 min)
- Deployment (1 min)
- Is CRISP-DM Agile or Waterfall? (2 min)
The IEEE 70xx standard
- IEEE Standard Model Process for Addressing Ethical
- Concerns during System Design (10 min)

Expected time schedule and concepts organization
Duration (min)	Description	Concepts	Activity
5	Introduction to what data is	Data, Information, Knowledge, Quantitative vs Qualitative Data, Quantitative vs Qualitative Analysis	Lecture
15	The stages of data analysis (e.g., extraction, exploration, visualization)	Multi-stage Data Analysis process, Collection, Extraction, Exploration, Cleaning, Analysis, Visualization, Sharing Results	Lecture
5	Recent trends in data mining	Data Mining modern applications	Lecture
10	CRISP-DM (Cross Industry Standard Process for Data Mining) methodology	CRISP-DM phases, Business Understanding, Data Understanding, Modeling, Evaluation, Deployment	Lecture
10	The IEEE 70xx standard	Ethical Issues, System Design	Lecture

Keywords