INTRODUCTION TO CODING AND DATA MANAGEMENT-2

The goal of this course is to teach students how to cleanse, process and visualize data. In particular, the students will learn how to use a programming language to read and write data from standard formats, process it to extract useful information, and visualize and plot it in order to show and explain its content.

The course introduces basic tools in the field of data management through programming.
Programming is intended as a way to model real-world problems and to design algorithmic solutions to solve them.
This course teaches students problem solving techniques and algorithmic thinking.
Technical topics cover algorithms, data structures, and Python programming.

The students will achieve the following objectives:

Knowledge: i) learn how to use common libraries (e.g., NumPy and Pandas) and complex data structures to address specific problems; ii) understand common data visualizations techniques and how to use common library (Seaborn) objects to create data visualizations; iii) understand how to organize code into modules and classes.

Application of knowledge: i) use complex library structures to organize, cleanse and analyze data to solve formal algorithmic problems; ii) organize solution code into modules and classes.

Communication: i) generate various data visualizations for preliminary analysis and final presentation.

Understanding of content in Introduction to Coding and Data Management – I, and in particular the basics of Python programming and of complex data structures.

• Structuring the code with modules and classes
• Data representation (txt, csv, json, …)
• File read and write
• Data cleansing
• Basics of data processing, analysis and visualization with Panda (series, dataframes, operation, mapping, join) and NumPy (matrices, operations, statistical functions)
• Basics of data visualization (data dimensionality, graphs, charts, maps) with Seaborn and plotly

Python for Data Analysis. O'Reilly. Wes McKinney.

Instructor notes.

Evaluation is achieved through a written exam. The written exam assess the capability of the student to apply problem solving techniques to simple problems.
The exam consists in a set of multiple choice questions and programming exercises, where the student is asked to write a small program to solve a given simple problem.
After the written test, an optional oral exam follows (at the discretion of the professor).

oral

Regarding the grading of the grade:
A. scores in the 18-22 range will be awarded in the presence of:
- sufficient understanding of common data management and plotting libraries
- sufficient skills in the development of code using common libraries for data analysis
B. scores in the 23-26 range will be awarded in the presence of:
- fair or good understanding of common data management and plotting libraries
- fair or good skills in the development of code using common libraries for data analysis
C. scores in the 27-30 range will be awarded in the presence of:
- excellent understanding of common data management and plotting libraries
- excellent skills in the development of code using common libraries for data analysis

Lectures and hands-on sessions.

English