EXPONENTIAL CODING WITH AI AND DATA MANAGEMENT
Stampa
Enrollment year
2020/2021
Academic year
2020/2021
Regulations
DM270
Academic discipline
SECS-S/01 (STATISTICS)
Department
DEPARTMENT OF ECONOMICS AND MANAGEMENT
Course
INTERNATIONAL BUSINESS AND ENTREPRENEURSHIP
Curriculum
Digital Management
Year of study
Period
1st semester (28/09/2020 - 22/12/2020)
ECTS
9
Lesson hours
66 lesson hours
Language
English
Activity type
WRITTEN AND ORAL TEST
Teacher
BARTOSIAK MARCIN LUKASZ (titolare) - 3 ECTS
LA VOLPE ALESSANDRO - 6 ECTS
Prerequisites
Basic computer skills.
Learning outcomes
The course is designed to be practically theoretical. We will cover enough theory to develop a frame of reference on which to build practical skills. In parallel, through exercises and projects, we will internalize theoretical concepts and reinforce our theoretical understanding.

Upon successful completion of this course, you will be able to:
- understand the main concepts of AI
- understand how AI can exponentially accelerate businesses
- use IBM’s Watson Assistant in real-life scenarios
- code in Python and apply your knowledge to Data Science problems
- understand the impact of Data Management on contemporary businesses
- recognize various database models and write simple queries
Course contents
The course will be split into three thematic sections:

Artificial Intelligence and Watson Assistant
- Artificial Intelligence: from daily life through Enterprise vision (with Watson Assistant)
- Knowledge Management (with Knowledge Studio)
- Data Science
- Machine Learning & Open Scale
- Computer Vision
- Visual Recognition
- Design Thinking

Python Lab
- Introduction to Python
- Conditional Statements & Functions
- Iterations & Strings Operations
- Collections
- Library import & External data sources

Data Management
- Data Management & Business Strategy
- Data Management Systems
- Database Design
- Querying databases
Teaching methods
Flipped class
Lectures
In-class practical exercises
Case study discussion

(Depending on the development of the COVID-19 epidemy and the sanitary norms, this can change. Part of the course or all the lessons may be delivered online.
In any event, class materials and recordings will be delivered online, permitting students in remote locations to follow the course).
Reccomended or required readings
- T. Markiewicz & J. Zheng, 2018, Getting Started with Artificial Intelligence, O'Reilly.
- Ch. Severance, 2016, Python for Everybody.

(Both e-books will be given to you at the beginning of the semester).
Assessment methods
- Team project
- Individual written test
Further information
Sustainable development goals - Agenda 2030