DASI. Data Arts and Science for Impact
Within the next ten years, it is expected that technology will have a significant impact in every economic sector and in society through automation and services customization. In the core of this transformation there are data and the construction of data-centered solutions.
Data Arts and Science for Impact (DASI) is a School of learning aimed at filling the gap within the job market in Data Science and educate a generation of complete and aware practitioners able to master the change.
The program is designed together with the major Italian experts and it is thought to be able to give a complete and unique education.
The course is composed by four streams:
- Fundamentals: to deliver adequate competencies on database principles, software Programming and Machine Learning in R and Python languages.
- System thinking: to understand the importance of model construction and use data in order to better comprehend the reality, sharing results and building data-centered solutions.
- Capstone Projects: To apply the Agile method on real business cases in two sprint weeks. Working on more than one case ensures a strong flexibility and inclination to the application.
- Creativity, Soft Skills and Well-being: To develop an approach oriented towards well-being and work life balance through innovative and modern techniques, in order to educate practitioners able to cope stress and resilient on work.
How it works
16 weeks in Blended mode: 45% lessons Face-to-Face at the Cottino Campus Social Impact + 55% Distance learning and individual study.
Graduates of all disciplines with a good logical-mathematical predisposition interested in working in the world of Data Science and in the construction of concrete solutions starting from data, in any context. The course is open both to STEM and non-STEM students through two different paths: the first is oriented to programming and coding, the second students will be able to use a non-coding Data Science platform. There will be a selection for accessing the course.
The demand within the job market for people able to comprehend, manage and develop data-centric solutions in order to solve real problems is constantly growing. Organizations request professional figures for positions that require non only a good academic knowledge, but also the ability to apply to real cases.
Aims and methods
The course aims to give a complete and unique education by ensuring, 16-week full-time blended, the development of structural hard skills, professional oriented towards the construction of data-centered solutions, and the development of necessary soft skills for personal and professional successes in this area. By the end of the course the participant will be able to follow and develop a Data Science project and find work as Data Scientist/Data Analyst/Data Engineer. The course mixes lectures from faculty, e-learning and peer learning self-study with constant tutoring, problem-based learning and challenge-based learning workshops starting from real cases.
Contents in a nutshell
- Introduction to statistics
- Learning to Learn & Self-study Enablement
- Introduction to R and Python
- Core database concepts
- Relational Database Support for Data Warehouses
- Data Warehouse Concepts, Design, and Data Integration
- Business Intelligence Concepts, Tools, and Applications
- Machine Learning concepts (structured, unstructured)
- Data Preparation in practice with Talend
- Machine Learning in practice with RapidMiner
- Distributed database systems
- NOSQL database systems
- Big Data Tools
- Data Management in the cloud
- Data Visualization with Tableau
- Marketing Analytics
- Learning Analytics
- Design Thinking
- Data Ethics
- Neuroscience and Learning
- Well Being Experiential Workshops
What Will I learn and what will I be able to do
- Developing and managing a Data Science project, form from beginning to end
- Entering in the job market as Data Scientist/Data Analyst/Data EngineerData Scientist/Data Analyst/Data Engineer.
Learning Journey With:
Raul De Maio
See the Impact Cherry:
DASI: Data Arts and Science for Impact