Smart Career Planning and Skill Development via Personal Analytics
Abstract
The project aims to develop a personal analytics platform for career planning and development. Each person at early stages of her or his career need to make a decision about in which skills to invest time or money in order to be successfull in the future and have an interested and well-paid profession. The platform would help an individual to make a decision which courses to take, which soft skills to develop, how to choose a university program, when and where to look for a new job. The data for analytics can be gathered from social networks, e.g., LinkedIn profile of an individual, open data sources to projects number of future jobs in each profession, from university web-sites, from MOOC web-portals, job search web-sites, etc.
The project goal is to develop a web-portal that aggregates user-specific information via LinkedIn API and based on other open data makes personalized recommendations about career choices. By the end of the summer school we would try to form a team for a startup company to develop the project further and create a self-contained prototype. The ultimate goal is to turn this project into the startup.
Project prerequisites :
- Linear algebra, matrix computations
- Introduction to business analytics (basic statistics, machine learning, simulation, optimization)
- Programming language: Python (numerical computations in Python, LinkedIn and Facebook Python API)
- Basics of web-development (front-end to the portal via one of existing CMS, back-end of the portal in Python)
- Enterpreneural skills and marketing skills
- Web-platform for testing and experimentation: https://datascientistworkbench.com
About lecturer:
Dr. Oleksandr Romanko,
Ph.D., Senior Research Analyst at IBM Canada and Adjunct Professor at University of Toronto.