Government expenditure can enhance the level of employment (if spent wisely) while reducing unemployment in both developed and developing countries. In this session, using Linear regression, we investigate the relation between government expenditure and unemployment rates among African countries. We compare this relation to that of European countries as well. Having such insight can inform further exploration and guide decision making on government spending.
In this session,Think Africa in collaboration with KampalR introduce simple linear regression in R and Python and the fundamental theory behind it. Linear models can be used for prediction or to assess whether there is a linear relationship between numerical variables.
Course materials are made available on Github
Data science, machine learning and artificial intelligence skills have become essential in many industries. Since there is a large interest in obtaining practical skills in these fields, Think Africa Ry and KampalR user group, both non-profit organizations have teamed up to offer means to obtain these skills. They will co-host and lead practical training sessions in essential data science skills in R and Python.
Initially, the trainings will collaboratively be held in Helsinki and Kampala, with plans to expand to more cities and countries. The collaborative training serves two purposes:
Attendance to the trainings is currently free. If you would like however to contribute to the sustainability and expansion of these trainings, your donation is warmly welcome through here.
We will have four trainings in 2018 held collaboratively in Finland and Uganda. In 2018, the trainings will cover: Linear regression (in March), Data extraction, exploration and visualization (~June), Supervised and unsupervised classification (~August), and Neural networks (~October).