Pythontz Machine Learning Summer School (PytzMLS2018)

About PytzMLSS2018

The three days PytzMLSS2018 summer school will bring together masters, PhD students, researchers and industry practitioners who have interests in machine learning and AI with aim to equip them with necessary cutting-edge and hands-on machine learning and AI skills. The school will provide an introduction to the themes and methods of the field through tutorial and hands-on labs activities. The tutorial will cover the foundations of machine learning and deep learning, unsupervised machine learning, and the application of these techniques in health, natural language processing, computer vision, and time-series analysis. The emphasis of the tutorial will be on helping participants to understand the underlying motivation of the state of the arts machine learning and AI techniques and how and why they work. The lab activities will equip participants on how to apply these techniques to a real world problems in their research and/or in the business career. Lab activities will be based on hands-on training in code development and testing, with application to real data-sets.

Target Audience

In principle, graduate students, doctoral students and researchers in the fields of machine learning and related fields will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees. Computer scientists who have interests in machine learning and AI and Industry practitioners who desire a more in depth understanding of these subjects are also encouraged to participate.

Requirements and Prerequisites

No deep previous knowledge of ML is required, but the attendants are assumed to have at least some basic background on linear algebra, probabilities and programming in python. A review on basic concepts python programming and an introduction to the necessary tools for implementation of machine learning algorithms using python will be given on 3rd April 2018 from 1500 to 1800hrs. There is no registration fee for students, non-students participants will pay a registration fees of Tsh 60,000.