Low Resourced languages pose an interesting challenge for Machine Learning algorithms, representation, data collection and accessibility of machine learning in general. In this tutorial, we work to provide a journey through machine learning in low resourced languages that covers a breadth of sub topics and depth in some of the areas of focus. We will do this through the lens of Natural Language processing for African languages. We present some historical context, recent advances and current opportunities that researchers can take advantage of to do impactful research in this area. We hope for this tutorial to not only shed light on the subject area, but to expand the number of practitioners who interact in a thoughtful and considerate way with the wider ML community working in these areas. We hope this to be as interactive as possible and to provide resources for researchers to tackle the challenges.