Data Science Africa 2019

Accra, Ghana (21st - 25th October, 2019)

The last few years have witnessed an explosion in the quantity and variety of data available in Africa, produced either as a by-product of digital services, from sensors or measuring devices, satellites and from many other sources. A number of practical fields have been transformed by the ability to collect large volumes of data: for example, bioinformatics with the development of high throughput sequencing technology capable of measuring gene expression in cells, or agriculture with the widespread availability of high quality remote sensing data. For other data sources – such as mobile phone usage records from telecoms operators, which can be used to measure population movement and economic activity – we are just beginning to understand the practical possibilities.

Data science seeks to exploit advances in machine learning and statistics to make sense of the growing amounts of data available from various sources. In Africa, a number of problems in areas such as healthcare, agriculture, disaster response and wildlife conservation would benefit greatly if domain experts were exposed to data science techniques. These skills would allow practitioners to extract useful information from these abundant sources of raw data

DSA 2019 Addis tentative speakers and instructors include:

  • Neil Lawrence, Amazon UK and University of Sheffield
  • John Quinn, Google AI and Makerere University
  • Moustapha Cisse, Google AI
  • Ernest Mwebaze, Google AI, Ghana and Makerere University
  • Dina Machuve - Nelson Mandela African Institute of Science and Technology
  • Billy Okal, Voyage
  • Elaine Nsoesie, Boston University
  • Martin Mubangizi, Pulse Lab Kampala
  • Charles I. Saidu, AUST/Baze University, Abuja
  • Ayorkor Korsah, Ashesi University, Ghana
  • Yannis KalantidisFacebook AI
  • Ricardo Andrade, UCSF Institute for Global Health Sciences
  • Damon Civin, Facebook
  • Karl Fezer, arm
  • Summer School on Machine Learning and Data Science
    Dates: 21 October - 23 October 2019
    Venue: Ashesi University, Ghana
     

    In the tradition of previous Africa Data Science workshops, a summer school on machine learning and data science will be held prior to the main workshop. This summer school will target graduate students, researchers and professionals working with huge amounts of data or unique datasets.

    The summer school will focus on introductory and advanced lectures in data science and machine learning as well as moderate to advanced practical and tutorial sessions where participants will get their hands wet wrangling and munging datasets and applying cutting edge machine learning techniques to derive inference from the data. Lectures will be given by distinguished world renown researchers and practitioners including researchers from Sheffield University, Amazon, Swansea University Medical School, Facebook, Pulse Lab Kampala, the AI and Data Science (AIR) lab-Makerere University, ARM and Dedan Kimathi University of Technology (DeKUT).

    The school will also involve end-to-end tutorial sessions from professionals walking the participants through a real data analytics problem from data acquisition to data presentation.

    Draft Lecture Schedule

    Stuff to install..

    To ensure we hit the ground running, it is essential you install the prerequiste software and test it out and make sure it is working on your computer. The venue for the summer school will have some computers on which the software will have been installed but you are advised to come with your own laptop with the software installed.

    Anaconda

    Luckily all the software required has already been prepackaged in a bundle called Anaconda. You can download the various versions of the software for your laptop OS and architecture from the Anaconda website. Please download the Python 3.6 version. Instructions on how to install are next to the download links on the Anaconda website.

    Stuff to do..

    To ensure that the software is working fine on your machine and to get you up and running, download the following jupyter notebook (right click and ‘save as’) and do the exercises in there. To access it you’ll need to run a jupyter notebook (instructions).

    Troubleshooting and comments..

    Use the comment section below to (a) ask questions that are not already answered (b) help your peers by providing answers to their questions, if you can.

    Summer School Day 1

    The first day of the data science school will introduce the jupyter notebook and overview the use of python for analyzing data. We will introduce the machine learning technique of classification and perform lab practicals exploring these techniques as well as introduce the fundamentals of IoT.

    Time

    Activity

    Material

    08:00-08:30

    Arrival and Registration

    08:30-09:00

    Opening Remarks

    09:00-10:00

    Introduction to Machine Learning
    Prof. Neil Lawrence

    10:00-10:30

    Tea Break

    10:30-11:30

    Python, Pandas and Jupyter Tutorial - with Practical Session
    Gezehagn Gutema, Emmanuel Adeiza

    ipynb

    11:30-12:30

    Data Visualisation with Practical Session
    Prof. Elaine, Mourine Amoturine

    ipynb

    12:30-13:30

    Lunch

    13:30-15:30

    Fundamentals of IoT - with Practical Session
    Prof.Engineer Bano, Dr. Ciira

    15:30-16:00

    Tea Break

    16:00-17:30

    ML at the edge
    Karl Fezer (arm)

    slides

    17:30-19:00

    Labs

    Summer School Day 2

    The second day will feature two tracks dealing deep learning methods, mechanism design techniques and DisARM Project

    Time

    Activity

    Material

    09:00-10:30

    Introduction to Deep Learning - with Practical Session on Computer Vision
    Moustapha, Ernest & John

    ipynb

    10:30-11:00

    Tea Break

    11:00-12:00

    Image Representation and fine-grained recognition - with practical session
    Yannis

    12:00-13:00

    Lunch Break

    13:00-14:00

    Mechanism Design
    Eric Sodomka

    14:00-15:30

    Natural Language Processing
    Dennis Owusu, Michael Melese, David Sasu

    slides

    15:30-16:00

    Tea Break

    16:00-17:00

    Cyber Security
    Allan Ogwang

    17:00-18:30

    Labs

    Summer School Day 3

    Time

    Activity

    Material

    09:00-10:30

    Introduction to Gaussian Processes
    Charles I. Saidu

    10:30-11:00

    Tea Break

    11:00-12:30

    Introduction to Reinforcement Learning
    Dr. Ayorkor

    11:00-12:00

    Lunch Break

    12:00-13:30

    Data for good presentation
    Facebook Team

    13:30-14:30

    Electrical grid mapping tutorial
    Damon Civin, Kadeem Khan

    14:30-15:00

    Tea Break

    15:00-16:30

    Research Clinic (Q&A for researchers), Feedback

    Data Science in Africa Workshop
    Dates: 24 October - 25 October 2019
    Venue: Ashesi University, Ghana

    Theme

    End to End Data Science

    Call for Registration

    The workshop will be organized around paper presentations and interactive panel discussions. We invite participants interested in presenting work at the workshop to submit a short abstract describing the application of data science methods to problems relevant to Africa. These may include, for example, the following areas:

    • Data Science for the Sustainable Development Goals
    • Healthcare
    • Agriculture
    • Wildlife conservation
    • Disaster response
    • Geospatial modelling
    • Telecommunications data modelling
    • Economic monitoring

    During the panel discussions, we will unite a wide range of stakeholders, including data scientists, representatives from government, development practitioners and the private sector; this will provide a unique setting in which innovative solution driven ideas can thrive.

    Participants will also develop a framework for attracting young African talent, mentors and researchers from academia, the public sector and the private sector in Africa to engage in activities geared towards harnessing big data and real-time analytics for the public good.

    Workshop programme outline:

    Draft Schedule

    Workshop Day 1

    Time

    Presentation

    08:00-09:00

    Arrival and Registration

    09:00-09:10

    Welcome remarks
    Program Chair- Charles I. Saidu

    09:10-09:30

    Opening remarks
    General Chair- Ayorko Korsah

    09:30-10:15

    Keynote 1- End-to-end Data Science
    Billy Okal

    10:15-11:15

    AI technology for health talks

    11:15-11:45

    Teak Break

    11:45-12:25

    Keynote 2- TBD
    TBD

    12:25-13:10

    Presentations...

    13:10-14:10

    Lunch Break

    14:10-14:55

    Keynote 3- TBD
    Neil Lawrence

    14:55-15:40

    Presentations...

    15:40-16:10

    Tea Break

    16:10-17:30

    Presentations...

    17:30-18:30

    Wrap-up day 1

    Workshop Day 2

    Time

    Presentation

    08:00-09:00

    Arrival and Registration

    09:00-09:30

    Keynote 4 - Satellite Images
    John Quinn

    09:30-11:00

    Presentations...

    11:00-11:30

    Tea Break

    11:30-12:00

    Keynote 5 - IoT Deployments for Ecosystem Monitoring
    Ciira Maina

    12:00-13:00

    Presentations

    13:00-14:00

    Lunch Break

    14:00-14:30

    Keynote 6 - TBD
    Elaine Nsoesie

    14:30-15:30

    Panel Session - Data Science Ethics
    Martin Mubangizi

    15:30-16:00

    Tea Break

    16:00-16:30

    Presentations - Natural Language Processing

    16:30-17:00

    Keynote 7 - Growth Data Science
    Damon Civin

    17:00-17:15

    Closing
    Charles I. Saidu

    Collaborators

    Sponsorship

    Gold Sponsors

    Silver Sponsors

    Bronze Sponsors

    Sponsoring Data Science Africa 2019 Event is a great way to communicate your commitment to support the achievement of the sustainable development goals. To become a sponsor, please contact Data Science Africa at info@datascienceafrica.org