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.

Summer School on Machine Learning and Data Science
Dates: 27 June - 29 June 2016
Venue: Makerere University, Kampala, Uganda
 

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, IBM Research, Facebook, Pulse Lab Kampala and the AI and Data Science (AIR) lab-Makerere University.

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. To benefit from this course participants are encouraged to have some background in programming particularly programming with Python.

School programme outline:

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.

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

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 and do the exercises in there. If you have not used jupyter notebook before, make friends with Google - a friend in need …

Time

Activity

Material

08:00-08:30

Arrival and Registration

08:30-09:00

Opening Remarks
Dean, School of Computing & IT, Makerere University
Prof. Neil Lawrence

Session 1 (Machine Learning and Data Science)

09:00-10:00

Lecture 1: Introduction to Data Science and Machine Learning
Neil D. Lawrence - University of Sheffield

video

10:00-10:30

Break

Session 2 (Machine Learning)

10:30-12:00

Lecture 2: Introduction to Classification
Michael T. Smith - University of Sheffield

html video

12:00-13:00

Lecture 2: Practice Session
All facilitators

code

13:00-14:00

Lunch

14:00-15:20

Lecture 2: Practice Session

15:20-15:30

Break

Session 3 (Data Science)

16:00-16:30

Lecture 3A: Spatial Data Analysis
Ricardo Andrade - UCSF Global Health Science

slides video

16:30-17:00

Lecture 3B: From raw data to meaningful features
Andreas Damianou - University of Sheffield

slides ipynb video

17:00-18:00

Lecture 3: Practice Session

Time

Activity

Material

Session 4 (Data Science)

09:00-10:00

Lecture 4: Data Wrangling with Pandas
Martin Mubangizi - Pulse Lab Kampala

ipynb data video

10:00-10:30

Break

10:30-12:00

Lecture 4: Practical Session

video

Session 5 (Machine Learning)

12:00-13:00

Lecture 5: Classification Continued
John Quinn - Pulse Lab Kampala and Makerere University

html video

13:00-14:00

Lunch

14:00-15:20

Lecture 5: Practical Session Malaria Detection

ipynb data

15:20-15:30

Break

Session 6 (Data Science)

15:30-16:30

Lecture 6: Data Exploration and Visualization
Ernest Mwebaze - Makerere University

video

16:30-18:00

Lecture 6 Practical Session

ipynb code

Time

Activity

Material

Session 7 (Data Science)

09:00-10:00

Lecture 7: Text Mining
Fred Kiwanuka - UNICEF

video

10:00-10:30

Break

10:30-12:00

Lecture 7: Practical Session
All facilitators

ipynb data

Session 8 (Machine Learning)

12:00-13:00

Model Selection
Ciira Maina - Dedan Kimathi University of Technology

PDF slides video

13:00-14:00

Lunch

14:00-15:20

Lecture 8: Practical Session

ipynb

15:20-15:30

Break

Session 9 (Data Science)

15:30-16:30

Lecture 9
IBM Research Nairobi

16:30-18:00

Lecture 9: Practical Session

18:00-19:30

Cocktail
Prof. Barman

The summer school is now fully subscribed, and registration has closed.

Data Science in Africa Workshop
Dates: 30 June - 01 June 2016
Venue: Pulse Lab, Kampala, Uganda
Program Chair: John Quinn
Program Chair: Ernest Mwebaze
Program Chair: Mubangizi Martin Gordon

Theme

Using data science to monitor and achieve the global goals in Africa

Call for Registration

The workshop will be organized around interactive panel discussions. Each panel will discuss how data science can advance the achievement of a specific Global Goal on the African continent.

This is part of the event will unite a wide range of stakeholders, uniting data scientists with representatives from government, development practitioners and the private sector; 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:

Schedule

Time

Presentation

09:00-09:30

Workshop Opening

Remarks by UN Resident Country Coordinator Ms Rosa Molango
Rosa Molango

09:30-10:00

Introduction Presentation
Pulse Lab Kampala data science team on current projects - Pulse Lab Kampala

video

10:00-10:20

Break

10:20-11:00

Current data science work at IBM Research Africa, including Cognitive Companions in Healthcare and Education.
Simone Fobi and Oliver Bent and Skyler Speakman - IBM Research Africa

video

11:00-13:00

Data Science for Agriculture

Big Data for Agriculture: Opportunities in Africa
Evan Girvetz - International Center for Tropical Agriculture (CIAT)

video

Smartphone-based Disease Surveillance
Ernest Mwebaze - Makerere University/Pulse Lab Kampala

video

KUDU: Mobile-Based Agricultural Market in Uganda
Richard Ssekibuule - Kudu

video

A Framework for Decision Support Tools to Optimize Smallholder Dairy Production in East Africa
Gladness Mwanga - Nelson Mandela African Institute for Science and Technology, Arusha, Tanzania

video

Data on Livelihoods to Target and Track Agricultural Interventions
Godfrey Taulya - IITA Uganda

video

Breed Composition of Tanzania Crossbred Dairy Cattle
Evans Cheruiyot - University of Nairobi and Usami Genomics Kenya

video

13:00-14:00

Lunch

14:00-15:30

Data Science for Sustainable Cities

Sustainable Urban Planning Using Big Data from Mobile Phones
Daniel Emaasit - University of Nevada, Las Vegas

video

An Atlas of Kampala Buildings
Bernard Wright - Geo Gecko

video

Telemetry for Urban Planning Case Study: Boda Boda
Joseph Kaizi - Thin Void

video

Crowd Sourced Transcription of Kampala's Traffic Collision Data
Michael T. Smith - University of Sheffield

video

16:00-16:30

Data Collection and Curation

Open Data Practice and Principles with the Kenya Open Data Initiative
Prestone Adie - Kenya Open Data Initiative

video

IVR Surveys
Jamie Arkin - Human Network International

video

16:30-17:00

AI Research at Facebook
Moustapha Cisse - Facebook AI Research

17:00-18:00

Networking

Time

Presentation

09:30-10:00

The Kenya Bioacoustics Project
Ciira Maina - Dedan Kimathi University of Technology, Nyeri, Kenya

video

10:00-10:30

New Directions in Data Science
Neil Lawrence - University of Sheffield

video

630.0

An Axis of Data Science Research
Dina Machuve - Nelson Mandela African Institute of Science and Technology

video

10:30-11:00

Break

11:00-13:30

Data Science for Health

Data Science for Malaria Elimination
Ricardo Andrade - University of California San Francisco

video

Social Science Approaches to Data Science
Kerry Holden - Queen Mary University of London

video

Automated Mobile Microscopic Diagnosis
Rose Nakasi - Makerere University

video

Monitoring Option B+ in Real Time
Martin Mubangizi - Pulse Lab Kampala

video


Arigye Joreen - Medical Access Uganda

13:30-14:30

Refereshments

14:30-15:30

Data Science for Planning and the Environment

Data Science at UNICEF
Fred Kiwanuka - UNICEF

video

Enhancing Water Quality Monitoring Efforts in the Lake Victoria Using Satellite Imagery
Anthony Gidudu - Geomatics and Land Management, Makerere University

video


Fred Kitoogo - National information Technology Authority


Joryne Arigye - Makerere University

video

15:30-16:30

Data Science Training and Mentorship in Africa


Paula Hidalgo Sanchis - Pulse Lab Kampala

video

'Data Science' Training & Mentoriship Programs: A Silicon Valley Hiring Manager Perspective
Eric Williams - Omada Health

video


Engineer Bainomugisha - Makerere University

16:30-17:30

Networking

The workshop is now fully subscribed, and registration has closed.

Collaborators

Sponsorship

Sponsoring Data Science Africa 2016 Event is a great way to communicate your commitment to support the achievement of the sustainable development goals. We thank this year's sponsors: