Data Science Africa, 2015
Nyeri, Kenya
Welcome to the website of the Workshop on Data Science in Africa, to be held at Dedan Kimathi University of Technology in Nyeri, Kenya.
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.
The workshop aims (1) to bring together leading researchers and practitioners working on data science methods or applications relevant to Africa, and (2) to provide training on state of the art data science methods to students and others interesting in developing practical skills.
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:
Time |
Activity |
Material |
---|---|---|
08:00-09:00 |
Arrival and Registration |
|
09:00-09:30 |
Opening Remarks |
|
|
||
09:30-10:30 |
Lecture 1: Introduction to Machine Learning and Data Science |
|
10:30-11:30 |
Break |
|
11:00-13:00 |
Lecture 2: Regression |
|
13:00-14:00 |
Lunch |
|
14:00-17:00 |
Lab 1 Regression |
Time |
Activity |
Material |
---|---|---|
Classification |
||
09:00-10:30 |
Lecture 3: Classification |
|
10:30-11:30 |
Break |
|
11:00-13:00 |
Lecture 4: Worked Example: Malaria Parasite Classification |
|
13:00-14:00 |
Lunch |
|
14:00-17:00 |
Lab 2 |
Time |
Activity |
Material |
---|---|---|
Unsupervised Learning |
||
09:00-10:30 |
Lecture 5: Clustering |
|
10:30-11:30 |
Break |
|
11:00-13:00 |
Lecture 6: Dimensionality Reduction |
|
13:00-14:00 |
Lunch |
|
14:00-17:00 |
Lab 3 |
|
17:00 |
Concluding Remarks |
The summer school is now fully subscribed, and registration has closed.
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:
Time |
Presentation |
|
---|---|---|
08:30- |
Arrival and Registration |
|
09:00- |
Opening Remarks |
|
|
||
|
||
|
||
09:00- |
Session 1: Agriculture |
|
09:20- |
Optimizing Small-scale Farm Management in Kenya using a Frugal Plant-Based Approach for Irrigation Scheduling |
|
09:50- |
Automated Monitoring of Viral Cassava Disease |
|
10:20-10:50 |
Coffee break |
|
- |
Session 2: Crisis Management |
|
10:50- |
Construction Of A Resiliency Platform for Preventing Future Crises In Sierra Leone |
|
11:20- |
Umati: Monitoring Dangerous Speech Online |
|
11:50- |
The Punya Mobile Application Development Platform |
|
12:20- |
|
|
- |
Session 3: Health, Bioinformatics and Privacy |
|
13:30- |
Personalised Medicine |
|
14:00- |
Improved Modelling of Malaria Incidence with Telecoms Data |
|
14:30- |
Differential Privacy |
|
15:00-15:30 |
Coffee Break |
|
15:30 |
Comparative Genomics of Tsetse's Chemosensory Proteins |
|
16:00- |
Concordance of Morphometrics and DNA barcoding in identifying Stingless bee species (Apidae: Meliponinae) in Kenya |
|
16:30- |
Investigating Traditional Systems of Medicine Using Phylogenies Derived from Gene Sequences |
Time |
Presentation |
|
---|---|---|
Session 4: Data Sources and Privacy |
||
09:00 |
Free Datasets For All |
|
09:30 |
Humanitarian Data Exchange Project |
|
10:00 |
New Sources of Information for Planning and Disaster Response |
|
10:30-11:00 |
Coffee break |
|
Session 5: Water |
||
11:00 |
Using Frugal Smart Meters to Increase Water Security in Kenya |
|
11:30 |
Understanding Nairobi's Water Supply Landscape: The Data Driven Approach |
|
12:00 |
Pivoting Entity-Attribute-Value data Using MapReduce for Bulk Extraction |
|
12:30-13:30 |
Lunch |
|
Session 6: Markets and Economy |
||
13:30 |
Auction Systems for Real-Time Agricultural Market Analysis |
|
14:00 |
Time Series Analysis of Financial Market Data [To be Confirmed] |
|
14:30 |
Wrap-up and discussion – next steps for data science in Africa? |
The workshop is now fully subscribed, and registration has closed.
Collaborators




Sponsorship
Sponsoring Data Science Africa, 2015 Event is a great way to communicate your commitment to support the achievement of the sustainable development goals. We thank this year's sponsors: