AIMS-GPSDD Data Science Fellowship Program

Program Background

The African Institute for Mathematical Sciences (AIMS) is a part of the partners network of the Global Partnership for Sustainable Development Data (GPSDD). GPSDD is a global network whose mandate is to use data to achieve the Sustainable Development Goals – improving lives, fighting inequality, and promoting environmental sustainability.

AIMS participated in the Data for Now workshop that GPSDD organised in Kigali during which AIMS was identified as one of the key academic and research partners to support capacity development efforts for this initiative. The Data for Now seeks to leverage collaboration and partnership with institutions like AIMS to increase the sustainable use of robust methods and tools that improve the timeliness, coverage, and quality of SDG data.

In collaboration with the UN Economic Commission of Africa (UNECA), GPSDD has mobilized partnerships to help African governments better respond to the ongoing and evolving COVID-19 pandemic and build the necessary capacity for the continent’s resilience.

As part of the ongoing efforts to combat ongoing and evolving COVID-19 pandemic, digitalisation has been identified as key in driving new COVID-19 response strategies. The needs of more capacity in data science are even more pressing in the New Normal created by the pandemic. Against this background, AIMS and GPSDD agreed to partner and pilot the Data Science Fellowship Program, which has two components including training and internship opportunities.

Training Program

The training component of the fellowship program aims to build data science capacity of civil servants from selected National Statistical Offices (NSO) and other key government institutions of 13 countries.

Building on past experiences of implementing the Big Data for Development project with the support of the World Bank Group, AIMS has developed an Introductory Data Science Course which will be delivered over a month with the following:

1. Python for Data Science

2. Data Pre-processing

3. Data Visualization

4. Machine Learning (ML) in Python

5. Real-Life Use Cases

This introductory course aims to teach the essential basics of processing large scale datasets using Python. In addition, the course also teaches how to perform common data science tasks such as data wrangling and building machine learning models in Python. This course takes a practical approach to equip participants with the most essential tools in the shortest possible time. The course emphasizes learning by doing, as such, there are a lot of exercises built into the course to give participants ample time to practice and be able to develop their respective use cases to apply these skills in real-life problems including COVID-19 data analysis.

The objectives and outcomes of the course will be adjusted to the program expectations.

1. Understand intermediate to advanced concepts of the Python language including data structures, functions, classes and the python packages ecosystem

2. Perform data science tasks using Python: data ingestion, processing, visualization, web scraping etc.

3. Handle large scale dataset (20gb+) using Apache Spark: big data basics, Hadoop ecosystem, cloud computing platforms, big data processing with Apache Spark.

4. Familiarize with essential machine learning (ML) theory: the learning problem, types of learning, loss functions, linear models, deep learning and more.

5. Build and evaluate machine learning models: use scikit-learn and TensorFlow to build and evaluate models using Python.

6. Appreciate real world ML and big data use cases: object detection in android devices, analyze large scale gps data for human mobility use cases or COVID-19.

Over 70 civil servants from various institutions of governments of 13 countries (Botswana, Ghana, Madagascar, Malawi, Mali, Mauritius, Nigeria, Senegal, Sierra Leone, Somalia, Somaliland and Togo) and the UN Economic Commission of Africa (UNECA) are expected to participate in this training.

Internship Program


Applications are now closed!!

This component of the program aims to provide promising AIMS alumni with internship opportunities to support Data Science projects in National Offices of Statistics, other government institutions and the UN Economic Commission of Africa (UNECA).

AIMS alumni interested in applying for this internship opportunity should use their AIMS email address and click the link provided below to complete and submit their application with all supporting documents as soon as possible. Shortlisted candidates will be contacted for further steps of the selection process.

Successful candidates will receive a monthly stipend to cover their cost of living in the internship host country, including accommodation and meals for 4 months.

Eligibility:

This program is restricted to AIMS alumni who are both citizens and residents of one of the following countries: Botswana, Ghana, Madagascar, Malawi, Mali, Mauritius, Nigeria, Senegal, Sierra Leone, Somalia, Somaliland and Togo.

Application submission:

Applications for this program should be submitted via the online application system, providing all required documents. Applications will be reviewed by a committee with members from AIMS and the institution that submitted the project.

Duration: 4 months (April to July 2021).

Deadline: March 30th, 2021 at 7 pm CAT.

Successful applicants will be contacted as soon as possible. Please consider your application unsuccessful if you don’t hear from the program team within weeks of the deadline. All inquiries should be sent to: aii@nexteinstein.org.


Applications are now closed!!