ASMN Premium Members’ Interactive Session holds 30th March 2025

To further empower African Scholars Mentorship Network (ASMN) Premium members for greater competence and get progress reports since its launch in 2024, DIaDeRC is holding an interactive session for ASMN premium members.

The event is geared toward receiving progress reports and feedback from the various clusters that ASMN Premium Members belong to. The virtual session will be held on Sunday, 30th March 2025, by 5 pm (GMT+1).  Apart from the  DIaDeRC Chair & ASMN Coordinator, Prof Evans Osabuohien, who is the host, other experts from the DIaDeRC Team will be joining him.

It is FREE and exclusively for ASMN Premium members. However, interested persons who want to be part of it are encouraged to sign up for ASMN Premium membership via this LINK.

Another important feature of the event is that it will have an expert in Data Science who will be joining us to espouse the opportuties latent therein.

The highlights are provided below:

Course Description:

This course introduces data science methods and their applications in applied economics and related fields. Participants will explore the machine learning workflow, including data collection, model development, evaluation, and programming tools like Python. While theoretical aspects will be considered, emphasis will be placed on the practical implementation through hands-on exercises, participants will develop skills essential for running models. Together, we will develop machine learning techniques using structured and unstructured data. The emphasis of the course will be on the meaningful integration of data science methods into applied economics. Participants will learn to apply their skills to working on problems in economics and related fields.

Learning objectives:

Participation in the course is expected to be hands-on, with the expectation of applying different data science techniques for different data types. To achieve this objective, each discussion topic is accompanied by a practical lab session. Specific objectives are: – Brief refresher of statistics and economic experiments – Develop a comprehensive understanding of key principles in statistical machine learning, including supervised and unsupervised learning, model evaluation, regularization, and dimensionality reduction. – Gain practical experience in applying machine learning methods to analyze and solve real-life problems

Guest Facilitator:

Oluwatosin Aderanti is a Data Scientist with a doctorate degree in Applied Economics. She fancies empirical research work both in academic and industrial settings. On the substantive level, her research pays particular attention to economic development. Her non-academic experience includes work on mergers and acquisitions in the crop science industry and work in governance as a Special Adviser on the concluded United Nations Millennium Development Goals (MDGs). After completing her PhD, she attended a Data Science training at the renowned Constructor Academy in Munich, Germany, where she gained skills in natural language processing, machine learning, and deep learning.