English

This course provides an overview of chemical ecology and aims to understand the history, development, and core concepts of chemical ecology.  It introduces how organisms interact via chemicals, focusing on insects and plants.   The course requires basic knowledge of biology and chemistry. 

This course introduces students to the concepts and methodology needed to implement and analyze computational models of cognition. It considers the fundamental issues of using a computational approach to explore and model cognition. In particular, this course explores the way that computational models relate to, are tested against, and illuminate psychological theories and data. The course introduces both symbolic and subsymbolic modelling methodologies, and provides practical experience with implementing models. The symbolic part focuses on cognitive architectures, while the subsymbolic part introduces probabilistic models. 

This course examines the analytical and managerial tasks involved in developing strategies that create value by satisfying customer demands and stakeholders’ interests in an everchanging competitive landscape. it covers strategy issues from the perspectives of Western firms as well as emerging market firms, both of which increasingly exposed to international competition. 

The course focuses on issues of post-conflict reconstruction and security - arms proliferation, drug trafficking, mercenaries as well as institutions of transitional justice - International Criminal Court, Truth Commissions, Special courts and tribunals.

This course focuses on concepts and contents of human rights. It examines international, regional and national conventions and legislations on human rights with specific reference to the rights of vulnerable populations. Additionally, the course reviews Ghana's compliance with human rights laws.

This course discusses the basic principles and molecular controls of embryonic development, emphasizing the progression from gametogenesis, fertilization, cleavage to gastrulation (i.e., the formation of the gut). The course also covers cell fate and embryonic axis determination as well as popular experimental models used by current developmental biologists. The course studies formation and derivatives from three germ layers, ectoderm, mesoderm and endoderm. The course then ends with a review of tissue and organ regeneration and the progression of regenerative medicine.  

This is the first course, in a two-semester course series, designed primarily for undergraduate psychology majors or minors who anticipate future applications of statistical methods. Topics covered in this course include an overview of descriptive statistics, foundational concepts in inferential statistics (probability, population, sample, sampling methods, sampling distributions, estimation of population parameters, binomial, normal, t, and F distributions), hypothesis significance testing (Type I and II errors, statistical power), and comparisons of means (t-tests, oneway analysis of variance, multiple comparisons of means, and effect sizes). 

Course prerequisite: Mastery of algebra and analytical geometry at the high-school level. 

Artificial intelligence in medicine has created tremendous business opportunities recently, creating an ideal environment for AI-Biomedical interdisciplinary specialists to make considerable contributions and significantly impact the world. Intelligent medicine aims to utilize state-of-the-art AI technologies for many medical applications such as accurate disease risk prediction and essential predictors selection, which are for early precise and efficient treatments. This course introduces the vast potential of intelligent medicine, seeking to advance student skills and motivation for AI-Biomedical interdisciplinary science.  

The course also introduces potential partners for future interdisciplinary collaboration to our students and provide opportunities for practical implementations through several carefully designed experiments, which shall demonstrate how to leverage real-world medical resources and related AI technologies. The course includes visits to prestigious companies and institutes and as well as seminars. 

This course examines various big data sources covering different urban aspects and the extensive information carried by big data. It looks at various urban dynamics, including but not limited to the everyday issues of housing, mobility, consumer markets, social
interactions, and environmental sustainability.