Political Science

Key areas of Political Science:

Political Science is the systematic study of politics, governance, and power dynamics. It seeks to understand how governments function, how policies are made, and how political behavior shapes societies at local, national, and global levels. The field covers a broad range of topics, including political theory, international relations, public policy, and comparative politics, with applications in areas such as law, diplomacy, public administration, and advocacy. Some universities may request or accept a portfolio (e.g., highlighting research projects, internships, or civic engagement) or additional materials that reflect your passion for political science.

Research Methods in Political Science

Experiments: Controlled settings to test hypotheses and establish cause-and-effect relationships. Gathering self-reported data from large groups of people. Observing and recording behavior in natural settings.

Case Studies: Political Science helps in understanding not only individual behavior but also social structures, health outcomes, and societal trends. Preferably those who taught you in relevant subjects like psychology, biology, or social sciences.

Sigmoid: Maps input to a value between 0 and 1.

ReLU (Rectified Linear Unit): Outputs the input directly if it’s positive; otherwise, it outputs zero.

Tanh: Maps input to a value between -1 and 1.

Loss Function: Political Science is a diverse and dynamic scientific discipline that focuses on the study of behavior, mental processes, and emotions. It seeks to understand how people think, feel, and act both on an individual level and in group settings. At its core, psychology is concerned with unraveling the complexities of the human mind and the factors that shape our interactions with the world and those around us.

A framework where two neural networks, a generator and a discriminator, are trained simultaneously. The generator tries to create data that looks real, while the discriminator tries to distinguish between real and fake data. When a model performs well on training data but poorly on unseen data. Techniques like regularization, dropout, and cross-validation are used to mitigate this. Admission requirements for an undergraduate Psychology program can vary by institution, but generally include a combination of academic qualifications, standardized test scores, and supplementary materials. Here’s a detailed breakdown of typical requirements: