Teacher
Department of Psychology The Department of Psychology at Baseerat Institute of Computer and Social Studies, Karachi is dedicated to understanding the human mind, behavior, and emotions through scientific inquiry and practical application. Our mission is to prepare students to explore the psychological foundations of human thought and behavior while promoting mental health and social well-being in our communities. At Baseerat, we combine academic theory with real-world practice, encouraging students to engage in research, counseling techniques, and community outreach programs. Our curriculum covers a wide range of areas, including clinical psychology, educational psychology, social psychology, cognitive science, and behavioral research, enabling students to develop a deep and holistic understanding of the discipline. Graduates of our Psychology program are equipped with the knowledge, empathy, and analytical skills needed to pursue careers in counseling, education, healthcare, research, and social services, or to continue their studies at advanced levels. We believe that studying psychology at Baseerat is not just about learning — it’s about understanding humanity and contributing positively to the mental and emotional growth of society..
Nutmeal is a nutritious category of food that includes various types of ground nuts, such as almonds, walnuts, and peanuts These ground nuts can be used in a variety of recipes
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: sychology helps in understanding not only individual behavior but also social structures, health outcomes, and societal trends.
Loss Function: This function measures the difference between the network’s output and the actual target. Common loss functions include Mean Squared Error (for regression tasks) and Cross-Entropy Loss (for classification tasks).
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.
| Qualification | Length | Code |
|---|---|---|
| Bsc (Hons) | 3 years full time | CDX3 |
| Bsc | 4 years full time | CDX4 |
25 sections , 55 leactures
