Title

CSCI1011 - Survey of Artificial Intelligence

Description

Description

This course provides an introduction to artificial intelligence (AI), machine learning (ML) and deep learning (DL). Students explore foundational concepts, real-world applications and ethical implications of AI technologies. Through hands-on labs using Python, students learn how to prepare data, build simple ML models, evaluate performance and experiment with neural networks, computer vision and natural language processing. The course concludes with a final project in which students develop and present a simple AI application.
API ID

Credits

3 (2/1/0)

Competencies

  1. Explain artificial intelligence, machine learning and deep learning.
  2. Identify real-world applications of artificial intelligence in healthcare, education, transportation and finance.
  3. Use Python libraries (NumPy, Pandas, scikit-learn, TensorFlow/Keras) to build machine learning models.
  4. Implement regression, classification and clustering algorithms.
  5. Apply evaluation metrics such as accuracy, precision, recall and F1 score.
  6. Build a simple neural network for classification.
  7. Experiment with computer vision and natural language processing tasks using modern tools.
  8. Explain how generative artificial intelligence models, such as generative pre-trained and bidirectional encoder representation transformers, work at a high level.
  9. Critically analyze ethical issues related to artificial intelligence and algorithmic bias.
  10. Design and present an artificial intelligence mini-project addressing a real-world problem.