The Department of Computer Science (Data Science and Analytics), Subbalakshmi Lakshmipathy College of Science, organized a Value Added Course titled “Foundational AI/ML Use Cases” for the students of II B.Sc CS(DSA) to strengthen their understanding of Machine Learning algorithms and model evaluation techniques through practical, application-oriented learning.
The course focused on the fundamentals of supervised and unsupervised learning, with an emphasis on understanding and applying appropriate Machine Learning algorithms to real-world problems. The topics covered included regression for predictive analytics, classification algorithms such as Logistic Regression, Decision Trees and Naive Bayes, and Convolutional Neural Networks (CNNs) for image
classification and handwritten digit recognition. Students were also introduced to clustering and recommendation system concepts, sentiment analysis, face detection using OpenCV, and predictive modelling using sample datasets from different application domains.
A key component of the course was the evaluation of Machine Learning models using appropriate performance metrics. Students were introduced to the importance of assessing model performance, comparing algorithm outputs and selecting suitable evaluation measures for regression and classification tasks. The course also emphasized data cleaning, preprocessing, feature preparation and visualization as
essential steps in building reliable Machine Learning models.
The course enabled students to develop a foundational understanding of Machine Learning algorithms and their practical applications. Students gained awareness of model evaluation metrics and the importance of measuring prediction performance, comparing algorithms and selecting suitable models for specific problems. The programme provided a foundation for further learning and project development in
Artificial Intelligence and Machine Learning.
Totally 39 students attended the Value Added Course and get benefitted.
