30 April, 2022

About the “Event”

The Department of Information Technology organized a Workshop on Artificial Intelligence and Machine Learning (AI–ML) aimed at introducing students to the fundamentals, models, and practical applications of Machine Learning. The workshop was conducted in five sessions of 90 minutes each, covering both supervised and unsupervised learning techniques along with their evaluation methodologies. The sessions were interactive, with conceptual explanations supported by practical demonstrations and assessment activities.

Objectives of the “Event”

• To familiarize participants with the AI fundamentals and types of Machine Learning.
• To provide hands-on understanding of supervised and unsupervised learning algorithms.
• To introduceevaluation metrics for regression and classification models.
• To demonstrate the use of clustering techniques and their performance measures.
• To enableparticipants to gain practical insightsinto real-world applications of ML.

Content/Discussion Points of the “Event”

• Introduction to MachineLearning – Fundamentals & Types
• Simple LinearRegression & Evaluation Metrics (Regression)
• Logistic Regression & Evaluation Metrics(Classification)
• K-Nearest Neighbors(KNN) & Confusion Matrix
• K-Means Clustering & Evaluation Techniques
• Assessment and Feedback Session

Outcomes of the “Event”

• Understand the Basics of Artificial Intelligence.
• Understand conceptsof Machine learning and algorithms
• Understand uses of Pythonfor Machine Learning and Deep Learning
• Use data analytics tools and technologies with ease
• Understand and experience in building real-world solutions for Data Analytics
• Translate data-driven insights into decisions and actions