After completion of the course, the students will be able to:

CO1: Understand the significance of value inputs in a classroom, distinguish between values and skills, understand the need, basic guidelines, content, and process of value education, explore the meaning of happiness and prosperity, and do a correct appraisal of the current scenario in society.

CO2: Distinguish between the Self and the Body, and understand the meaning of Harmony in the Self and the Co-existence of Self and Body.

CO3: Understand the value of harmonious relationships based on trust, respect, and other naturally acceptable feelings.

CO4: Apply in human-human relationships and explore their role in ensuring a harmonious society.

CO5: Create harmony in nature and existence, and work out their mutually fulfilling participation in nature.

CO6: Distinguish between ethical and unethical practices, and start working out the strategy to actualize a harmonious environment wherever they work.

 



TCS-364 -- Fundamentals of Artificial Intelligence and Machine Learning

After completion of the course, the students will be able to:

CO1: Define Artificial Intelligence (AI), Machine Learning (ML), and  Deep Learning, and differentiate between them.

CO2: Explain problem-solving frameworks in AI and describe search  strategies like breadth-first, depth-first, and A*.

CO3: Choose appropriate classification techniques like Logistic  Regression, KNN, or SVM based on specific data  characteristics.

CO4: Compare and contrast different performance metrics like  accuracy, precision, recall, and F1-score for evaluating ML  models.

CO5: Evaluate the strengths and limitations of specific unsupervised  learning techniques like K-means and hierarchical clustering for  a given task.

CO6: Design a simple machine learning pipeline involving data pre￾processing, model selection, and evaluation for a classification task.


Dear All,
This an Audit Course which provides you with a basic idea of probability and statistics. This course will help to understand probability models and statistical methods for analyzing data.
This course is very useful for students of engineering and the natural sciences.