Message from the Head of Department (HoD)

It gives me immense pleasure to welcome you to the Artificial Intelligence and Machine Learning (AIML) Department. In this era of technological transformation, AI and ML are reshaping industries, redefining human capabilities, and creating new opportunities for innovation. Our department is committed to empowering students with the knowledge, skills, and ethical grounding needed to excel in this dynamic field.

I invite you to join us on this exciting journey as we shape the future of Artificial Intelligence and Machine Learning.

Course Overview

The Diploma in Artificial Intelligence and Machine Learning is a comprehensive program designed to equip students with the technical and analytical skills required to excel in the rapidly advancing field of AI and ML. This course blends theoretical foundations with hands-on experience, enabling learners to develop innovative solutions to complex real-world challenges using state-of-the-art tools and techniques.

The curriculum encompasses a wide range of topics, including programming, machine learning algorithms, deep learning, natural language processing, neural networks, computer vision, and AI model deployment. Students will gain proficiency in building and optimizing predictive models, automating intelligent systems, and applying AI-driven solutions across diverse industries.

Program Outcome

1. Basic and Discipline specific knowledge: Utilize a strong foundation in basic mathematics, science, and engineering principles, along with expertise in a specific engineering field, to effectively address and solve engineering challenges.

2. Problem Analysis: Recognize and assess clearly defined engineering issues by applying established and recognized methodologies.

3. Design/ development of solutions: - Develop solutions for clearly defined technical challenges and contribute to the design of system components or processes that fulfill specific requirements.

4. Engineering Tools, Experimentation and Testing: - Employ advanced engineering tools and suitable techniques to perform standard tests and gather accurate measurements.

5. Engineering practices for society, sustainability and environment: - Implement suitable technologies while considering their impact on society, sustainability, the environment, and adhering to ethical practices.

6. Project Management: Apply engineering management principles, either independently, as a team member, or as a leader, to oversee projects and communicate effectively about clearly defined engineering tasks.

7. Lifelong Learning: The capacity to assess personal learning needs and actively pursue knowledge updates in response to technological advancements

Course Outcome

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Course Outcome - Program Outcome Mapping

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Frequently Asked Questions