Artificial Intelligence and Machine Learning

Welcome to Department of Artificial intelligence

Artificial intelligence and Machine Learning are the part of computer science that are correlated with each other. These two technologies are the most trending technologies which are used for creating intelligent systems.

Artificial intelligence is a field of computer science which makes a computer system that can mimic human intelligence. Machine learning is about extracting knowledge from the data.

• AI refers to the simulation of human intelligence in machines that can perform tasks that typically require human intelligence.
• The ultimate goal of AI is to create intelligent agents capable of understanding, reasoning, learning, and problem-solving. AI encompasses a wide range of techniques and approaches to achieve these capabilities, including machine learning, natural language processing, computer vision, robotics, Drone applications and many more.
• Machine Learning is a subset of AI that focuses on the development of algorithms and statistical models that enable computers to learn and improve their performance on specific tasks without being explicitly programmed. Instead of following predefined rules, ML algorithms use data to identify patterns, make predictions, or optimize decision-making processes.
• Machine Learning is widely used in various applications, including image and speech recognition, natural language processing, recommendation systems, autonomous vehicles, and many other AI-driven technologies.
• In summary, AI is the overarching field focused on creating intelligent machines, while Machine Learning is a subset of AI that deals specifically with enabling machines to learn and improve from data without explicit programming. Both AI and ML play critical roles in shaping the future of technology and have applications across various industries and domains.

Vision

• Transform Industry and Society at large through the power of AI.

Mission

• Impart quality education to generate skilled manpower through the state-of-the-art concepts and technologies in Artificial Intelligence and Machine Learning.
• Mould students to be technically competent using knowledge in AI space and entrepreneurship development.
• Inculcate values of professional ethics, social concerns, environment protection and life-long learning.
• Establish center of excellence in computing and artificial intelligence for developments in interdisciplinary areas.

•  Program outcomes (Pos)
  1. Basic and discipline specific knowledge: Apply knowledge of basic mathematics, science and engineering fundamentals and engineering specialization to solve the engineering problems.
  2. Problem analysis: Identify and analyze well-defined engineering problems using codified standard methods.
  3. Design/ development of solutions: Design solutions for well-defined technical problems and assist with the design of systems components or processes to meet specified needs.
  4. Engineering tools, experimentation and testing: Apply modern engineering tools and appropriate technique to conduct standard tests and measurements.
  5. Engineering practices for society, sustainability and environment: Apply appropriate technology in context of society, sustainability, environment and ethical practices.
  6. Project management: Use engineering management principles individually, as a team member or a leader to manage projects and effectively communicate about well-defined
  engineering activities.
  7. Life-long learning: Ability to analyze individual needs and engage in updating in the context of technological changes.
•  PEO’s:
  PEO – 1. The students will socially responsible to creates environment friendly AI solutions for real-time problems adapting professional ethics.
  PEO – 2. The students will practice AI framework and technologies in multidisciplinary work environments.
  PEO – 3. The student will be able to work individually and as a team by communicating effectively in their area of work.
• PSO’s:
  PSO – 1. Students will able to solve real-life problem using latest and advanced technologies in artificial intelligence and machine learning field.
  PSO – 2. Apply knowledge of computer engineering and an understanding of management principles for applying them while managing artificial intelligence and Data
  science projects.

HOD’s desk
I am eager to collaborate with each of you to achieve our departmental goals and strengthen our position as a leading force in AI and ML. As we move forward, I would like to emphasize a few key points:

1. Research Excellence: Let us continue pushing the boundaries of AI and ML research. partnerships with industry and academia.
2. Student Collaborate with your peers, seek out opportunities for interdisciplinary projects, and engage in Engagement: Our students are the future leaders in AI and ML. Let us provide them with a nurturing environment where they can develop their skills, engage in hands-on projects, and contribute to real-world applications.
3. Diversity and Inclusion: We are committed to fostering a diverse and inclusive department. Embracing different perspectives and backgrounds enriches our research and educational experiences.
4. Professional Development: Let us support each other in our professional growth. Encourage participation in conferences, workshops, and continuous learning to stay at the forefront of AI and ML advancements.

1.Path chart

Semester-I

Semester-II

Semester III

Semester IV

Semester V

Semester VI