B. Tech Artificial Intelligence & Machine Learning

About This Course

Tech in AI & ML provides the budding engineers with a spectacular array of courses dedicated to frontiers in the field of Artificial Intelligence and Machine Learning (AI&ML) with a foundation of Computer Science & Engg. The 4-year full-time program presents exposure to hands-on technologies to create applications and solutions for the world that we live in. B.Tech course in Artificial Intelligence and Machine Learning which aims to develop a strong foundation by using the principles and technologies that consist of many facets of Artificial Intelligence including logic, knowledge representation, probabilistic models, and machine learning. This course is best suited for students seeking to build world-class expertise in Artificial Intelligence and Machine Learning and emerging technologies which help to stand in the crowd and grow careers in the upcoming technological era.

The course is designed to give the students enough exposure to the variety of applications that can be built using techniques covered under this program. They shall be able to apply AI/ML methods, techniques and tools to the applications. The students shall explore the practical components of developing AI apps and platforms. A proficiency in mathematics will prove to be beneficial as this degree requires strong problem-solving and analytical skills. They shall be able to acquire the ability to design intelligent solutions for various business problems in a variety of domains and business applications. The students shall be exploring fields such as neural networks, natural language processing, robotics, deep learning, computer vision, reasoning and problem-solving. The key objective is to identify logic and reasoning methods from a computational perspective, learn about agent, search, probabilistic models, perception and cognition, and machine learning.

With a huge explosion in data and its applications, a career in the field of AI&ML can be very promising as Big Data Engineer, Business Intelligence Developer, Data Scientist, Machine Learning Engineer, Research Scientist, AI Data Analyst, AI Engineer, Robotics Scientist, etc. With a specific job description on AI&ML, students have been recruited by reputed industries.

Program Outcomes

Engineering Graduates will be able to:

  1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  2. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
  3. Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
  4. Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
  5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
  6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
  7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
  8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  10. Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
  11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
  12. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.

 

Program Educational Objectives (PEOS)

PEO 1 : Graduates will gain expertise in the emerging areas of Machine Learning and Artificial Intelligence.

PEO 2 : To prepare graduates into industry ready professionals and efficient researchers with sense of social responsibilities.

PEO 3 : Graduates will demonstrate proficiency in soft skills, ethical approaches, team work and life-long learning.

Program Specific Outcomes (PSOS)

PSO 1 :  Graduates will apply their programming skills for providing efficient and cost-effective solutions to engineering problems.

PSO 2 : Graduates contribute towards the knowledge base through significant research activities and develop themselves into professionals who are ready to serve the industry and society at large.

Value Added Courses

  1. Python Programming
  2. Machine Learning with Python
  3. Deep Learning and Neural Networks with Keras
  4. IBM AI Engineering professional Certificate
  5. Blockchain Technology
  6. Cyber Security
  7. Cloud Computing
  8. Drone Technology
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