The Department of Computer Science and Engineering- Artificial Intelligence and Machine Learning (CSE-AIML) is established in the year 2020 with an intake of 60 students. Department has faculty with research experience and industry experience. The department has three years of students like first year, second year and third year. The present strength of the department is 180 students.
Artificial Intelligence and Machine Learning course 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.
Highlights of AIML
- Department offers best teaching & learning practices in Artificial Intelligence and Machine Learning program.
- Builds a solid foundation in advanced technologies of machine learning through industry-oriented curriculum.
- Hands-on industry projects and regular sessions by industry experts.
- Gain expertise in advanced topics such as web technologies, machine learning, deep learning, pattern recognition, computer vision, cognitive computing, human-computer interaction, generative AI, Sustainable AI etc.
- AIML students got internships in top companies like AMAZON, Microsoft, Optum, PWC, Hexagon.
- AIML students had bagged with industry projects in collaboration with companies like Hexagon in Deep Learning and Machine Learning.
- AIML students successfully completed courses offered by Simplilearn, Talentsprint, Coursera, Linkedin etc.
- Department has equipped with advanced laboratories with advanced softwares, class rooms with digital teaching resources.
- AIML faculty are upgrading their skill as per the present requirements of industry.
Undergraduate programmes offered
B.Tech.
IN COMPUTER SCIENCE AND ENGINEERING - ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (CSE - AI&ML)
Computer will overtake humans with Artificial Intelligence within the next 100 years. When that happens, we need to make sure the computers have goals aligned with ours. -Stephen Hawking
The four-year undergraduate programme, Bachelor of Technology (B.Tech.) in Computer Science and Engineering – Artificial Intelligence and Machine Learning (CSE-AI&ML) specialization will enable students to be ready for Industry 4.0 emerging and exponential technologies. CSE-AI&ML started with a sanctioned intake of 60 from the academic year 2020-2021. The Department has state of the art facilities, infrastructure and computing equipment supported by uninterrupted high-speed internet connection to fulfill the requirements of academics, supports research and learning skills to keep up with the state-of-the-art technological advances as per the industry requirement.
The department of Computer Science and Engineering has a vibrant faculty with 28 in number (5 Professors, 5 Associate Professors and 18 Assistant Professors). Faculty with their vast Industrial and Teaching experience set the standards for the quality of education for approaching years. The department is also supported by Adjunct Faculty from Industry and Academia.
Artificial Intelligence (AI) is a branch of Computer Science that focuses on creating intelligent machines that work as human beings and replicates intelligent behavior.
Example: In any scenario of online shopping, after picking up a certain product, interest/relevant products are automatically popped. There is no need for explicit rules; the system figures out the recommendations on its own. This is the power of Artificial Intelligence (AI), an intelligent system that can perform human-like tasks such as recommendations.
Machine Learning (ML), a sub area of AI, makes a machine to learn on its own without being explicitly programmed. It provides the system, an ability to automatically learn and advance from experience.
Example: Continuing the same scenario of online shopping, the system learns, to make recommendations by observing the products, purchasers are interested in. The more the system observes, the more it learns about their purchasing behaviour and provides better recommendations. The technology behind is Machine Learning.
Artificial Learning and Machine Learning (AI & ML) is an undergraduate programme with advanced learning solutions imparting knowledge of advanced innovations like machine learning, often called Deep Learning and Artificial Intelligence.
The students shall explore the practical components of developing Artificial Intelligence applications and platforms. Proficiency in Mathematics will thrive, as this Bachelors’ 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.
As all industries and organizations have adapted to Artificial Intelligence applications, currently there is and, in the future, there will be a high demand for opportunities in this field. Industries require new techniques to automate their process. There is a huge demand for professionals with AI & ML skills. Due to exponential growth in the field of Artificial Intelligence in almost every sector, the course can benefit the aspirants with high salary options and scope of growth in their career.
Few courses offered under the CSE – AI & ML specialization are:
- Intelligent systems
- AI for games
- Machine Learning
- Data Visualization
- Deep Learning
- Robotics
- Natural Language Processing
- Data Analytics, etc.
Vision
Produce competent technocrats, researchers, and entrepreneurs in Artificial Intelligence & Machine Learning to build an ecosystem that significantly contributes to the national.
Mission
M1: To impart skills through various learning methodologies and value-added courses to be technically competent.
M2: To build the research culture through participations in innovative projects and publications
M3: To inculcate ethics, leadership skills, life skills and lifelong learning
M4: To expose the students to real time environment by internships and mentorships through collaborations with industries and premier institutions.
Program Outcomes (POs)
Engineering Graduates will be able to:
- Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
- Problem analysis: Identity, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering
- 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 public health and safety, and cultural, societal, and environmental
- 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
- 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
- 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
- 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
- Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering
- Individual and teamwork: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary
- 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
- 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
- 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
Program Educational Objectives (PEOs)
PEO-1: Adapt emerging technologies to contribute to the technical innovations for the progressive development in their respective fields.
PEO-2: Productively engage in multidisciplinary research areas by applying the basic principles of engineering sciences.
PEO-3: Demonstrate strong technical skills to bring out novel designs/products to address social & environmental issues.
PEO-4: Exhibit professional attitude, teamwork and practice code of ethics
Program Specific Outcomes (PSOs)
PSO 1: Ability to apply learned skills to build optimized solutions pertaining to Computer & Communication Systems, Data Processing, and Artificial Intelligence.
PSO 2: Employ standard strategies and practices in project development using FOSS (Free & Open-Source Software).
