The Department of Artificial Intelligence and Machine learning is established in the year 2024-2025. The Department offers B.Sc. Artificial Intelligence and Machine Learning Programme under the Faculty of Computer Science. Artificial Intelligence, in the modern era, has become the driving force in almost all the domains. It has become the core necessity for most of the companies around   the World and is being widely used by most of them. So, B.Sc. Artificial Intelligence & Machine Learning in the present times, is the right option that promises a voluminous scope.

The Department is committed to import rigorous training to students to generate knowledge through the state of the art concepts and technologies in AI/ML, and to transform the Department as a Centre of Excellence in imparting AI/ML education and research. The curriculum is designed as a convenient learning path for any novice learner to attain expertise in the domain. The department guides the students to unleash their potential towards endless opportunities in industry and research globally.

  • Machine Learning Engineer
  • Data Scientist
  • NLP Scientist
  • Business Intelligence Developer
  • Human -Centered Machine Learning Developer
  • Research Scientist
  • Machine Learning Developer
  • Data Engineer
  • Business Intelligence Analyst
  • Artificial Intelligence Engineer
  • Computer Vision Engineer

Program Educational Objectives (PEO):

  • PEO1: Become successful, qualified, innovative, and productive in fulfilling the needs of the Industry, Government, and Commerce.
  • PEO2: Capability to continue formal education and successfully complete an advanced degree.
  • PEO3: Grow professionally with the knowledge acquired and apply the skills throughout the career.
  • PEO4: Contribute to the growth of the nation and society by applying the acquired knowledge in technical, computing, and managerial skills.
  • PEO5: Establish interpersonal skills, leadership ability, and team building to achieve organization goals and serve society with professional ethics and integrity.

Program Outcomes (PO):

  • PO1 : Develop knowledge in the field of cyber security courses necessary to qualify for the degree.
  • PO2 : Apply the knowledge of financial accounting career skills, applying both quantitative and qualitative knowledge to their future careers in business.
  • PO3 : Develop the ability to analyses the accounting concepts, principles, and frameworks to communicate effectively to stakeholders.
  • PO4 ; Use research-based knowledge including design tools, analysis and interpretation of data, and synthesis of the information to provide applicable conclusions.
  • PO5 :  Apply ethical principles and commit to professional ethics, responsibilities, and norms the accounting practices.
  • PO6 :  Incorporate the leadership and problem-solving skills to lead the organizations they join or to initiate their own ventures.
  • PO7 ;  Function effectively as an individual, and a member or leader in diverse teams, and in multidisciplinary settings.
  • PO8 :  Update the skill sets in a challenging world in equipping themselves to maintain their competence and in implementing global business practices
  • PO9 :  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 Specific Outcomes (PSO):

  • PSO1 :  Gain knowledge and skills in various commercial aspects, computer application courses and its recent trends.
  • PSO2 :  Adopt critical thinking and problem-solving skills effectively in the business world.
  • PSO3 : Improve their leading role in the community, enabling him or her to take responsibilities and contribute to solving problems through innovative thinking, collective work, reflection, and self-development
  • PSO4 : Become ethically and socially responsible commerce graduates with computer application knowledge.

S.No. Sem Part Sub Type Course
Code
Course Name Credit Hours INT EXT Total
1 1 1 L1   Language – I 3 5 50 50 100
2 1 2 L2   English – I 3 5 50 50 100
3 1 3 Core    Core  Course – I Theory Problem Solving Techniques Using C 4 5 50 50 100
4 1 3 Core     Core Course – II Theory / Practical Problem Solving Techniques Using C 4 4 50 50 100
5 1 3 Allied   Allied-I Mathematics for Computer Science 4 5 50 50 100
6 1 4 SEC   Skill Enhancement Courses – I Database Management System / Practical – Database Management system Lab 4 4 50 50 100
7 1 4 AEC   Ability Enhancement Course I Environmental Studies or Universal Human Values & Professional Ethics 2 2 50 0 50
            24 30 350 300 650
                     
1 2 1 L1   Language – II 3 5 50 50 100
2 2 2 L2   English – II 3 5 50 50 100
3 2 3 Core    Core  Course – V Theory Python Programming 4 5 50 50 100
4 2 3 Core     Core  Course – VI Theor y / Practical Python Programming Lab 4 4 50 50 100
5 2 3 Elective   Elective  – I Entrepreneurship Development 4 4 50 50 100
6 2 3 Allied   Allied-II Numerical Methods 4 5 50 50 100
7 2 4 AEC   Ability Enhancement Course II Design Thinking 2 2 50 0 50
8 2 5 Ext   Extension Activity – I (NASA) 1 0 25 0 25
            25 30 375 300 675
                     
1 3 1 L1   Language – III 3 4 50 50 100
2 3 2 L2   English – III 3 4 50 50 100
3 3 3 Core    Core  Course – V Theory Artificial Intelligence 4 6 50 50 100
4 3 3 Core     Core  Course – VI Theory / Practical Artificial Intelligence Lab 4 4 50 50 100
5 3 3 Allied   Allied-III Statistics for Machine Learning 4 5 50 50 100
6 3 4 SEC   Skill Enhancement Courses – II Practical / Training 
Mobile Application Development
4 5 50 50 100
7 3 4 AEC   Ability Enhancement Course III Soft Skill-1 2 2 50 0 50
8 3 3 ITR   Internship / Industrial Training (Summer vacation at the end of II semester activity) 2 0 50 0 50
9 3 5 Ext   Extension Activity – II (NASA) 1 0 25 0 25
            27 30 425 300 725
                     
1 4 1 L1   Language – IV 3 4 50 50 100
2 4 2 L2   English – IV 3 4 50 50 100
3 4 3 Core    Core  Course – VII Theory Machine Learning 4 6 50 50 100
4 4 3 Core     Core  Course – VIII Theory / Practical Machine Learning Lab 4 4 50 50 100
5 4 3 Allied   Allied-IV Discrete Mathematics 4 5 50 50 100
8 4 3 Elective    Elective  – II 
Web Mining
Deep Learning
Cloud Computing
4 5 50 50 100
7 4 4 AEC   Ability Enhancement Course IV Soft Skill-2 2 2 50 0 50
8 4 5 Ext   Extension Activity – III (NASA) 1 0 25 0 25
            25 30 375 300 675
                     
1 5 3 Core    Core  Course – IX Theory Robotic Process Automation 4 6 50 50 100
2 5 3 Core     Core  Course – X Theory / Practical Robotics Lab 4 6 50 50 100
3 5 3 Elective    Elective  – III 
Data Mining using R
Network Security and Cryptgraphy
Design and Analysis of Algorithms
4 6 50 50 100
  5 3 PRJ   Project 0 6 0 0 0
4 5 4 SEC   Skill Enhancement Courses – III Practical / Training 
Embedded Systems and IoT
4 6 50 50 100
5 5 3 ITR   Internship / Industrial Training (Summer vacation at the end of IV semester activity) 2 0 50 0 50
6 5 5 Ext   Extension Activity – IV (NASA) 1 0 25 0 25
            19 30 275 200 475
                     
1 6 3 Core    Core  Course – XI Theory Natural Language Processing 4 6 50 50 100
2 6 3 Core     Core  Course – XII Theory / Practical Natural Language Processing Lab 4 4 50 50 100
3 6 3 Elective    Elective – IV
Fuzzy Logic and Neural Networks
Digital Image Processing
Human Computer Interaction
4 6 50 50 100
4 6 3 PRJ   Core Project 8 8 100 100 200
5 6 4 SEC   Skill Enhancement Courses – IV Practical / Training 
Web Technology 
4 6 50 50 100
            24 30 300 300 600
          Total credit 144 180 2100 1700 3800

 

Additional Credits
S.No. Sem Part Sub Type Sub Code Subject Credit Hours INT EXT Total
1 2 6 VAC   VAC – Microsoft CoE Course  2 2 50 0 50
2 3 6 VAC   Inter Department Course 2 2 50 0 50
3 4 6 IDC   VAC – Microsoft CoE Course 2 2 50 0 50
4 5 6 VAC   VAC – Microsoft CoE Course 2 2 50 0 50