B.Sc AI & ML

Overview of the Programme

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.

Career Opportunities

  • 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

CO, PO, PSO

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.

Curriculum Structure

RATHINAM COLLEGE OF ARTS AND SCIENCE (AUTONOMOUS)

Scheme of curriculum for B.Sc. Artificial Intelligence and Machine Learning

for the students admitted in the Batch during 2024 – 2025

Board of Studies – Computer Science (UG)

 

S.No.

Sem

Part

Sub Type

Sub Code

Subject

Credit

Hours

INT

EXT

Total

1

1

1

L1

  

Language – I

4

4

50

50

100

2

1

2

L2

  

English for Communication – I

4

4

50

50

100

3

1

3

Core

  

Core  – I – Problem Solving techniques using C

4

4

50

50

100

4

1

3

Core Practical

  

Core – I Practical – C  Programming Lab

2

4

20

30

50

5

1

3

DSC

DSC

DSC 1

4

4

50

50

100

6

1

3

DSC Practical

  

DSC Practical – 1

2

4

20

30

50

7

1

3

Allied-I

DSA

DSA 1A

4

4

50

50

100

8

1

4

AEC

  

Ability Enhancement Course I

2

2

50

  

50

9

1

6

VAC

  

Value Added Course – I%

2

–

50

  

50
           

28

30

      

1

2

1

L1

  

Language – II

4

4

50

50

100

2

2

2

L2

  

English for Communication – II

4

4

50

50

100

3

2

3

Core

  

Core  – II – Python Programming

4

4

50

50

100

4

2

3

Core Practical

  

Core Practical II – Python Programming Lab

2

4

20

30

50

5

2

3

DSC

DSC

DSC 2C

4

4

50

50

100

6

2

3

DSC Practical

  

DSC Practical – 2C

2

4

20

30

50

7

2

3

Allied-II

DSA

DSA 2A

4

4

50

50

100

8

2

4

AEC

  

Ability Enhancement Course II

2

2

50

  

50

9

2

6

VAC

  

Value Added Course – II %

2

–

50

  

50
           

28

30

      

1

3

3

Core

  

Core III – Java Programming

4

5

50

50

100

2

3

3

Core Practical

  

Core Practical III –  Java Programming Lab

2

4

20

30

50

3

3

3

DSC

  

DSC 3C

4

5

50

50

100

4

3

3

DSC Practical

  

DSC Practical – 3C

2

4

20

30

50

5

3

3

Allied-III

DSA

DSA 3A

4

5

50

50

100

6

3

4

SEC

SEC-I

Skill Enhancement Courses – I

2

5

20

30

50

7

3

4

AEC

  

Ability Enhancement Course III

2

2

50

  

50

8

3

6

VAC

  

Value Added Course – III %

2

–

50

  

50

9

3

6

IDL

  

Inter Department Learning – I#

2

–

50

  

50
           

24

30

      

1

4

3

Core

  

Core IV – Natural Language Processing

4

5

50

50

100

2

4

3

Core Practical

  

Core Practical IV –  Natural Language Processing Lab

2

4

20

30

50

3

4

3

DSC

DSC

DSC 4C

4

5

50

50

100

4

4

3

DSC Practical

  

DSC Practical – 4C

2

4

20

30

50

5

4

3

Allied-IV

DSA

DSA 4A

4

5

50

50

100

6

4

4

SEC

SEC-II

Skill Enhancement Courses – II

2

5

20

30

50

7

4

4

AEC

  

Ability Enhancement Course IV

2

2

50

  

50

8

4

6

VAC

  

Value Added Course – IV %

2

–

50

  

50

9

4

6

IDL

  

Inter Department Learning – II#

2

–

50

  

50
           

24

30

      

1

5

3

Core

  

Core V – Machine Learning techniques

4

4

50

50

100

2

5

3

Core Practical

  

Core Practical V  – Machine Learning Lab

2

4

20

30

50

3

5

3

DSC

DSC

DSC 5C

4

4

50

50

100

4

5

3

DSC Practical

  

DSC Practical – 5C

2

4

20

30

50

5

5

3

DSE

DSE – I

Elective  – I – DSE 1E

4

5

50

50

100

6

5

3

DSE

DSE – II

Elective  – II – DSE 2E

4

5

50

50

100

7

5

4

SEC

SEC-III

Skill Enhancement Courses – III

2

4

20

30

50

8

5

6

VAC

  

Value Added Course – V%

2

–

50

  

50
           

24

30

      

1

6

3

Core

  

Core VI –  Big Data Analytics

4

6

50

50

100

2

6

3

Core Practical

  

Core Practical VI  –  Big Data Analytics using SCALA Lab

2

4

20

30

50

3

6

3

DSE

DSE – III

Elective – III – DSE 3E

4

6

40

60

100

4

6

3

DSE

DSE – IV

Elective – IV – DSE 4E

4

6

50

50

100

5

6

3

Core Course – XI

DSC

Core Project

8

4

80

120

200

6

6

4

SEC

SEC-IV

Skill Enhancement Courses – IV

2

4

20

30

50

7

6

5

EX

  

Extension Activity- EX %

2

–

50

  

50
           

26

30

1900

1950

3850
         

Total credit

154

        

Note :

@   –     No End Semester Examination, only Internal Exam.

#    –     No Internal Examination, only End Semester Exam.

Discipline Specific Core

S.No

Course Code

Course

Pre-request

Offering Department

Mandatory

1

 

Data Structures

–

Computer Science

Yes

2

 

Operating System

–

Computer Application

Yes

3

 

Deep Learning

–

BCA

 

4

 

Artificial Intelligence and Knowledge Representation

–

  

 Yes

5

 

Software Engineering

–

  

 

6

 

Data Mining and warehouse

–

 

 

7

 

Ethical Hacking

–

Computer Science

Yes

8

 

Robotic Process Automation

–

 

Yes 

9

 

Data Structures Lab

DSC 1C S.NO1

Computer Science

 

10

 

Operating System Lab

DSC 1C S.NO2

Computer Application

 

11

 

Data Mining and warehouse Lab

DSC 1C S.NO3

BCA

 

12

 

Artificial Intelligence Lab

DSC 1C S.NO4

  

 

13

 

Software Engineering Lab

DSC 1C S.NO5

  

 
   

Data Mining Lab

DSC 1C S.NO6

 

  

16

 

Ethical Hacking Lab

DSC 1C S.NO8

Computer Science

 

17

  

Robotic Process Automation Lab

DSC 1C S.NO9

 

  

18

 

Professional Skills Lab

 

 

 

Allied

S.No

Course Code

Course

Pre-request

Offering Department

Mandatory

1

 

Mathematics for Computer Science

–

Maths

 

2

 

Statistics of computer science

–

Maths

Yes

3

 

Entrepreneurial Development

–

Commerce

 

4

 

Bayesian statistics

–

Maths

Yes

Skill Based Subject

S.No

Course Code

Course

Pre-request

Offering Department

Mandatory

1

  

Linux & Shell Programming

–

Computer Science

  

2

  

Predictive analysis of R Programming

–

Computer Technology

Yes

3

  

Internet Of Things

–

Information Technology

Yes

4

  

Information Security & Cyber Law

–

Computer Science

Yes

5

  

Wireless sensor network

–

Information Technology

  

6

  

Signal Processing

–

Computer Science

  

7

  

Programming with scala

–

Information Technology

  

8

  

Capstone Project Work (Based on AI & Machine Learning)

  

Information Technology

  

Discipline Specific Elective

S.No

Course Code

Course

Pre-request

Offering Department

Mandatory

1

  

Business Data Analytics

–

–

  

2

  

Social Network Analysis

–

–

  

3

  

Software Agents

–

–

  

4

  

Artificial Neural Networks and Fuzzy System

–

–

  

5

  

Web Application Security

–

–

  

6

  

Embedded Systems

–

–

  

7

  

Principles of Secure Coding

–

–

  

8

  

Open source software

–

–

  

Ability Enhancement Course

S.No

Course Code

Course

Pre-request

Offering Department

Mandatory

1

 

Environmental Studies

–

General

Yes

2

 

Women Studies

–

Commerce II

 

3

 

Constitution of India

–

Commerce I

 

4

 

Human Rights

–

General

Yes

5

 

Yoga

–

Tamil

 

6

 

NCC

–

Viscom

 

7

 

Communicative English

–

English

 

8

 

Quantitative Apptitude

–

Mathematics

 
           

Value Added Course

 

S.No

Course Code

Course

Pre-request

Offering Department

Mandatory

 

1

 

Fundamental of Office Automation

–

  

Yes

 

2

 

Advance Excel

–

  

 

 

3

 

Fundamental of Multimedia -I

–

  

 

 

4

 

Fundamental of Multimedia -II

–

  

Yes

 

5

 

Video Editing

–

  

 

 

6

 

Fundamental of Visual Effects

–