Gojan School of Business and Technology

GOJAN SCHOOL OF BUSINESS AND TECHNOLOGY

Approved by A.I.C.T.E. New Delhi & Affiliated to Anna University, Chennai

NAAC Accredited Institution Recognized by UGC u/s 2(f) & 12(B) of the UGC Act

80 Feet Road, Edapalayam, Redhills, Chennai – 600 052

ADMISSION OPEN FOR 2024-2025 APPLY NOW         ACADEMIC CALANDER 2024-2025         TRANSPORT DETAILS 2024

GOJAN
SCHOOL OF BUSINESS AND TECHNOLOGY

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Approved by A.I.C.T.E. New Delhi & Affiliated to Anna University, Chennai NAAC Accredited Institution Recognized by UGC u/s 2(f) & 12(B) of the UGC Act

80 Feet Road, Edapalayam, Redhills, Chennai – 600 052

ADMISSION OPEN FOR 2024-2025 CLICK HERE TO APPLY NOW

B.E-CSE(Artificial Intelligence and Machine Learning)

About the Department

The Department of Computer Science and Engineering-Artificial Intelligence and Machine Learning was established in the year 2022. The current intake students are 30 for UG Programme. UG Programmes are conducted based on the syllabus prescribed by the Anna University, Chennai. The Bachelor of Engineering (B.E.) in Computer Science and Engineering with a specialization in Artificial Intelligence and Machine Learning (AIML) at Gojan School of Business and Technology is dedicated to educating and conducting research in the fields of computer science, artificial intelligence, and machine learning. This program covers a wide range of computer science topics and provides a deeper focus on AI and machine learning concepts. The department typically has a team of experienced and well-qualified faculty members with expertise in various AI and machine learning subfields. The department usually has state-of-the-art facilities and research labs equipped with high-performance computing resources, datasets, and tools for conducting AI and machine learning experiments. Students often have access to these resources for their research and projects. 

The department is often involved in cutting-edge research in the fields of artificial intelligence and machine learning. Research areas may include Natural Language Processing (NLP), Reinforcement Learning, Deep Learning, Robotics, Data Mining, Pattern Recognition, AI Ethics and Fairness, AI for Healthcare, AI for Autonomous Systems. The Computer Science and Engineering department specializing in Artificial Intelligence and Machine Learning provides students with a strong foundation in computer science and a deep understanding of AI and machine learning. It also contributes to cutting-edge research and innovation in these exciting fields.

Vision & Mission

Vision

Mission

HOD and Faculty

Department Faculty

S.NO NAME OF FACULTY ROLE AND DESIGNATION
1
Mrs. Jaya Lakshmi A
Assistant Professor
2
Mrs. Vidhya L
Assistant Professor
3
Mrs. Shanthi R
Assistant Professor

PEOs, PSOs,POs

Program Educational Objectives (PEOs)

PEO 1: Apply their technical competence in computer science to solve real world problems, with technical and people leadership.

PEO 2: Conduct cutting edge research and develop solutions on problems of social relevance.

PEO 3: Work in a business environment, exhibiting team skills, work ethics, adaptability and lifelong learning

Program Outcomes (POs)

PO1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems

PO2: 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

PO3: 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.

PO4: 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.

PO5: 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.

PO6: 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.

PO7. 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.

PO8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.

PO9: Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.

PO10: 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.

PO11: 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.

PO12: 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 Specific Outcomes (PSOs):

PSO 1: Exhibit design and programming skills to build and automate business solutions using cutting edge technologies.

PSO 2: Strong theoretical foundation leading to excellence and excitement towards research, to provide elegant solutions to complex problems.

Course Outcomes

Gojan School Of Business And Technology Department Of Computer Science And Engineering(AIML) Course Outcomes

Third Semester

MA3354-DISCRETE MATHEMATICS

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Have knowledge of the concepts needed to test the logic of a program
CO2
Have an understanding in identifying structures on many levels.
CO3
Be aware of a class of functions which transform a finite set into another finite set which relates to input and output functions in computer science
CO4
Be aware of the counting principles
CO5
Be exposed to concepts and properties of algebraic structures such as groups, rings and fields.

CS3351-DIGITAL PRINCIPLES AND COMPUTER ORGANIZATION

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Design various combinational digital circuits using logic gates
CO2
Design sequential circuits and analyze the design procedures
CO3
State the fundamentals of computer systems and analyze the execution of an instruction.
CO4
Analyze different types of control design and identify hazards
CO5
Identify the characteristics of various memory systems and I/O communication

CS3352-FOUNDATIONS OF DATA SCIENCE

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Define the data science process
CO2
Understand different types of data description for data science process
CO3
Gain knowledge on relationships between data
CO4
Use the Python Libraries for Data Wrangling
CO5
Apply visualization Libraries in Python to interpret and explore data

CD3291-DATA STRUCTURES AND ALGORITHMS

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Explain abstract data types
CO2
Design, implement, and analyze linear data structures, such as lists, queues, and stacks, according to the needs of different applications
CO3
Design, implement, and analyze efficient tree structures to meet requirements such as searching, indexing, and sorting
CO4
Model problems as graph problems and implement efficient graph algorithms to solve them
CO5
Analyze the various searching and sorting algorithms.

CS3391-OBJECT ORIENTED PROGRAMMING

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Apply the concepts of classes and objects to solve simple problems
CO2
Develop programs using inheritance, packages and interfaces
CO3
Make use of exception handling mechanisms and multithreaded model to solve real world problems
CO4
Build Java applications with I/O packages, string classes, Collections and generics concepts
CO5
Integrate the concepts of event handling and Java FX components and controls for developing GUI based applications

CD3281-DATA STRUCTURES AND ALGORITHMS LABORATORY

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Implement ADTs as Python classes
CO2
Design, implement, and analyse linear data structures, such as lists, queues, and stacks, according to the needs of different applications
CO3
Design, implement, and analyse efficient tree structures to meet requirements such as searching, indexing, and sorting
CO4
Model problems as graph problems and implement efficient graph algorithms to solve them
CO5
Analyze the various searching and sorting algorithms

CS3381-OBJECT ORIENTED PROGRAMMING LABORATORY

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Design and develop java programs using object oriented programming concepts
CO2
Develop simple applications using object oriented concepts such as package, exceptions
CO3
Implement multithreading, and generics concepts
CO4
Create GUIs and event driven programming applications for real world problems
CO5
Implement and deploy web applications using Java

CS3361- DATA SCIENCE LABORATORY

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Make use of the python libraries for data science
CO2
Make use of the basic Statistical and Probability measures for data science.
CO3
Perform descriptive analytics on the benchmark data sets
CO4
Perform correlation and regression analytics on standard data sets
CO5
Present and interpret data using visualization packages in Python.

Fourth Semester

CS3452- THEORY OF COMPUTATION 

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Construct automata theory using Finite Automata
CO2
Write regular expressions for any pattern
CO3
Design context free grammar and Pushdown Automata
CO4
Design Turing machine for computational functions
CO5
Differentiate between decidable and undecidable problems

AL3391 -ARTIFICIAL INTELLIGENCE

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Explain intelligent agent frameworks
CO2
Apply problem solving techniques
CO3
Apply game playing and CSP techniques
CO4
Perform logical reasoning
CO5
Perform probabilistic reasoning under uncertainty

AL3451 MACHINE LEARNING

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Explain the basic concepts of machine learning
CO2
Construct supervised learning models.
CO3
Construct unsupervised learning algorithms
CO4
Evaluate and compare different models

AD3391 -DATABASE DESIGN AND MANAGEMENT

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Understand the database development life cycle and apply conceptual modeling
CO2
Apply SQL and programming in SQL to create, manipulate and query the database
CO3
Apply the conceptual-to-relational mapping and normalization to design relational database
CO4
Determine the serializability of any non-serial schedule using concurrency techniques
CO5
Apply the data model and querying in Object-relational and No-SQL databases.

AL3452 OPERATING SYSTEMS

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Analyze various scheduling algorithms and process synchronization.
CO2
Explain deadlock prevention and avoidance algorithms.
CO3
Compare and contrast various memory management schemes.
CO4
Explain the functionality of file systems, I/O systems, and Virtualization
CO5
Compare iOS and Android Operating Systems.

GE3451-ENVIRONMENTAL SCIENCES AND SUSTAINABILITY

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
To recognize and understand the functions of environment, ecosystems and biodiversity and their conservation.
CO2
To identify the causes, effects of environmental pollution and natural disasters and contribute to the preventive measures in the society.
CO3
To identify and apply the understanding of renewable and non-renewable resources and contribute to the sustainable measures to preserve them for future generations.
CO4
To recognize the different goals of sustainable development and apply them for suitable technological advancement and societal development
CO5
To demonstrate the knowledge of sustainability practices and identify green materials, energy cycles and the role of sustainable urbanization.

AD3381 DATABASE DESIGN AND MANAGEMENT LABORATORY

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Understand the database development life cycle and apply conceptual modeling
CO2
Apply SQL and programming in SQL to create, manipulate and query the database
CO3
Apply the conceptual-to-relational mapping and normalization to design relational database
CO4
Determine the serializability of any non-serial schedule using concurrency techniques
CO5
Apply the data model and querying in Object-relational and No-SQL databases

AL3411 ARTIFICIAL INTELLIGENCE & MACHINE LEARNING
LABORATORY

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Implement uninformed and informed search techniques
CO2
Build a knowledge base in Prolog and process queries to perform inference
CO3
Develop supervised learning models
CO4
Develop regression models
CO5
Compare and evaluate the performance of different models

Fifth Semester

AL3501 NATURAL LANGUAGE PROCESSING

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
tag a given text with basic Language features
CO2
implement a rule based system to tackle morphology/syntax of a language
CO3
design a tag set to be used for statistical processing for real-timeapplications.
CO4
compare and contrast the use of different statistical approaches for different types of NLP applications.
CO5
use tools to process natural language and design innovative NLP applications

AL3502 DEEP LEARNING FOR VISION

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Implement basic Image processing operations
CO2
Understand the basic concept of deep learning
CO3
Design and implement CNN and RNN and Deep generative model
CO4
Understand the role of deep learning in computer vision applications.
CO5
Design and implement Deep generative model

CB3491- CRYPTOGRAPHY AND CYBER SECURITY

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Understand the fundamentals of networks security, security architecture, threats and vulnerabilities
CO2
Apply the different cryptographic operations of symmetric cryptographic algorithms
CO3
Apply the different cryptographic operations of public key cryptography
CO4
Apply the various Authentication schemes to simulate different applications.
CO5
Understand various cyber crimes and cyber security

CS3551 DISTRIBUTED COMPUTING

COs
Course Outcome: The students, after the completion of the course, are expected to….
CO1
Explain the foundations of distributed systems.
CO2
Solve synchronization and state consistency problem.
CO3
Use resource sharing techniques in distributed systems.
CO4
Apply working model of consensus and reliability of distributed systems.
CO5
Explain the fundamentals of cloud computing.

Department Advisory Committee (DAC)

Gojan School Of Business And Technology Department Of Computer Science And Engineering (AIML)

S.NO NAME OF FACULTY ROLE AND DESIGNATION
1
Dr.C.Selvakumar
PRINCIPAL
2
Dr.G.Arunsankar
DIRECTOR -Academic Affairs
3
Mr.R.Ramadhurai
DIRECTOR – Student Affairs
4
Mr.Kannan R
Faculty Member
5
Mrs.Jaya Lakshmi A
Faculty Member
6
Mr.Ayyappan TS
Faculty Member
7
Mr.Bhagath G
Faculty Member
8
Ms.Ghayathri U
Faculty Member
9
Mrs.Krithiga N
Faculty Member
10
Mr. Maria Ratchaganathan,
Church Pastor, F/O M.Nehemiah Nesanathan – II year CSE(AIML)

Board of Studies

The composition of the Board of Studies is given below:

 

  1. The Head of the Department as Chairman.
  2. All Professor / Associate Professor / Assistant Professor of the Department.
  3. One senior professor to be co-opted by the BoS from other department nominated by the Director in consultation with Head of Department (If necessary).
  4. One subject expert (ACADEMIC) nominated by the Director on the recommendation of the Head of concerned Department.
  5. One subject expert (R&D / INDUSTRY) nominated by the Director on the recommendation of the Head of concerned Department.
    • Experts should be from Central / State Organization / R&D labs or from the Industry
  6.  In addition to the above members, One Senior Alumni (ACADEMIC / R&D / INDUSTRY) to be co-opted by the BoS nominated by the Director in consultation
    with Head of the Department. (If necessary).

(Alumni Members should be at least 5 years of experience in the relevant field).

1. The BoS shall be constituted by the department for a period of THREE years.
2. The meetings of the BoS shall be arranged at least ONCE IN A YEAR.
3. The members of the BoS will be nominated by the Director from the list recommended by the Head of the department.
4. In the absence of the Chairman (BoS), the senior member of the BoS will act as Chairman with the director’s approval.
5. The BoS shall co-opt experts in a particular field as a member of BoS with prior approval of the Director.
6. The Board of Studies shall have a power:
To prepare a detailed content of different courses of each department and submit to the Senate for approval.
Revise / update the contents of the syllabi from time to time and submit to the Senate for approval.

Laboratory

Journal And Publications

NAME TITLE JOURNAL YEAR
Mrs.A.Jaya lakshmi
A Survey on Security and Network management of SDWSN with ML Technique
2023 International Conference on Intelligent Systems for Communication, IoT and Security (ICISCoIS)
2023
Mrs.A.Jaya lakshmi
An Energy-Efficient Approach to Transfer Data from WSN to Mobile Devices
Advances in Intelligent Systems and Computing book series (AISC,volume 1432)
2023

Achievements