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

HOD

Mr.R.Kannan

Head of Department

Department of Computer Science and Engineering(AIML)

Mr.R.Kannan is the Head of the Department for the Department of Computer Science and Engineering(AIML) at Gojan School of Business and Technology. He obtained his B.E (CSE) at SCAD College of Engineering and Technology, Chennai in 2009, M.Tech (Computer Science and Engineering) at Bharath University, Chennai in 2012. He has around 8 years of academic expertise teaching a variety of computer-related disciplines. He is currently engaged in the pursuit of his Ph.D., immersing himself in in-depth research, scholarly exploration, and the advancement of expertise within his chosen academic domain. He frequently instructs students in artificial intelligence, which is his area of expertise.

Department Faculty

S.NO	NAME OF FACULTY	ROLE AND DESIGNATION
1	Mr. Kannan R	Assistant Professor/HOD
2	Ms. Karthika L	Assistant Professor
3	Mrs. Jaya Lakshmi A	Assistant Professor
4	Mrs. Divya A	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:

The Head of the Department as Chairman.
All Professor / Associate Professor / Assistant Professor of the Department.
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).
One subject expert (ACADEMIC) nominated by the Director on the recommendation of the Head of concerned Department.
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
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

The Department of Computer Science and Engineering(Artificial Intelligence and Machine Learning). These requirements can be categorized into physical infrastructure, equipment, software, and operational aspects. Invest in servers with high-performance CPUs, GPUs, and TPUs for training and running complex machine learning models. Equip workstations with powerful CPUs, GPUs, sufficient RAM, and high-quality monitors for researchers and students. Implement a scalable data storage solution, which could include Network-Attached Storage (NAS) or cloud storage for datasets and research data. Depending on research goals, you may need sensors, cameras, and other data collection devices. Install and maintain popular AI and ML software frameworks like TensorFlow, PyTorch, scikit-learn, and libraries for data analysis and visualization. Provide development environments, such as Jupyter notebooks, for coding and experimentation. Implement version control systems (e.g., Git) to manage code repositories and collaboration. Curate and maintain datasets relevant to research projects. Consider purchasing, collecting, or collaborating to obtain diverse datasets. Utilize lab management software for resource scheduling, tracking research progress, and managing equipment

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