Department of Artificial Intelligence & Machine Learning
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Overview
Artificial Intelligence (AI) is a technology that makes the machines to reproduce human behavior. Machine Learning (ML) is a sub-part of AI by which machines automatically learn from past data without programming, meaning the machines would learn from past activities on their own. AI and ML together innovate human-like intelligent computer systems to solve complex problems.
B. Tech in CSE with Specialization in AIML ( CSE – AIML ) is to provides the budding engineers with a spectacular array of courses dedicated to frontiers in the field of Artificial Intelligence and Machine Learning (AI&ML) with a foundation of Computer Science & Engg. This course is an ideal choice for students to enhances their knowledge of computer technologies in addition to programming, coding, database and web development. The technology of Artificial Intelligence and Machine learning is at the forefront of developing intelligent solutions to real-life problems. As our technology-laden society increasingly relies on digital data, machine learning is crucial for most of our current and future applications. Engineers with AI expertise would be needed in all the crucial domains such as Healthcare, Industry 4.0, Finance, Agriculture, Security, Law, and Environment Management in the near future. This course is established to spearhead the development of globally competent engineers with AI knowledge and expertise in applying AI to challenging projects. A degree in this program is valuable and will make the student industry-relevant with apt knowledge and effectual interpersonal skills and communication skills.
This is a field changing the world in unprecedented ways, becomes in high demand, and can expect to find a wide range of exciting career opportunities upon graduation. The curriculum will focus to learn the foundations of Computational Mathematics, core areas of Computer Science, along with the latest advancements in Artificial Intelligence and Machine Learning. Core courses in Computer Science help students to drive them through the ever-changing IT requirements. The specialized areas of AI&ML are offered as minor specializations. about machine learning, deep learning, natural language processing, computer vision, data mining, special courses like Explainable AI, Generative Adversarial Networks, Multimodal AI and Regenerative AI. The students will also gain hands-on experience with tools and technologies such as Python, R, TensorFlow, Spark, Hadoop, and many more. The demand for skilled professionals in this field is growing exponentially, and there is a huge shortage of talent worldwide.
Career Prospects
With a huge explosion in data and its applications, a career in the field of AIML can be very promising as Big Data Engineer, Business Intelligence Developer, Data Scientist, Machine Learning Engineer, Research Scientist, AI Data Analyst, AI Engineer, Robotics Scientist, etc. With a specific job description on AI&ML, students have been recruited by reputed industries like Microsoft, Amazon, Goldman Sachs, Oracle GBU, Cisco, Dell Technologies, Accenture, among others. From the IT sector to healthcare, AI&ML has proven its worth. The future roles are many with AI&ML as the foundation. The graduates of the program can pursue higher education and research at premier national or international universities with a great future in research When it comes to B. Tech Artificial Intelligence and Machine Learning Salary, both the entry-level as well as high-level positions’ annual average salary of an AI and ML engineer is higher than the average salary of any other engineering graduate.
Programme
Duration:
4 years (Regular) / 3 years (Lateral Entry)
No. of Semesters:
8 (Regular) / 6 (Lateral Entry)
Intake / No. of Seats:
Total - 30 (Government - 15, Management - 15)
Eligibility:
10+2 system of Education. Must have secured a pass in Physics, Chemistry and Mathematics in the qualifying examination.
For more information Click here
Vision
To be a centre of excellence for transforming students into proficient Artificial Intelligence and Machine Learning Engineers using through sustainable practices.
Mission
M1. Impart core fundamental knowledge and necessary skills in Artificial Intelligence and Data Science through innovative teaching and learning methodology.
M2. Inculcate critical thinking, ethics, lifelong learning and creativity needed for industry and society.
M3. Cultivate the students with all-round competencies, for career, higher education and self-employability.
Programme Educational Objectives (PEOs)
PEO1. | Graduates will be prepared for analysing, designing, developing and testing the software solutions and products with creativity and sustainability |
PEO2. | Graduates will be skilled in the use of modern tools for critical problem solving and analyzing industrial and societal requirements |
PEO3. | Graduates will be prepared with managerial and leadership skills for career and starting up own firms |
Program Specific Outcomes (PSOs)
Engineering Graduates will be able to
PSO1. | Develop creative solutions by adapting emerging technologies / tools for real time applications of Industry |
PSO1. | Apply the acquired knowledge to develop software solutions and innovative mobile apps for various automation applications |
Programme Outcomes (PO)
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 Sustain ability: 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 multi disciplinary 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 multi disciplinary 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. |
Programme
Duration:
4 years (Regular) / 3 years (Lateral Entry)
No. of Semesters:
8 (Regular) / 6 (Lateral Entry)
Intake / No. of Seats:
Total - 30 (Government - 15, Management - 15)
Eligibility:
10+2 system of Education. Must have secured a pass in Physics, Chemistry and Mathematics in the qualifying examination.
For more information Click here
Faculty
Name | Qualification | Designation | Area of Specialization |
Dr. NAGASUBRAMANIAN R |
M.E.,Ph.D., | Head - PG | Computer Science Engineering |
Dr. SUBRAMANIAN P |
M.E.,Ph.D., | Head - UG | Wireless Sensor Networking and Image Processing |
Dr. PREMALATHA G |
M.E.,Ph.D., | Associate Professor | Image Processing and Machine Learning |
Mrs. SARANYA V |
M.Tech.,(Ph.D) | Assistant Professor | IOT and Cloud Computing |
Mrs. SASIKALA L |
M.E | Assistant Professor | Computer Science and Engineering |
Mrs. KIRUTHIKA S |
M.E | Assistant Professor | Computer Science and Engineering |
Mrs. ASRIN MAHMOOTHA A |
M.E | Assistant Professor | Computer Science Engineering |
Mr. PRAVEENKUMAR P |
M.E | Assistant Professor | Computer Science Engineering |
Mr. RAJAKUMAR B |
M.Tech.,(Ph.D) | Assistant Professor | IOT, AI, NLP and Image Processing |
Mr. RAJASEKAR R |
M.E.,(Ph.D) | Assistant Professor | IOT, Network Security |
Sl.No | Name of the Lab | Facility Available | Courses Offered | Virtual Link / ICT Tools | Soft copy of Lab Record |
---|---|---|---|---|---|
1 | C Programming Lab | View Details | CS8261 - C Programming | View | Download |
2 | Internet Programming Lab | View Details | CS8661 - Internet Programming | View | Download |
3 | Operating Systems Lab | View Details | CS8461 - Operating Systems | View | Download |
4 | Object Oriented Analysis and Design Lab | View Details | CS8461 - Object Oriented Analysis and Design | View | Download |
5 | Web Technology Lab | View Details | IT8511 - Web Technology | View | Download |
6 | Networks Lab | View Details | CS8581 Networks Lab | View | Download |
Academics
Anna university Syllabus
BE - 2021 Syllabus | ![]() |
Course Materials
S.No. | Subject Code | Subject Name | Lesson Plan | Question Bank | Lecture Notes | ICT Tools | |
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1 | MA3354 | Discrete Mathematics | View | View | View | View | |
2 | CS3351 | Digital Principles and Computer Organization | View | View | View | View | |
3 | AD3391 | Database Design and Management | View | View | View | View | |
4 | AD3351 | Design and Analysis of Algorithms | View | View | View | View | |
5 | AD3301 | Data Exploration and Visualization | View | View | View | View | |
6 | AL3391 | Artificial Intelligence | View | View | View | View | |
7 | AD3381 | Database Design and Management Laboratory | View | View | View | View | |
8 | AD3311 | Artificial Intelligence Laboratory | View | View | View | View | |
9 | GE3361 | Professional Development | View | View | View | View |
PLACEMENT DETAILS
NEWS & EVENTS
Student Activities
Members of Alumni Association
infrastructures
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