COMPUTER ENGINEERING (ARTIFICIAL INTELLIGENCE - BTECH)
Overview
Low error probability: Since human capabilities have their limitations, using AI will help reduce the risks of errors to a great extent. It will also increase the accuracy of results obtained, making it a much more efficient choice.
Overcomes limitations: There are some applications such as mining exploration and ocean exploration where human intervention has its limitations. In such a scenario, you can use AI to get the job done in no time at all.
Studying artificial intelligence opens a world of opportunities. In the field of artificial intelligence, the opportunities are truly endless. Learning in the artificial intelligence field could help you to perform complex tasks that are otherwise hard to perform. It uses various concepts of Neural Networks, Image Processing, Natural Language Processing, etc. Marwadi University is the first in the region to offer UG specialization in the Artificial Intelligence domain. 
Educational
Objectives
To give a brief of artificial intelligence (AI) concepts and approachesTo build up a basic understanding of the building blocks of AI as presented in terms of intelligent agents, Search, Knowledge representation, inference, logic, and learningTo learn Classification Algorithms, Neural Networks, Image Processing, Deep Learning, NLP ModelsTo enable students to be creative in addressing and solving scientific and technological problems through research in Artificial Intelligence.To fulfill these objectives MARWADI UNIVERSITY – the Best Computer Engineering-AI College in Rajkot has well-equipped labs with state-of-the-art infrastructure, digital workstations with the latest configurations and required software. Structures Lab, C Programming Lab, Internet Lab, Computer Networking Lab, Project Lab are some of the key places that impart practical knowledge and technical skill to the students. The Computer Engineering-AI department has a highly qualified and experienced pool of faculty members who are ready to support students in their development in all dimensions.
Eligibility Criteria
| For Indian and International Students | ||
|---|---|---|
| 12th (HSc) in Science with a minimum of 45%. They should have appeared in GUJCET and should be registered under ACPC. Equivalent Qualification is required for international students |
Admission Process
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Fee structure
| For Indian Student (INR) | ||
|---|---|---|
| Computer Engineering (Artificial Intelligence) | 4 Years | 62500/- (Per Sem) |
| For International Student (USD) | ||
|---|---|---|
| Computer Engineering (Artificial Intelligence) | 4 Years | 1800/- (Annual) |
Curriculum
| B. Tech. Year I, Sem I | Evaluation Scheme | |||||||||||
| Subject Code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | |||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term Work (TW) | |||||
| 01MA0106 | Calculus | BS-UC | 4 | 2 | 0 | 5 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01EE1101 | Basics of Electrical & Electronics Engineering | ES-UC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01CE1101 | Computer Programming | ES-UC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01GS1101 | Engineering Physics | GN-UE | 2 | 0 | 0 | 2 | 0 | 30 | 20 | 25 | 25 | 100 |
| 01CR1103 | Value Education | ES-UC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01CE1102 | Computer Workshop | GN-UC | 2 | 0 | 0 | 2 | 0 | 0 | 0 | 50 | 50 | 100 |
| 01GS0103 | Indian constitution | ES-UC | 0 | 0 | 2 | 1 | 0 | 0 | 0 | 25 | 25 | 50 |
| 01CR0105 | Verbal Ability – 1 | NCC | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| Total | 29 | 17 | 2 | 10 | 22 | 200 | 150 | 100 | 200 | 200 | 850 | |
| B. Tech. Year I, Sem II | Evaluation Scheme | |||||||||||
| Subject Code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | |||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term work (TW) | |||||
| 01MA0104 | Linear Algebra | BSC | 3 | 2 | 0 | 5 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01CE0104 | Object Oriented Programming | PCC | 2 | 0 | 4 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01ME1103 | Engineering Drawings | ESC | 2 | 0 | 4 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01EC0102 | Digital Electronics | ESC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01SL0102 / 01SL0103 | Reading and Writing for Technology / Speaking and Presentation Skills | HSMC | 2 | 0 | 0 | 2 | 0 | 30 | 20 | 25 | 25 | 100 |
| 01EN1101 | Basics of Environmental Studies | MC | 2 | 0 | 0 | 0 | 50 | 30 | 20 | 0 | 0 | 100 |
| 01CR0104 | Professional Ethics | MC | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 50 | 50 | 100 |
| 01CR0106 | Verbal Ability – 2 | MC | 1 | 0 | 0 | 0 | 50 | 0 | 0 | 0 | 50 | 100 |
| Total | 16 | 2 | 10 | 19 | 300 | 180 | 120 | 175 | 225 | 1000 | ||
| NCC-2 • 3 hrs. NCC work will be for students who opt for NCC • 2 extra credits for NCC course will be given to the students who opt this subject | ||||||||||||
| B. Tech. Year II, Sem III | Evaluation Scheme | |||||||||||
| Subject Code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial / Practical Marks | Total Marks | |||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term Work (TW) | |||||
| 01AI1301 | Probability and Statistics | BSC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01CE1301 | Data Structure | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01CE2302 | Database Management System | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01IT0301 | Data Communication and Networking | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01AI0302 | Programming with Python | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01CE1304 | Design Thinking and Problem Solving Skills | MC | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 25 | 25 | 50 |
| Total | 15 | 0 | 12 | 20 | 250 | 150 | 100 | 150 | 150 | 800 | ||
| Proactive Programming Technique | MC | 36 hours during the semester | 0 | |||||||||
| NCC • 3 hrs. NCC work will be for students who opt for NCC • 2 extra credits for NCC course will be given to the students who opt this subject | ||||||||||||
| B. Tech. Year II, Sem IV | Evaluation Scheme | |||||||||||
| Subject Code | Subject Name | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | ||||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term work (TW) | |||||
| 01AI0402 | Discrete Mathematical Structures | BSC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01IT0402 | Operating System & Virtualization | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01IT1401 | Computer Network | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01AI0401 | Java Programming | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01CE0406 | Machine Learning Essentials | PCC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01CE0408 | Creativity, Problem Solving and Innovation | MC | 0 | 0 | 2 | 1 | 0 | 30 | 0 | 20 | 0 | 50 |
| Total | 15 | 0 | 12 | 21 | 250 | 180 | 100 | 145 | 125 | 800 | ||
| Proactive Programming Technique | MC | 36 hours during the semester | 0 | |||||||||
| NCC • 3 hrs. NCC work will be for students who opt for NCC • 2 extra credits for NCC course will be given to the students who opt this subject | ||||||||||||
| B. Tech. Year III, Sem V | Evaluation Scheme | |||||||||||
| Subject Code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | |||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term Work (TW) | |||||
| 01CE0504 | Theory of Automata & Formal Language- | PC | 3 | 0 | 0 | 3 | 50 | 30 | 20 | 0 | 0 | 100 |
| 01AI0501 | Advanced Java Programming | LC-CE | 0 | 0 | 4 | 2 | 50 | 0 | 0 | 25 | 25 | 100 |
| 01AI0502 | Artificial Intelligence | PC | 3 | 0 | 2 | 5 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01CE0503 | Design and Analysis of Algorithms | PC | 4 | 0 | 2 | 5 | 50 | 30 | 20 | 25 | 25 | 150 |
| Department Elective-2 | PEC | 4 | 0 | 2 | 5 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01AI0503 | Cloud Computing | LC-CE | 0 | 0 | 4 | 2 | 50 | 0 | 0 | 25 | 25 | 100 |
| 01CE0508 | Reverse Engineering | EE | 0 | 0 | 2 | 1 | 0 | 0 | 0 | 25 | 25 | 50 |
| Course Enrollment Udemy/Udacity etc | EE | 4 | X | |||||||||
| Total | 30 | 14 | 0 | 16 | 27 | 300 | 120 | 80 | 150 | 150 | 800 | |
| Department Elective – 2 1) 01AI0504 – Digital Image Processing 2) 01IT0503– Advanced Computer Network 3) 01CE0604 – Cyber Security | ||||||||||||
| B. Tech. Year III, Sem VI | Evaluation Scheme | |||||||||||
| Subject Code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | |||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term Work (TW) | |||||
| 01AI0601 | Human Computer Interface | PC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01IT0601 | Software Engineering | PC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01AI0602 | Web Intelligence and Mining | PC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01AI0603 | Machine Learning Techniques | PC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01CR0601 | Business Benchmark | UC | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 50 | 50 | 100 |
| 01AI06XX | Department Elective – 3 | PEC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 |
| 01AI0606 | Mathematics for Data Science | BS-UC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 0 | 0 | 100 |
| Total | 31 | 19 | 0 | 12 | 25 | 250 | 150 | 100 | 175 | 175 | 950 | |
| Department Elective – 3 1)Block Chains-01AI0604 2)System and Network Security-01AI0605 | ||||||||||||
| B. Tech. Year IV, Sem VII | Evaluation Scheme | ||||||||||||
| Subject Code | Subject Name | Category | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | ||||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term Work (TW) | ||||||
| 01AI0701 | Deep Learning | PC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01AI0706 | Compiler Design | PC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01AI0702 | Natural Language Processing | PC | 3 | 0 | 2 | 4 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01CE0XXX | Department Elective – 4 | PEC | 4 | 0 | 2 | 5 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01AI0XXX | Department Elective – 5 | PEC | 4 | 0 | 2 | 5 | 50 | 30 | 20 | 25 | 25 | 150 | |
| 01IT1703 | Major Project-I | EE | 0 | 0 | 8 | 4 | 0 | 0 | 0 | 50 | 50 | 100 | |
| NPTEL/SWAYAM course Enrollment/MOOC/Udemy etc | EE | 0 | 0 | 0 | 0 | 0 | 0 | X | |||||
| Total | 35 | 17 | 0 | 18 | 26 | 250 | 150 | 100 | 175 | 175 | 850 | ||
| Department Elective – 4 1. Android Programming (01CE0704) 2. Mobile Computing (01CE0701) 3. Business Intelligence (01CE0805) | Department Elective – 5 1. Internet Of things (01CE0806) 2. Computer Vision (01AI0703) 3. Virtual and Augmented Reality (01AI0704) | ||||||||||||
| B. Tech. Year IV, Sem VIII | Evaluation Scheme | ||||||||||||
| Subject Code | Subject Name | Teaching Scheme (Hours) | Credits | Theory Marks | Tutorial/ Practical Marks | Total Marks | |||||||
| Theory | Tutorial | Practical | ESE(E) | IA | CSE | Viva (V) | Term work (TW) | ||||||
| 01IT0801 | Industrial Internship/Major Project-II | PC | 0 | 0 | 18 | 9 | 0 | 0 | 0 | 200 | 200 | 400 | |
| Total | 18 | 0 | 0 | 18 | 9 | 0 | 0 | 0 | 0 | 0 | 400 | ||
Elective Courses
| Serial No. | Course name |
| 1 | Machine Learning Essentials |
| 2 | Advanced Computer Network |
| 3 | Digital Image Processing |
| 4 | Cyber Security |
| 5 | Block Chain |
| 6 | System and Network Security |
| 7 | Android Programming |
| 8 | Mobile Computing |
| 9 | Business Intelligence |
| 10 | Internet Of things |
| 11 | Computer Vision |
| 12 | Virtual and Augmented Reality |
Core Courses
| Serial No. | Course name |
Career Opportunities
Private and Public organizations Education, both primary and advanced Advanced Healthcare facilities Government agencies Government Committees related to Research Military Software Engineers, Developers, and AnalystsResearch ScientistsManufacturing and Maintenance EngineersMechanical EngineersGame Programmers, Developers and Algorithm SpecialistsComputer EngineersElectrical EngineersSurgical TechniciansComputational PhilosopherRobot Personality DesignerRobot Obedience TrainerAutonomous Vehicle Infrastructure Designer
Career Options
Software Engineers, Developers, and Analysts
Research Scientists
Manufacturing and Maintenance Engineers
Mechanical Engineers
Game Programmers, Developers and Algorithm Specialists
Computer Engineers
Electrical Engineers
Surgical Technicians
Computational Philosopher
Robot Personality Designer
Robot Obedience Trainer
Autonomous Vehicle Infrastructure Designer
Student Outcomes
Today’s demand for expertise in Artificial Intelligence and Machine Learning far exceeds the supply, and this imbalance will become more critical over the coming few years. So this programme provides an opportunity to bridge this gap of demand and supply of technocrats in AI. The average salaries of AI professionals in India across industries are quite attractive.
To understand what constitutes “Artificial” Intelligence and how to recognize systems with Artificial Intelligence. To study various AI and Machine Learning algorithms To apply knowledge representation, reasoning, and Machine Learning techniques to solve real-life problems To implement traditional Artificial Intelligence and Machine Learning techniques. To demonstrate practical experience by implementing and experimenting with the learned algorithms
Career Opportunities, Placement, Packages, Alumni
The scope of AI is pretty significant as the ultimate aim is to create computer programs that can tackle different problems and provide goal-oriented solutions efficiently. Thus, there is a scope for computer vision, game development, speech recognition, robotics, and language detection.Private and Public organizationsEducation, both primary and advancedAdvanced Healthcare facilitiesGovernment agencies and committees related to researchMilitary.
Key Highlight
We were the first college to introduce this Vertical ( CE-AI)in this region. Experienced Faculties, Industry Connects, Foreign Exchange Programmes.
Facilities
Lab
Oracle LabJetson Nano TechnologyCISCO LabIBM LabResearch & Development LabBasic Computing LabRobotics LabComputing LabNetworking LabData Processing LabObject-Oriented Programming LabHigh-Performance Computing LabSoftware Engineering LabProject Lab 
Library
There are two main libraries which make up the MU Learning Resource Centre. Specialist collections, use of up-to-date technology, and a team of enthusiastic and dedicated staff all combined to form a library which serves the Users of the Marwadi Education as well as contributes towards the research needs of the Institution, and is one of the best ICT-equipped academic libraries in the region.
Fully equipped with RFID (Radio Frequency Identification Device) Technology
Specially devised and designed Self KIOSK for Self Check in & Check out
E-Resource Lab having 60+ computer systems with latest configuration to assist for online research and resources
Specially devised and designed Mobile Application having features of; Intimation, Alerts, History, Account Status and Books search facilities
Connected with other libraries and resource centers to retrieve information resources worldwide Separate Study rooms and discussion rooms
Additional Transportation facility for special Late Evening & Sunday for Library users
More than 50000 books in the library
Scholarship
Campus Facilities
Impressive Infrastructure IT Enabled Infrastructure Sports Infrastructure State-of-the-art Classrooms Hostels with Gymnasium Library with 50000+ Books Academic & Cultural Events
HOD's Message
Dr Madhu Shukla
HoD, Department of Computer Engineering – Artificial Intelligence
In the world of tomorrow, human and artificial intelligence will come together to hopefully augment the life of every human being. From self-driving cars to housekeeping robots, life is being made simpler and better by automating cheaper cognitive tasks due to the advances in the field of AI.
Also, for much more cognitively complex tasks such as medical diagnosis or financial analysis, AI-aided systems help people get more accurate results in less time than a non-AI system would have afforded. Instead of worrying that AI will take their jobs, people should be getting excited that they will soon be able to do their jobs through intelligent systems or in collaboration with intelligent agents. The collaboration between humans and AI should help reduce each other’s errors, ushering in a new era of work. Augmenting human intelligence, especially creativity and decision-making with the help of automated systems presents a completely new way of living life itself.
Come. Join and Discover the hidden potential.
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Awards & Recognition
Nurturing Bright Students- Training for Outstanding students in Trending Domains Technical Workshops MU Fest. Internships (Full / Part time) (Online/Offline)
https://ieeexplore.ieee.org/document/9730646
https://www.analyticsvidhya.com/blog/2021/06/the-challenge-of-vanishing-exploding-gradients-in-deep-neural-networks/
https://www.analyticsvidhya.com/blog/author/harsh_dhamecha/
https://www.analyticsvidhya.com/blog/2021/08/how-to-perform-exploratory-data-analysis-a-guide-for-beginners/
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