COMPUTER SCIENCE & ENGINEERING (ARTIFICIAL INTELLIGENCE)

Course Duration: 4 Years | Semesters: 8 |

Program overview

The Computer Science & Engineering (Artificial Intelligence) program is designed to equip students with the knowledge and skills to develop intelligent systems capable of mimicking human cognitive functions.

Key Program Highlights:

  • Solid Foundation in Computer Science: Gain a strong understanding of core computer science concepts like algorithms, data structures, programming languages, software engineering, and computer architecture.
  • In-Depth Exploration of AI & ML: Dive deep into the fascinating world of AI and ML, learning techniques for developing intelligent agents, building and training machine learning models, and applying deep learning architectures.
  • Emphasis on Practical Applications: The program focuses on practical applications of AI and ML. You'll gain hands-on experience through coursework, projects, and potential internships, working on real-world problems in areas like computer vision, natural language processing, robotics, and intelligent systems.
  • Development of Essential Skills: Sharpen your critical thinking, problem-solving, analytical, research skills, effective communication, teamwork, and ethical considerations in the development and deployment of AI solutions.
  • Preparation for Rewarding Careers: This program equips you with the skills and knowledge sought after by leading companies and research institutions in the rapidly growing field of AI.

Benefits of the Program:

  • Industry-Relevant Curriculum: Stay ahead of the curve with a curriculum that keeps pace with the latest advancements in AI and ML.
  • Faculty Expertise: Learn from professors who are passionate about AI and actively involved in cutting-edge research.
  • Project-Based Learning: Develop your practical skills through hands-on projects that tackle real-world AI challenges.
  • Career Opportunities: can pursue careers in a wide range of fields including machine learning engineering, data science, natural language processing, robotics, and AI research and development

Dr. Rajashree V Biradar

Prof. & HOD

Department of CSE - Artificial Intelligence

As the Head of the Computer Science & Engineering (Artificial Intelligence) department, I want to extend my warmest greetings to all students enrolled in our program. Our department stands at the forefront of innovation, where we explore the ever-expanding frontiers of Artificial Intelligence (AI) and its applications in diverse fields.

CSE (Artificial Intelligence) department is stared in the academic year 2022-23 with the intake of 60. Subsequently in the academic year 2023-24, the intake has been increased to 120.Here at BITM, we offer a rigorous curriculum that blends the fundamentals of computer science with cutting-edge AI and Machine Learning (ML) techniques. You'll gain hands-on experience through coursework, projects, and potential internships, tackling real-world problems in areas like computer vision, natural language processing, robotics, and intelligent systems.

AI is not just a subject of study; it's a powerful tool that has the potential to revolutionize industries, improve lives, and solve some of the world's most pressing challenges. In our program, we strive to provide you with a comprehensive education that combines theoretical foundations with hands-on experience, enabling you to become proficient in the development and deployment of AI systems.

Our dedicated faculty consists of passionate researchers and industry experts who are committed to fostering your intellectual growth. They will guide you in developing the critical thinking, problem-solving, analytical, and research skills essential for success in AI. We also emphasize ethical considerations in AI development, ensuring you become responsible innovators who shape technology for a positive impact.

Finally, I want to remind you that your education extends beyond the classroom. Take advantage of research opportunities, internships, and extracurricular activities to deepen your understanding and broaden your skills. Collaborate with your peers, engage with faculty mentors, and immerse yourself in the vibrant community of AI enthusiasts.

Welcome again, and let's embark on this incredible exploration of Artificial Intelligence together!

VISION AND MISSION OF THE DEPARTMENT

Vision:

To contribute AI experts for global industries and organizations, fostering innovation while upholding social responsibility and ethical practices.


Mission:

  • To nurture student with cutting-edge expertise through project based learning approaches.
  • To foster industry-relevant design and development skills.
  • To promote a culture of innovation and leadership skills while emphasizing ethical principles.

 

PEO-1: To harvest proficient AI professionals, contributing to major technological advancements and solutions in renowned companies or research institutions.

PEO-2: To exhibit professionalism through ethical innovation and leadership skills while encouraging interdisciplinary collaborations to address societal challenges.

PEO-3: To develop the ability to launch thriving AI based start-ups, and businesses across the world.

Program outcomes (POs)

PO1Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.

PO2Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using the 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 public health and safety, and cultural, societal, and environmental considerations.

PO4Conduct 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.

PO5Modern 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.

PO6The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal & cultural issues and the consequent responsibilities relevant to the professional engineering practice.

PO7Environment and sustainability: Understand the impact of 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 & responsibilities and norms of the engineering practice.

PO9Individual 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.

PO11Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one's work, as a member and leader in a team, to manage projects and in multidisciplinary environments.

PO12Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent & life-long learning in the broadest context of technological change.

 

Department of Computer Science and Engineering. ( Artificial Intelligence)
Course Outcomes (COs)
Course code Course Name CO-numbering Statement
22MDA31 Graph theory and Discrete Mathematical Structures, Probability and Statistics

 

C301.1  Understand and explain the basic concepts of graph theory.

 

C301.2 Understand an intense foundational introduction to fundamental concepts in discrete Mathematics.
C301.3 Interpret, identify, and solve the language associated with logical structure, sets, relations and functions, modular arithmetic.

 

C301.4  Make use of the correlation and regression analysis to fit a suitable mathematical model for the statistical data.

 

C301.5 Applying discrete and continuous probability distributions in analyzing the probability models arising in engineering field.

 

C301.6 Construct joint probability distributions.
     22CA32

 

 

Digital System Design And Computer Organization

 

C302.1 Illustrate different simplifying techniques in the design of combinational circuits.
C302.2 Design various combinational and sequential digital circuits.
C302.3 Design various counters using Flip-Flops.
C302.4 Demonstrate the fundamentals of computer organization with machine instructions.
C302.5 Elaborate the communication of input/output devices with computer system and solve arithmetic Operations using various techniques.
22CA33 Operating System

 

C303.1 To introduce operating system, OS responsibilities, and OS services.
C303.2 To discuss process concept, process scheduling techniques, and multi-threading concepts.
C303.3 To demonstrate deadlock condition in the computer system, and usage of main memory.
C303.4 To introduce virtual memory management concepts and file system.
C303.5 To explain about secondary storage system and Linux OS as a case study.
22CA34 Data Structures And Applications

 

C304.1 Explain the fundamentals of data structures and their applications to solve real life problems.
C304.2 Demonstrate the working of linear and nonlinear data structures.
C304.3 Write solutions to problems using linear data structures and nonlinear data structures.
C304.4 Apply different data structures to solve given problem.
C304.5 Develop skills to apply appropriate data structures in problem solving
22CAL35 Data Structures And Applications Lab

 

C305.1 Illustrate implementation of basic operations on data structures.
C305.2 Interpret Applications of different data structures.
C305.3 Demonstrate data structures and their variants.
C305.4 Illustrate various searching techniques using trees and graphs.
C305.5 Develop skills to identify appropriate data structures to solve a given problem.
22CA36 Object Oriented Programming With Java C306.1 Learn fundamental features of object-oriented language and JAVA.
C306.2 Learn object-oriented concepts using programming examples.
C306.3 Study the concepts of importing packages, exception handling mechanism and multi threading.
C306.4 Introduce event handling mechanism.
C306.5 Create Graphical User Interface (GUI) applications using swings.
22CA383 R Programming

 

C308.1 Explore and understand how R and R Studio interactive environment.
C308.2 To learn and practice programming techniques using R programming.
C308.3 Read Structured Data into R from various sources.
C308.4 Understand the different data Structures, data types in R.
C308.5 To develop small applications using R Programming.
22BB41 Biology For Engineers

 

C401.1 To familiarize the students with the basic biological concepts and their engineering applications.
C401.2 To enable the students with an understanding of bio design principles to create novel devices and structures.
C401.3 To provide the students an appreciation of how biological systems can be re-designed as substitute products for natural systems.
22CA42 Principles  Of  Artificial Intelligence

 

C402.1 Gain a historical perspective of AI and its foundations
C402.2 Become familiar with basic principles of AI toward problem solving
C402.3 Get to know approaches of inference, perception, Uncertain Knowledge and Reasoning.
C402.4 Experience AI development tools such as an ‘AI language’, expert system shell, and/or data mining tool.
C402.5 Experiment with a machine learning model for simulation and analysis.
22CA43 Database Management Systems C403.1 Learn and practice data modelling using entity relationship and developing database design
C403.2 Practice SQL programming through a variety of database problems.
C403.3 Apply normalization techniques to normalize the database
C403.4 Demonstrate the use of concurrency and transactions in database
C403.5 Design and build database applications for real world problems.
22CA44 Analysis And Design Of Algorithms C404.1 Describe basic concepts, notations, methods used in design and analysis of algorithms
C404.2 Explain various algorithm design techniques.
C404.3 Design and analyze the efficiency of a given problem using various design techniques.
C404.4 Differentiate efficiency of different algorithm design techniques for a given problem.
C404.5 Apply the suitable algorithm design technique for a given problem
22CAL45 Algorithms Lab C405.1 Demonstrate the basic  concepts of Java Programming.
C405.2 Illustrate Different Sorting Algorithm design techniques.
C405.3 Solve Graph Applications using various design techniques.
C405.4 Interpret combinatorial problems using Backtracking technique.
C405.5 Develop skills to identify suitable algorithm design technique to solve a given problem
22CA462 Object Oriented programming With Python C406.1 Learn the syntax and semantics of Python programming language.
C406.2 Illustrate the process of structuring the data using lists, tuples and dictionaries.
C406.3 Demonstrate the use of built-in functions of file system.
C406.4 Implement the Object Oriented Programming concepts in Python
C406.5 Appraise the need for working with various documents like Excel, PDF, Word and Others.
S. No Name Designation Experience (In Years)
1 Dr. RAJASHREE V BIRADAR Professor - HOD 32
2 Mr. VIKRAM SANDEEP P Assoc. Prof 11
3 Mr. BIMANNA A Associate Professor 10
4 Mrs. AMRUTHA H Assistant Professor 03
5 Ms. PREMA Assistant Professor 03
6 Mr. RAMESH KUMAR K. R. Assistant Professor 07
Lab Instructor Mr. Gangaraju
Department Attender Mr. Suresh
Name Of The Lab CSE(AI)
Size in Square Meters 181.18
No. Of. Computer System 70
Configuration DELL OPTIPLEX 3060 SFF, CORE I7-8TH GEN PROCESSOR, 16GB DDR4 RAM, 512 NVME SSD, 22 INCH DELL MONIOTOR KEYBOARD & MOUSE WI1 10/11 PRO
Lab Manual Yes
Lab Instructor Mr. Gangaraju
Staff In Charge Mr. Rameshkumar  K R

Labs held in odd and even semesters:

  • DS lab
  • OS lab
  • DBMS lab
  • C & C++ lab
  • Algorithms lab
  • AI lab
  • R programming
  • Python programming

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