About
The B.Tech in Computer Science Engineering (CSE) with a specialization in Artificial Intelligence (AI) and Data Science at Pimpri Chinchwad University (PCU) provides students with a solid foundation in computer science while imparting specialized knowledge in AI and data science. This program integrates core computer science engineering principles with advanced courses in artificial intelligence and data science, preparing graduates to tackle complex problems using cutting-edge technologies.
Our curriculum includes core subjects such as programming, algorithms, and data structures, along with specialized courses in AI and data science, including machine learning, deep learning, natural language processing, and big data analytics. Emphasizing practical learning, the program offers lab sessions, projects, and internships to give students hands-on experience in developing and deploying AI and data science solutions.
Graduates can pursue careers as AI engineers, data scientists, machine learning engineers, and AI researchers. They are equipped to work in various industries, including technology, healthcare, finance, and automotive, making them highly valuable in the job market.
Preamble
The curriculum of B.Tech. Computer Science and Engineering program offered by the Department of Computer Science Engineering under Academic Regulation of NEP 2020 is prepared in accordance with the curriculum framework of AICTE, UGC and Maharashtra State Council of Higher Education, National Higher Education Qualifications Framework (NHEQF) and National Credit.
Framework (NCrF). Further this Outcome Based Curriculum (OBC) is designed with Choice Based Credit and Semester System (CBCSS) enabling the learners to gain professional competency with multi-disciplinary approach catering the minimum requirement (Program Specific Criteria) of Lead Societies like AICTE,ACM and other Professional Bodies as per the Engineering Accreditation Commission (EAC) of ABET and NBA. In addition, the curriculum and syllabi are designed in a structured approach by deploying Feedback Mechanism on Curriculum from various stakeholders viz. Industry, Potential Employers, Alumni, Academia, Professional Bodies, Research Organizations and Parents to capture their voice of the respective stakeholders. The Curriculum design, delivery, and assessment, the three major pillars of academic system is completely aligned in line with Outcome Based Education (OBE) to assess and evaluate the learning outcomes to facilitate the learners to achieve their Professional and Career Accomplishments.
After due deliberations, the scheme and syllabus have been formulated. Salient features of this model curriculum are enumerated as under:
- Adequate number of credits.
- Well defined learning objectives & outcomes for each course.
- Inclusion of courses on socially relevant topics.
- Built-in flexibility to the students in terms of professional elective and open elective courses and minor course.
- Mandatory internship to equip the students with practical knowledge and provide them exposure to real time industrial environments
- Mapping of Courses to its equivalent NPTEL/SWAYAM Course
Vision and Mission
To develop engineers well versed with Critical Theory and Practical's (problem solving ability) and sensitive to National and Global challenges from Inter-disciplinary perspective. To create Industry ready socially and ethically strong professionals.
To develop Computer Professionals by imparting computer engineering knowledge with professional ethics. To provide the service to the communities to which we belong at local and national levels, combined with a deep awareness of our ethical responsibilities to our profession and to society.
Program Objectives
The Program Objectives for the B.Tech CSE (AI & Data Science) program are as follows:
- To provide students with a substantial understanding of Data Science fundamentals todevelop their technical competence to address the real life problems.
- To train the students with the knowledge and skills in the area of Data Science for analysis, design and implementation of real life problems.
- To groom the students overall personality for professional growth.
- To inculcate values and ethics among the students and making them aware about their social commitments.
4 Years
Duration
₹ 2,40,000
Fees (Per Annum)
PCET
Centralized Placement Cell
Program Highlights
Structured Program with Dedicated Support
Dedicated Career Assistance
Hands on Learning
Job Readiness Program
Curriculum designed to cater recent trends
Quality placements.
Student participation in global competitions.
Exposure of In-house Incubation Cell nurturing various Start ups.
Course Curriculum
Semester
I
- Linear Algebra & Differential Calculus
- Engineering Physics/Engineering Chemistry
- Basic Electronics Engineering/Basic Electrical Engineering
- Engineering Graphics & Design/Web Programming
- Procedural Programming
- IT Workshop/Fab Workshop
- Applied Communication
- UHV - I: Professional Ethics/IKS: Indian Science, Engineering & Technology
Semester
II
- Integral Calculus & Numerical Techniques
- Engineering Chemistry/Engineering Physics
- Basic Electrical Engineering/Basic Electronics Engineering
- Web Programming/Engineering Graphics & Design
- Object Oriented Programming
- Fab Workshop/IT Workshop
- Advanced Communication
- IKS: Indian Science, Engineering & Technology/UHV - I: Professional Ethics
Semester
III
- Data Structures and Algorithms
- Data Structures and Algorithms Laboratory
- Python Programming
- Python Programming Laboratory
- Open Elective - I
- OpenElective - I Lab
- Discrete Mathematics
- Operating System
- Community Engineering Project
- International Language - I
- UHV - II :Understanding Harmony/ Contitution of India
Semester
IV
- Database Management System
- Database Management System Laboratory
- Java Programming
- Computer Organisation
- Applied Mathematics
- Open Elective - II
- Open Elective - II Lab
- Java Programming Laboratory
- International Language - II
- Minor - I
- UHV: Understanding Harmony/Constitution of India
- Project Based on Digital and Technological Solutions
Semester
V
- Theory of Computation
- Computer Network
- Computer Network Lab
- Data Science
- Data Science Lab
- Programme Elective - I
- Programme Elective - I Lab
- Minor 2
- Applied Statistical Techniques
- Technical Seminar - AIDS
- International Language - III
- Aptitude and Logical Reasoning/Environmental Studies
Semester
VI
- Data Science and Analytics
- Data Science and Analytics Lab
- Software Engineering and Project Management
- Design and Analysis of Algorithms
- Design and Analysis of Algorithms Lab
- Programme Elective - II
- Programme Elective - II Lab
- Programme Elective - III
- Programme Elective - III Lab
- Minor - 3
- International Language - IV
- MOOC - II (Data Visualization using R programming/Advanced Full stack development/PHP)
- Aptitude and Logical Reasoning
Semester
VII
- Machine Learning
- Machine Learning Lab
- Programme Elective - IV
- Programme Elective - IV Lab
- Minor - 4
- Industry/International/Research Internship
- Major Project – I AIDS
- MOOC - III (Networking and Cyber Security/ARVR Certification)
Semester
VIII
- Deep Learning
- Deep Learning Lab
- Programme Elective - V
- Programme Elective - VI
- Programme Elective - VII
- Research Methodology & IPR
- Minor - 5
- Major Project - II
- MOOC - 3 Virtual Reality/Data Mining/UAV
List of Open Electives:
- Open Elective - I : Digital Logic& Microprocessor
- Open Elective - I Lab :Digital Logic& Microprocessor Lab
- Open Elective - I : Signals and Systems
- Open Elective - I Lab : Signals and Systems Lab
- Open Elective - II : IoT
- Open Elective - II Lab : IoT Lab
- Open Elective - II : Digital Image Processing
- Open Elective - II Lab : Digital Image ProcessingLab
List of Programme Elective:
- PROGRAM ELECTIVE COURSES - I : Artificial Intelligence
- PROGRAM ELECTIVE COURSES - I LAB : Advanced Web Programming
- PROGRAM ELECTIVE COURSES - I : Artificial Intelligence Lab
- PROGRAM ELECTIVE COURSES - I LAB :Advanced Web Programming Lab
- Program Elective Course - II : Machine Learning
- Program Elective Course - II : Pattern Recognition and Optimization
- Program Elective Course - II : Machine Learning Lab
- Program Elective Course - II : Pattern Recognition and Optimization Lab
- Program Elective Course - III : Big Data Analytics
- Program Elective Course - III : STQA
- Program Elective Course - II : Big Data Analytics lab
- Program Elective Course - II : STQA lab
- Program Elective Course - IV : Deep Learning
- Program Elective Course - IV : Natural Language Processing
- Program Elective Course - IV : Deep Learning Lab
- Program Elective Course - IV :Natural Language Processing Lab
- Program Elective Course - V : Robotic Process Automation
- Program Elective Course - V :Computer Vision and Video Processing
- Program Elective Course - V : Robotic Process Automation Lab
- Program Elective Course - V :Computer Vision and Video Processing Lab
- Program Elective Course - VI : Quantum Computing
- Program Elective Course - VI : Cloud Computing
Web Development (WD)
Offering School : School of Engineering &
Technology
- WD Minor1 : Introduction of HTML (# II/ *IV)
- WD Minor2 : Getting started with JavaScript (# III/ *V)
- WD Minor3 : Server-side Programming with Node.js (# IV/*VI)
- WD Minor4 : Front-end Development with React & Type Script (# V/*VII)
- WD Minor5 : Back-end frameworks - Django, Ruby on Rails (# VI/*VIII)
Robotics Process Automation (RP)
Offering School : School of Engineering &
Technology
- RP Minor1 : Basics of Robotics Process Automation (# II/ *IV)
- RP Minor2 : Fundamentals of RPA Business Analysis (# III/ *V)
- RP Minor3 : Automation Techniques in RPA (# IV/*VI)
- RP Minor4 : Future of RPA with Business Automation (# V/*VII)
- RP Minor5 : RPA Tool (# VI/*VIII)
Artificial intelligence &
Machine Learning
(ML)
Offering School : School of Engineering &
Technology
- ML Minor1 : Artificial Intelligence (# II/ *IV)
- ML Minor2 : Machine Learning (# III/ *V)
- ML Minor3 : Natural Language Processing (# IV/*VI)
- ML Minor4 : Optimization Techniques (# V/*VII)
- ML Minor5 : Deep Learning For Computer Vision (# VI/*VIII)
Data Science (DS)
Offering School : School of Engineering &
Technology
- DS Minor1 : Applied Data Science With Python (# II/ *IV)
- DS Minor2 : Data Visualization With Tableau (# III/ *V)
- DS Minor3 : Business Analytics (# IV/*VI)
- DS Minor4 : Data Analytics (# V/*VII)
- DS Minor5 : Generative AI (# VI/*VIII)
Media Communications (MM)
Offering School : School of media &
communications studies
- MM Minor1 : Literary Study (# II/ *IV)
- MM Minor2 : Digital Media Production (# III/ *V)
- MM Minor3 : Photography (# IV/*VI)
- MM Minor4 : Performing Arts - Theater (# V/*VII)
- MM Minor5 : Film Studies (# VI/*VIII)
Psychology (PSY)
Offering School : School of science
- PSY Minor1 : Introductory Psychology (# II/ *IV)
- PSY Minor2 : Foundations of Social Psychology (# III/ *V)
- PSY Minor3 : Theories of Personality Development (# IV/*VI)
- PSY Minor4 : Industrial Psychology (# V/*VII)
- PSY Minor5 : Mindfulness and Mental Health (# VI/*VIII)
Nutrition (NUT)
Offering School : School of science
- NUT Minor1 : Human Nutrition (# II/ *IV)
- NUT Minor2 : Lifestyle Management (# III/ *V)
- NUT Minor3 : Introduction to Weight Management (# IV/*VI)
- NUT Minor4 : Food Quality and Management (# V/*VII)
- NUT Minor5 : Novel Foods and Application (# VI/*VIII)
Design Thinking &
Methodologies (DM)
Offering School : Pune Design School
- DM Minor1 : Design Thinking (# II/ *IV)
- DM Minor2 : Brand Identity Design (# III/ *V)
- DM Minor3 : Digital tools for 2D design (# IV/*VI)
- DM Minor4 : Physical model making/ Prototyping (# V/*VII)
- DM Minor5 : Digital Tools for 3D design (# VI/*VIII)
Economics & Finance (FE)
Offering School : School of Management
- FE Minor1 : Micro-economics (# II/ *IV)
- FE Minor2 : Fundamentals of Accounting (# III/ *V)
- FE Minor3 : Principles of Finance (# IV/*VI)
- FE Minor4 : Cost and Management Accounting (# V/*VII)
- FE Minor5 : Macro economics (# VI/*VIII)
Entrepreneurship and
Innovations (EI)
Offering School : School of Management
- EI Minor1 : Entrepreneurship-New venture Development (# II/ *IV)
- EI Minor2 : Rural Entrepreneurship (# III/ *V)
- EI Minor3 : Design Thinking (# IV/*VI)
- EI Minor4 : Institutional and Legal framework for Startups and small Businesses (# V/*VII)
- EI Minor5 : Managing creativity and learning organizations (# VI/*VIII)
Drugs & Healthcare (DH)
Offering School : School of Pharmacy
- DH Minor1 : Health and hygiene (# II/ *IV)
- DH Minor2 : Know your drugs (# III/ *V)
- DH Minor3 : Complementary and alternative medicine (# IV/*VI)
- DH Minor4 : Drug Discovery (# V/*VII)
- DH Minor5 : Forensic Science (# VI/*VIII)
Software Application Design and Development
(AD)
Offering School : School of Engineering and
Technology
- AD Minor1 : System Analysis and Design (# II/ *IV)
- AD Minor2 : User Experience and Design (# III/ *V)
- AD Minor3 : Introduction to GitHub. (# IV/*VI)
- AD Minor4 : Introduction to Gaming Applications. (# V/*VII)
- AD Minor5 : Mobile Application Development (# VI/*VIII)
Cyber Security (CS)
Offering School : School of Engineering and
Technology
- CS Minor1 : Cyber Ethics, Cyber Law and Cyber Policy (# II/ *IV)
- CS Minor2 : Introduction to Cryptography (# III/ *V)
- CS Minor3 : Social Media Security. (# IV/*VI)
- CS Minor4 : Introduction to Blockchain. (# V/*VII)
- CS Minor5 : Data Security & Privacy. (# VI/*VIII)
English Literature (E)
Offering School : School of
Liberal Arts
- E Minor1 : English for Competitive Examinations-I (# II/ *IV)
- E Minor2 : English for Competitive Examinations-II (# III/ *V)
- E Minor3 : English for Competitive Examinations-III (# IV/*VI)
- E Minor4 : English for Competitive Examinations-IV (# V/*VII)
- E Minor5 : English for Competitive Examinations-V (# VI/*VIII)
English Literature (E)
Offering School : School of
Liberal Arts
- Learning English With Shakespeare-Romeo and Juliet (Minor-I) (# II/ *IV)
- Learning English With Shakespeare-Hamlet (Minor-II) (# III/ *V)
# : Courses offered for B Sc, BBA, Media, and Management& Liberal Arts
List of Audit Courses:
- Practicing Meditation, Sports, Yoga
- Performing Arts:
Music, Singing, Poetry, Indian Conventional Dancing, Photography, Short Movie Making, Painting/ Sketching/ Drawing, Theatre Arts, Anchoring, Calligraphy etc.
- Social welfare and Cultural Awareness
- Caring and service:
Hospital Caring, Personal Safety, First Aid, Disaster Management, Gardening, Organic farming, Cooking etc.
List of Foreign Languages:
- German
- Japanese
Programme
Programme Educational Objectives (PEOs)
- To provide students with a substantial understanding of Data Science fundamentals to develop their technical competence to address the real life problems.
- To train the students with the knowledge and skills in the area of Data Science for analysis, design and implementation of real life problems.
- To groom the students overall personality for professional growth.
- To inculcate values and ethics among the students and making them aware about their social commitments.
Programme Outcomes (POs)
- Engineering Knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
- Individual and Team Work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
- 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.
- 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.
- 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 Specific Outcomes (PSOs)
- Apply computing theory, languages and algorithms, mathematical and statistical model and the principles of optimization to appropriately formulate and use data analysis.
- Invent and use appropriate models of data analysis, access the quality of input, derive insights from results and investigate potential issues.
Eligibility
Passed 10+2 examination with Physics & Mathematics AND one of the subject from the following:
Chemistry/ Computer Science/ Electronics/ Information Technology/ Biology / Informatics Practices/ Biotechnology/ Technical Vocational subject/ Agriculture/ Engineering Graphics/ Business Studies/ Entrepreneurship.
Obtained at least 45% marks (40marks in case of candidate belonging to reserved category) in the above subjects taken together.
In addition to this, the applicant must have qualified at least one engineering entrance examination like MHT-CET 2025/JEE 2025 /Other State or National Level Engineering Entrance Exam of 2025 / PERA 2025 / CUET 2025 or Entrance Test Conducted by PCU
Candidates are selected based on entrance test score and on merit.
Career Opportunities
Graduates of the program can pursue careers in various fields as below and they can also pursue higher education and research in computer science and engineering.
FAQ's
What is B.Tech Computer Science Engineering (CSE) with AI & Data Science?
B.Tech Computer Science Engineering (CSE) with AI & Data Science is an undergraduate program that combines core computer science engineering principles with specialized courses in artificial intelligence and data science.
What career opportunities are available after completing this course?
Graduates can pursue roles such as AI engineers, data scientists, machine learning engineers, and AI researchers in industries like technology, healthcare, finance, and automotive.
What are the fees for B.Tech Computer Science Engineering?
Our B.Tech Computer Science Engineering program is competitively priced at 2, 40, 000 (Per Annum) offering excellent value for the comprehensive education and career preparation provided.
What should I do after B.Tech in CSE with AI & Data Science?
After completing B.Tech in CSE with AI & Data Science, graduates can opt for higher studies like M.Tech or MBA, or enter the workforce in roles such as AI engineers, data scientists, or software developers.
Which is better: B.Tech CSE or BCA?
B.Tech CSE offers a more in-depth and technical education suited for advanced engineering roles, while BCA provides a broad understanding of computer applications, ideal for various IT positions.
What are the subjects in B.Tech CSE with AI & Data Science?
The subjects include core computer science courses like programming, data structures, and algorithms, as well as specialized courses in AI and data science such as machine learning, deep learning, and big data analytics.
Are there AI and Data Science courses available in India for students after 12th?
Yes, several AI and Data Science courses are available in India after 12th, including diploma and certification programs. However, pursuing a B.Tech degree in computer science with a specialization in AI & Data Science is often a better option for a comprehensive education and better career opportunities.
What are the top engineering colleges in Pune for B.Tech CSE?
Pimpri Chinchwad University (PCU) is recognized to have one of the top engineering institutes in Pune, particularly for B.Tech CSE, due to our robust curriculum, experienced faculty, and excellent placement opportunities.
What is the syllabus for B.Tech CSE with AI & Data Science?
The B.Tech CSE syllabus includes core computer science subjects like programming, data structures, and algorithms, along with specialized courses in AI and data science such as machine learning, deep learning, natural language processing, and big data analytics. By offering a comprehensive education in B.Tech Computer Science Engineering with a specialization in AI and Data Science, we prepare our students to excel in the rapidly evolving fields of artificial intelligence and data science, ensuring they are equipped with the knowledge and practical skills needed to succeed in their careers.