B.Tech in Artificial Intelligence and Machine Learning is a four-year undergraduate engineering programme about building systems that learn from data, make decisions, and improve with experience. It is an AI engineering degree built on a solid artificial intelligence curriculum, and it asks for more than writing code. Students learn how machines “think”, how to work with data, patterns, and uncertainty, and how to build systems that evolve instead of simply following fixed instructions.
BLKGNIT Group of Institutions run this programme at GNIT (IPU Campus), a private engineering college in Greater Noida. It is a Grade “A” college of GGSIPU and is approved by AICTE. The course takes fundamentals into real-world problems, so students gain working knowledge of the tools behind modern AI and ML applications: Python, machine learning, data science, deep learning, and NLP. The curriculum leans on practical learning, industry-aligned exposure, and research-driven innovation, which prepares graduates to take on complex data and automation challenges in healthcare, finance, automotive, and technology.
Learning is supported by expert faculty, industry mentors, real-time projects, and case studies. Students also work in advanced AI labs and take part in AI hackathons, seminars, and industrial visits, so theory and practice stay close together. The aim is to produce graduates who think, innovate, and solve problems in a field that keeps changing, and not coders alone.
Duration 4 Years | Semesters 8 • Affiliated to Guru Gobind Singh Indraprastha University (GGSIPU) & AICTE Approved
B.Tech AIML Eligibility Criteria
Eligibility: Candidates must pass Class 12 (10+2) from CBSE or an equivalent board with at least 55% aggregate marks (50% for SC/ST) in PCM*. English must also be passed as a subject (core, elective, or functional). * Physics and Mathematics are mandatory. Chemistry can be replaced with Computer Science, Electronics, IT, Biology, Informatics Practices, Biotechnology, a Technical Vocational subject, Engineering Graphics, Business Studies, or Entrepreneurship.
Admission: Admission is based on merit or rank in JEE or CUET, followed by GGSIPU counselling.
Lateral Entry (2nd Year B.Tech): Candidates with a 3-year Engineering Polytechnic Diploma, or a B.Sc. degree with Mathematics (minimum 60% aggregate for General/EWS and 45% for SC/ST), can apply for direct entry into the 2nd year (3rd semester) through lateral entry counselling. Candidates must appear in JEE or CUET, followed by GGSIPU counselling.
B.Tech AIML Specialisations
The B.Tech AIML programme features cutting-edge domain specialisations designed to equip students with specialized mastery in modern AI applications:
Soft Computing
Machine Learning and Data Analytics
R-Programming
Image Processing and Computer Vision
B.Tech AIML Programme Structure & Curriculum
Detailed syllabus structure for B.Tech (AIML) affiliated with GGSIPU across all eight semesters, including theory papers, lab sessions, and Minor Specialization Courses (MSC):
Group
Paper Code
Paper Title
L
P
Credits
MDC
AR101
Engineering Mathematics-I
3
-
3
SEC
AR103
Programming for Problem Solving using C
3
-
3
DSC
AR107
Basics of Computer Organisation
3
-
3
DSC
AR109
Applied Engineering Materials
3
-
3
MSC
AR111
Basic Electrical Engineering
3
-
3
AEC
AR113
Design Thinking (NUES)
1
-
1
SEC
AR151
Programming for Problem Solving using C Lab
-
2
1
DSC
AR153
Applied Engineering Materials Lab
-
2
1
MSC
AR155
Basic Electrical Engineering Lab
-
2
1
AEC
AR157
Programming in Python Lab
-
2
1
VAC-I*
AR165 / AR167
Engineering Drawing with CAD Lab / Analytics and Dashboard Development
-
4
2
Total Marks: Total CreditsTotal Credits: 22
# (NUES): Non-University Exam Subject, Comprehensive evaluation by the concerned teacher, out of 100, as per detailed syllabus.
Programme Outcomes & Knowledge Profile
Knowledge and Attitude Profile [WK]
WK1: A systematic, theory-based understanding of the natural sciences applicable to the discipline and awareness of relevant social sciences.
WK2: Conceptually-based mathematics, numerical analysis, data analysis, statistics and formal aspects of computer and information science to support detailed analysis and modelling applicable to the discipline.
WK3: A systematic, theory-based formulation of engineering fundamentals required in the engineering discipline.
WK4: Engineering specialist knowledge that provides theoretical frameworks and bodies of knowledge for the accepted practice areas in the engineering discipline; much is at the forefront of the discipline.
WK5: Knowledge, including efficient resource use, environmental impacts, whole-life cost, reuse of resources, net zero carbon, and similar concepts, that supports engineering design and operations in a practice area.
WK6: Knowledge of engineering practice (technology) in the practice areas in the engineering discipline.
WK7: Knowledge of the role of engineering in society and identified issues in engineering practice in the discipline, such as the professional responsibility of an engineer to public safety and sustainable development.
WK8: Engagement with selected knowledge in the current research literature of the discipline, awareness of the power of critical thinking and creative approaches to evaluate emerging issues.
WK9: Ethics, inclusive behaviour and conduct. Knowledge of professional ethics, responsibilities, and norms of engineering practice. Awareness of the need for diversity by reason of ethnicity, gender, age, physical ability etc. with mutual understanding and respect, and of inclusive attitudes.
Programme Outcomes [PO's]
PO1: Engineering Knowledge: Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in WK1 to WK4 respectively to develop solutions for complex engineering problems.
PO2: Problem Analysis: Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions with consideration for sustainable development. (WK1 to WK4)
PO3: Design/Development of Solutions: Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for public health and safety, whole-life cost, net zero carbon, culture, society, and the environment as required. (WK5)
PO4: Conduct Investigations of Complex Problems: Conduct investigations of complex engineering problems using research-based knowledge including design of experiments, modelling, analysis and interpretation of data to provide valid conclusions. (WK8)
PO5: Engineering Tool Usage: Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling, recognizing their limitations to solve complex engineering problems. (WK2 and WK6)
PO6: The Engineer and The World: Analyze and evaluate societal and environmental aspects while solving complex engineering problems for their impact on sustainability with reference to economy, health, safety, legal framework, culture, and the environment. (WK1, WK5, and WK7)
PO7: Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national and international laws. (WK9)
PO8: Individual and Collaborative Team Work: Function effectively as an individual, and as a member or leader in diverse and multidisciplinary teams.
PO9: Communication: Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences.
PO10: Project Management and Finance: Apply knowledge and understanding of engineering management principles and economic decision-making and apply these to one's own work, as a member and leader in a team, and to manage projects in multidisciplinary environments.
PO11: Life-Long Learning: Recognize the need for, and have the preparation and ability for: (i) independent and life-long learning; (ii) adaptability to new and emerging technologies; (iii) critical thinking in the broadest context of technological change. (WK8)
Career Scope & Pathways in AI & ML
Graduates of our B.Tech AIML programme are equipped with the theoretical foundations and hands-on laboratory experience required for top industry roles:
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