Department of

Computer Science & Engineering (AIML)

Building the future of software and computing technology

Future-ready curriculum, outcome-based learning, and partnerships with leading technology companies empower NSRIET students to innovate confidently and lead the next wave of digital transformation.

Explore CurriculumAcademic Calendar
  • AI Powered
  • Strategic Industry Partner with global tech leaders
  • Experiential learning through hackathons & sponsored labs
  • Best Practices & Accomplishments

Program Duration

4 years (8 semesters)

Intake

120 students

Approvals

AICTE And JNTU GV

Program Overview

The Computer Science & Engineering (AIML) program at NSRIET is designed to develop skilled software professionals who can solve real-world computational problems. Students gain expertise in programming, software design, and computer systems while working on industry-relevant projects and research initiatives.

Program Duration
4 years (8 semesters)
Intake
120 students
Approvals
AICTE And JNTU GV

Vision & Mission

Vision

To become a centre of excellence in producing competent and innovative AI and ML professionals capable of driving future technologies.

Mission

  • To deliver strong theoretical and practical foundations in Artificial Intelligence and Machine Learning.
  • To provide a research-driven and innovation-focused environment that addresses real-world challenges.
  • To impart industry-ready training through advanced tools, technologies, and experiential learning.

Program Educational Objectives (PEOs)

  • PEO1: Technical Excellence & Problem-Solving — Apply strong foundational and advanced knowledge in computer science to solve complex real-world problems using critical thinking, adapting to rapidly changing technologies to meet industry and client needs.
  • PEO2: Professional Success & Leadership — Build successful careers as entrepreneurs, team members, or leaders in IT and related industries, demonstrating professional competence and collaborative skills.
  • PEO3: Lifelong Learning & Career Growth — Engage in continuous self-learning and pursue higher education or certifications to stay current with industry trends and achieve sustained professional excellence.

Program Outcomes (POs) & PSOs

Program Outcomes (POs)

PO1: Apply mathematics, computing, and engineering principles to solve complex AI/ML challenges.
PO2: Analyze and interpret data-driven problems using theoretical and research-oriented approaches.
PO3: Design AI/ML models, applications, and solutions considering ethics, safety, culture, and sustainability.
PO4: Conduct research involving data analysis, model evaluation, experimentation, and validation.
PO5: Use modern AI frameworks, programming tools, and advanced technologies effectively.
PO6: Examine societal, ethical, environmental, and legal impacts of AI and data-driven technologies.
PO7: Demonstrate ethical AI practices, inclusivity, transparency, and professional responsibility.
PO8: Work collaboratively in interdisciplinary teams and contribute effectively as a leader or member.
PO9: Communicate complex AI/ML concepts clearly through reports, documentation, and presentations.
PO10: Apply project management and economic principles to develop AI/ML solutions.
PO11: Engage in continuous learning and adapt to emerging AI and ML advancements.

Program Specific Outcomes (PSOs)

  • PSO1: Design intelligent software using AI/ML and data engineering practices.
  • PSO2: Build secure, scalable full-stack solutions for cloud and mobile platforms.

Curriculum Highlights & Syllabi

Core Subjects

  • ✓Data Structures and Algorithms
  • ✓Database Management Systems
  • ✓Operating Systems
  • ✓Computer Networks
  • ✓Web Development
  • ✓Software Engineering
  • ✓Mobile Application Development
  • ✓Cloud Computing

Learning Outcomes

  • Proficiency in multiple programming languages and frameworks
  • Understanding of software development lifecycle and best practices
  • Ability to design scalable and secure systems
  • Problem-solving skills for complex computational challenges

Outcome-based curriculum covering core computing, emerging tech electives, and interdisciplinary pathways. Download the detailed syllabus and course outcomes below.

📄 UG Syllabus📄 Elective Booklet

Academic Calendar

The department follows an activity-rich calendar with assessments, workshops, internships, and hackathons mapped semester-wise.

Select Academic Calendar
📄 3rd Year 1st Semester📄 2nd Year 1st Semester

Industry Sponsored Laboratory

iGenuine

Focus: Industry Sponsored Lab

Teckybot

Focus: Industry Sponsored Lab

Memoranda of Understanding (MoUs)

NASSCOMCouncil for Skills and CompetenciesiGenuineTeckybotTeckTeam Solutions

Innovative Teaching Methodologies

Industrial oriented program
LMS
Problem-based learning using hackathons and ideathons

Professional Development Activities

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Faculty Development Program

Annual FDPs on AI/ML, cloud and cybersecurity run with industry mentors, ensuring faculty stay ahead of emerging tech.

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Industry Design Sprints(DiDac,sony,coffeday)

Four-week immersion where student-faculty squads ship prototypes for partner companies using agile methods.

Innovation Showcases

Bi-semester showcases featuring student products, patent pitches, and investor feedback rounds.

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Peer Learning Studios

Community-of-practice circles where learners exchange toolkits, code recipes, and research insights.