Adichunchanagiri University
Artificial Intelligence
& Machine Learning
Innovating in AI and machine learning for sustainable development and value-based socio-economic needs. B.E. AI&ML with focus on deep learning, NLP, computer vision, and intelligent systems.
About the Department

The Department of Artificial Intelligence & Machine Learning at BGS Institute of Technology (BGSIT) was established under Adichunchanagiri University to meet the growing demand for AI professionals. With an annual intake of 60 students, the programme is designed to equip graduates with deep expertise in intelligent systems, data-driven decision-making, and cutting-edge AI technologies.

The department focuses on innovation in deep learning, natural language processing, computer vision, and reinforcement learning. Students work with industry-standard frameworks including TensorFlow, PyTorch, and Scikit-learn in dedicated GPU-equipped laboratories from the early semesters.

Guided by the vision of sustainable development and value-based socio-economic impact, the AI&ML department actively collaborates with industry partners to ensure graduates are prepared for the rapidly evolving technology landscape.

  • AICTE-Approved B.E. Artificial Intelligence & Machine Learning
  • Established under Adichunchanagiri University (ACU)
  • Annual intake of 60 students
  • Dedicated GPU-equipped Deep Learning & AI labs
  • 86% average placement rate across BGSIT programmes
  • Focus areas: Deep Learning, NLP, Computer Vision, Edge AI
  • Industry partnerships with leading tech companies
  • Project-based learning integrated from early semesters
Course Details & Eligibility
Programme Bachelor of Engineering (B.E.)
Specialisation Artificial Intelligence & Machine Learning
Duration 4 Years (8 Semesters)
Annual Intake 60 Students
Eligibility 10+2 PCM / PCMB · Min 45%
Accreditation NAAC A+ · AICTE Approved

Eligibility Criteria

  • Passed 10+2 or equivalent with Physics, Chemistry & Mathematics as core subjects
  • Minimum 45% aggregate marks (40% for SC/ST/OBC candidates as per norms)
  • Valid KCET / COMEDK / JEE Main rank
  • Recognised boards: CBSE, ICSE, Karnataka PUC and state equivalents
Focus Areas & Specialisations
B.E. AI&ML — Focus Area
Deep Learning & Neural Networks

Convolutional neural networks, recurrent architectures, GANs, transformers, and end-to-end deep learning model design using TensorFlow and PyTorch.

Deep Learning
B.E. AI&ML — Focus Area
Natural Language Processing

Text classification, sentiment analysis, machine translation, chatbot development, and large language model fine-tuning for real-world applications.

NLP
B.E. AI&ML — Focus Area
Computer Vision

Image recognition, object detection, semantic segmentation, video analytics, and deploying vision models on edge devices for real-time inference.

Computer Vision
B.E. AI&ML — Focus Area
Reinforcement Learning

Markov decision processes, Q-learning, policy gradient methods, multi-agent systems, and applications in robotics and autonomous navigation.

Reinforcement Learning
B.E. AI&ML — Focus Area
Data Engineering & Analytics

Big data pipelines, ETL processes, data warehousing, statistical modelling, and visualisation with Tableau, Power BI, and Python analytics libraries.

Data Engineering
B.E. AI&ML — Focus Area
Edge AI & IoT Intelligence

Deploying AI models on resource-constrained devices, TinyML, on-device inference, smart sensor integration, and cloud-edge hybrid architectures.

Edge AI
Vision, Mission & Programme Objectives
Vision

To innovate in the fields of artificial intelligence and machine learning for achieving sustainable development and to meet the value based socio-economic needs.

Mission
  • Advance AI systems' capabilities to enhance human life.
  • Align AI/ML with sustainable development goals for positive change.
  • Develop technologically entrepreneurial operations and innovation for socio-economic needs.

Programme Educational Objectives (PEOs)

1 Analyse requirements, realize technical specification and design Engineering solutions by applying AI theory and principles.
2 Make successful career in higher studies/industry/research.
3 Be life-long learning and should be able to work on multi-disciplinary projects.
4 Be competent for effective communication, management, professional skills and ethics.

Programme Specific Outcomes (PSOs)

1 Ability to apply concepts, principles and practices of AI and ML and critically evaluate results with proper arguments, selection of tools and techniques.
2 Ability to use AI and ML models on data for enabling better decision making.
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Curriculum & Syllabus

Download the latest ACU scheme syllabus for the AI&ML programme. All curricula are updated to the current academic scheme.

B.E. AI&ML Core Scheme 2022 · 8 Semesters Download PDF
Deep Learning Track Elective · Sem 5–8 Download PDF
Data Science Track Elective · Sem 5–8 Download PDF
Placements & Industry Connect

BGSIT's dedicated Placement Cell maintains active relationships with 100+ industry partners, offering structured internship programmes, pre-placement training, and direct campus recruitment drives. The AI&ML department benefits from growing industry demand for AI professionals across every sector.

Top recruiters include global technology leaders such as TCS, Infosys, Wipro, Accenture, and Capgemini, alongside AI-focused product companies. AI&ML graduates command competitive packages driven by the high demand for machine learning and data science talent.

  • 86% average placement rate across BGSIT programmes
  • Strong demand for AI/ML engineers across all industries
  • 100+ active recruiter partnerships across sectors
  • Structured internship pipelines from Semester 5
  • Placement training: aptitude, coding, group discussion, HR rounds
  • Annual campus drives (October through February)
TCS Infosys Wipro Accenture Capgemini IBM Cognizant HCL Technologies Amazon Google Microsoft Intel
Career Opportunities

A B.E. AI&ML from BGSIT opens doors to a wide spectrum of high-growth technology roles across every industry sector:

AI/ML Engineer
Data Scientist
NLP Engineer
Computer Vision Engineer
Robotics Engineer
Deep Learning Researcher
Data Engineer
MLOps Engineer
AI Product Manager
Autonomous Systems Engineer
Business Intelligence Analyst
AI Ethics Consultant
Conversational AI Developer
Recommendation Systems Engineer
Research Scientist
Tech Entrepreneur
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