A BTech in Artificial Intelligence is a 4-year (8-semester) Bachelor's degree offered by Purbachal University, primarily focusing on providing comprehensive knowledge of Artificial Intelligence to students. Purbanchal University’s Bachelor of Technology in Artificial Intelligence (BTech AI) is designed to equip students with the theoretical knowledge and practical skills needed to excel in this rapidly evolving field.
Institutions offering BTech in AI
Students pursuing BTech in AI can learn introductory courses in programming, computer science, mathematics, and statistics as well as crucial AI topics and techniques, including state-space search, gameplaying, Machine Learning, Neural networks, Computer vision, Language Understanding, and more advanced subjects.
BTech in Al graduates can use AI strategies and approaches to implement data-driven decision-making in firms and institutions with significant volumes of data. As a result, they may work in the various data analysis stages and create autonomous and efficient machine learning systems.
ATTENDANCE REQUIREMENT:
A student must achieve at least 80% attendance of lectures, tests, and tutorial classes in order to qualify for sitting for the final examination of any subject. There are no unauthorized cuts from classes; persistent poor attendance may result in exclusion from classes. In the case of unavoidable absence, such as for illness of the student, serious illness, or death of a member of the family, or similar compelling reasons for absence, all work missed must be satisfactorily made up, and the responsibility for making up this work rests with the concerned students.
After accomplishing this program, the student can enroll for a graduate degree such as:
- Master of Technology in Artificial Intelligence
- Master of Science in Artificial Intelligence
- Master of Computer Application
- Master of Information Technology
- Master of Science in Computer Science
- Master of Science in Computer Information Systems
- Master of Business Administration
Salient Features
Industry-Aligned Curriculum: Covers Python, TensorFlow, PyTorch, AI algorithms, and cloud computing.
Practical Learning: Labs, projects, and internships with AI companies.
Research Opportunities: Access to AI research centres and collaborations.
Expert Faculty: Experienced professors and industry professionals.
Entrepreneurship Support: Guidance for AI-based startups.
Eligibility
Students seeking admission in the Bachelor of Technology in Artificial Intelligence (BTech in AI) program:
- Should have successfully completed twelve years of schooling in the science stream.
Should have achieved a minimum D+ grade in each subject of 10+2 with a CGPA of 2.0 or more
OR
Should have secured a minimum score of second division (45%) marks in 10+2, PCL, or equivalent in the science discipline.
OR
Students who have passed grade 11 and are waiting for the supplementary exam (PURAK PARIKSHA) of grade 12 can also apply. However, they have to submit all the required documents at the time of admission.
OR
Students who appeared in the final exam and are waiting for the result and certificates can also apply for the entrance examination. However, they have to submit all the required documents at the time of admission.
- In case of a foreign certificate, the student should submit an equivalence certificate and each subject grading with CGPA or total percentage document from the concerned authority.
- Should pass the entrance examination as conducted by Purbanchal University
Job Prospects
- Machine/Deep learning Expert/Analyst
- Al professional
- AI specialist
- Analytics consultant
- Technology consultant
Curricular Structure
Year I – Semester I
| Course Code | Course Title | Credits | Lecture (Hrs) | Tutorial (Hrs) | Lab (Hrs) | Total (Hrs) |
|---|---|---|---|---|---|---|
| BT101CO | Introduction to Programming | 3 | 3 | 1 | 2 | 6 |
| BT102CO | Digital Logic | 3 | 3 | 1 | 2 | 6 |
| BT103HS | Calculus | 3 | 3 | 1 | 0 | 4 |
| BT104HS | Introduction to Artificial Intelligence | 3 | 3 | 1 | 0 | 4 |
| BT105HS | Technical Report Writing and Presentation | 3 | 3 | 1 | 0 | 4 |
| BT106HS | Society and Professional Ethics | 3 | 3 | 1 | 0 | 4 |
Year I – Semester II
| Course Code | Course Title | Credits | Lecture (Hrs) | Tutorial (Hrs) | Lab (Hrs) | Total (Hrs) |
|---|---|---|---|---|---|---|
| BT251CO | Object Oriented Programming | 3 | 3 | 1 | 2 | 6 |
| BT252CO | AI and Intelligent Systems | 3 | 3 | 1 | 2 | 6 |
| BT253CO | Microprocessor and Assembly Language | 3 | 3 | 1 | 2 | 6 |
| BT254CO | Probability and Statistics | 3 | 3 | 1 | 0 | 4 |
| BT255HS | Linear Algebra | 3 | 3 | 1 | 0 | 4 |
| BT256CO | Project I | 2 | 1 | 0 | 2 | 3 |
Year II – Semester I
| Course Code | Course Title | Credits | Lecture (Hrs) | Tutorial (Hrs) | Lab (Hrs) | Total (Hrs) |
|---|---|---|---|---|---|---|
| BT201CO | Database Management System | 3 | 3 | 1 | 2 | 6 |
| BT202CO | Data Structure and Algorithm | 3 | 3 | 1 | 2 | 6 |
| BT203CO | Computer Organization | 3 | 3 | 1 | 0 | 4 |
| BT204CO | Operating System | 3 | 3 | 1 | 2 | 6 |
| BT205HS | Differential Equations | 3 | 3 | 1 | 0 | 4 |
| BT206CO | Project II | 2 | 0 | 0 | 3 | 3 |
Year II – Semester II
| Course Code | Course Title | Credits | Lecture (Hrs) | Tutorial (Hrs) | Lab (Hrs) | Total (Hrs) |
|---|---|---|---|---|---|---|
| BT251CO | Numerical Methods | 3 | 3 | 1 | 2 | 6 |
| BT252CO | Computer Networks | 3 | 3 | 1 | 2 | 6 |
| BT253CO | Design and Analysis of Algorithms | 3 | 3 | 1 | 0 | 4 |
| BT254CO | Programming for AI (Tools, Techniques, Libraries) | 3 | 3 | 1 | 2 | 6 |
| BT255HS | Introduction to Data Science | 3 | 3 | 1 | 2 | 6 |
| BT256CO | Project III | 2 | 0 | 0 | 3 | 3 |
Year III – Semester I
| Course Code | Course Title | Credits | Lecture (Hrs) | Tutorial (Hrs) | Lab (Hrs) | Total (Hrs) |
|---|---|---|---|---|---|---|
| BT301CO | Machine Learning | 3 | 3 | 1 | 2 | 6 |
| BT302CO | Optimization Techniques | 3 | 3 | 1 | 2 | 6 |
| BT303CO | Embedded Systems | 3 | 3 | 1 | 2 | 6 |
| BT304CO | Pattern Recognition and Image Processing | 3 | 3 | 1 | 2 | 6 |
| BT305CO | Data Warehousing and Mining | 3 | 3 | 1 | 2 | 6 |
| BT306CO | Project IV | 2 | 0 | 0 | 3 | 3 |
Year III – Semester II
| Course Code | Course Title | Credits | Lecture (Hrs) | Tutorial (Hrs) | Lab (Hrs) | Total (Hrs) |
|---|---|---|---|---|---|---|
| BT351CO | Object Oriented Software Engineering | 3 | 3 | 1 | 2 | 6 |
| BT352CO | Computer Vision | 3 | 3 | 1 | 2 | 6 |
| BT353CO | Deep Learning | 3 | 3 | 1 | 2 | 6 |
| BT354CO | Speech and Natural Language Processing | 3 | 3 | 1 | 2 | 6 |
| BT355HS | Research Methods | 3 | 3 | 1 | 0 | 4 |
| BT356CO | Project V | 2 | 0 | 0 | 3 | 3 |
Year IV – Semester I
| Course Code | Course Title | Credits | Lecture (Hrs) | Tutorial (Hrs) | Lab (Hrs) | Total (Hrs) |
|---|---|---|---|---|---|---|
| BT401CO | Internship | 3 | 0 | 0 | 3 | 3 |
| BT402CO | Reinforcement Learning | 3 | 3 | 1 | 2 | 6 |
| BT403CO | Cloud Computing | 3 | 3 | 1 | 2 | 6 |
| BT404CO | Project VI | 2 | 0 | 0 | 3 | 3 |
Year IV – Semester II
| Course Code | Course Title | Credits | Lecture (Hrs) | Tutorial (Hrs) | Lab (Hrs) | Total (Hrs) |
|---|---|---|---|---|---|---|
| BT451CO | IoT for Smart City | 3 | 3 | 1 | 2 | 6 |
| BT452** | Elective I | 3 | 3 | 1 | 0 | 4 |
| BT453** | Elective II | 3 | 3 | 1 | 0 | 4 |
| BT454CO | Professional Project | 3 | 0 | 1 | 3 | 4 |
Elective Courses
Computer Vision
Image and Video Processing
Surveillance Video Analytics
People Detection and Biometric Recognition
Mathematics
Introduction to Statistical Learning
Optimization Methods in Machine Learning / Convex Optimization
Kernel Methods
Bayesian Data Analysis
Computing / IoT
Smart Product Development
Predictive Analysis and IoT
Modeling & Simulation
Pervasive Computing
Data Science
Fundamentals of Big Data Analytics
Data Analysis and Visualization
Business Intelligence
Social Media Analytics
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