Course Structure Overview
The curriculum for the Bachelor of Technology in Engineering at Akal University Bathinda is meticulously designed to provide a strong foundation, followed by specialized knowledge and practical application. The program spans eight semesters over four academic years, with each semester offering core courses, departmental electives, science electives, and laboratory sessions.
| Year | Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|---|
| First Year | I | ENG101 | Engineering Mathematics I | 3-1-0-4 | - |
| ENG102 | Engineering Physics | 3-1-0-4 | - | ||
| ENG103 | Engineering Chemistry | 3-1-0-4 | - | ||
| ENG104 | Basic Electrical Engineering | 3-1-0-4 | - | ||
| ENG105 | Introduction to Programming | 2-0-2-3 | - | ||
| ENG106 | Engineering Graphics | 2-0-2-3 | - | ||
| ENG107 | Professional Communication | 2-0-0-2 | - | ||
| ENG108 | Workshop Practice | 0-0-4-2 | - | ||
| First Year | II | ENG201 | Engineering Mathematics II | 3-1-0-4 | ENG101 |
| ENG202 | Engineering Mechanics | 3-1-0-4 | - | ||
| ENG203 | Materials Science | 3-1-0-4 | - | ||
| ENG204 | Electronics Devices and Circuits | 3-1-0-4 | ENG104 | ||
| ENG205 | Data Structures & Algorithms | 2-0-2-3 | ENG105 | ||
| ENG206 | Engineering Drawing | 2-0-2-3 | - | ||
| ENG207 | Environmental Studies | 2-0-0-2 | - | ||
| ENG208 | Introduction to Engineering Design | 0-0-4-2 | - | ||
| Second Year | III | ENG301 | Thermodynamics | 3-1-0-4 | ENG201, ENG202 |
| ENG302 | Fluid Mechanics and Hydraulic Machines | 3-1-0-4 | ENG201 | ||
| ENG303 | Strength of Materials | 3-1-0-4 | - | ||
| ENG304 | Control Systems | 3-1-0-4 | ENG204 | ||
| ENG305 | Digital Logic and Microprocessor | 3-1-0-4 | ENG204 | ||
| ENG306 | Computer Organization and Architecture | 3-1-0-4 | ENG205 | ||
| ENG307 | Engineering Economics | 2-0-0-2 | - | ||
| ENG308 | Design Project I | 0-0-4-2 | - | ||
| Second Year | IV | ENG401 | Heat Transfer | 3-1-0-4 | ENG301 |
| ENG402 | Mechanics of Machines | 3-1-0-4 | ENG303 | ||
| ENG403 | Design of Machine Elements | 3-1-0-4 | - | ||
| ENG404 | Signals and Systems | 3-1-0-4 | ENG201 | ||
| ENG405 | Probability and Statistics | 3-1-0-4 | ENG101 | ||
| ENG406 | Database Management Systems | 2-0-2-3 | ENG205 | ||
| ENG407 | Project Management | 2-0-0-2 | - | ||
| ENG408 | Design Project II | 0-0-4-2 | - | ||
| Third Year | V | ENG501 | Machine Learning Fundamentals | 3-1-0-4 | ENG405 |
| ENG502 | Deep Learning with TensorFlow | 3-1-0-4 | ENG501 | ||
| ENG503 | Natural Language Processing | 3-1-0-4 | ENG501 | ||
| ENG504 | Computer Vision and Image Processing | 3-1-0-4 | ENG502 | ||
| ENG505 | Cybersecurity Principles | 3-1-0-4 | - | ||
| ENG506 | Network Security | 3-1-0-4 | ENG505 | ||
| ENG507 | Robotics and Automation | 3-1-0-4 | - | ||
| ENG508 | Structural Analysis | 3-1-0-4 | ENG303 | ||
| Third Year | VI | ENG601 | Advanced Machine Learning | 3-1-0-4 | ENG502 |
| ENG602 | Reinforcement Learning | 3-1-0-4 | ENG601 | ||
| ENG603 | Cloud Computing and Big Data | 3-1-0-4 | - | ||
| ENG604 | Embedded Systems | 3-1-0-4 | - | ||
| ENG605 | Power System Analysis | 3-1-0-4 | ENG204 | ||
| ENG606 | Renewable Energy Systems | 3-1-0-4 | - | ||
| ENG607 | Biomedical Instrumentation | 3-1-0-4 | - | ||
| ENG608 | Project Management | 2-0-0-2 | - | ||
| Fourth Year | VII | ENG701 | Capstone Project I | 0-0-8-4 | - |
| ENG702 | Advanced Research Methodology | 3-1-0-4 | - | ||
| ENG703 | Thesis Proposal | 0-0-6-3 | - | ||
| ENG704 | Research Ethics and Integrity | 2-0-0-2 | - | ||
| ENG705 | Specialized Elective I | 3-1-0-4 | - | ||
| ENG706 | Specialized Elective II | 3-1-0-4 | - | ||
| ENG707 | Professional Development | 2-0-0-2 | - | ||
| ENG708 | Internship | 0-0-12-6 | - | ||
| Fourth Year | VIII | ENG801 | Capstone Project II | 0-0-10-5 | - |
| ENG802 | Thesis Final Report | 0-0-8-4 | - | ||
| ENG803 | Final Project Defense | 0-0-4-2 | - | ||
| ENG804 | Industry Exposure Program | 0-0-6-3 | - | ||
| ENG805 | Final Placement Preparation | 2-0-0-2 | - | ||
| ENG806 | Entrepreneurship Workshop | 2-0-0-2 | - | ||
| ENG807 | Graduation Ceremony | 0-0-0-0 | - | ||
| ENG808 | Career Counseling Session | 2-0-0-2 | - |
Advanced Departmental Electives
The program includes a wide range of advanced departmental elective courses that allow students to specialize in emerging areas of engineering. These courses are designed to provide deep insights into specific domains while encouraging interdisciplinary thinking and innovation.
- Machine Learning Fundamentals: This course introduces students to foundational concepts in machine learning, including supervised and unsupervised learning algorithms, neural networks, decision trees, clustering techniques, and regression models. Students will implement these algorithms using Python and TensorFlow, preparing them for more advanced coursework.
- Deep Learning with TensorFlow: Building upon the fundamentals, this course delves into deep neural architectures such as CNNs, RNNs, LSTMs, and Transformers. Students will explore image classification, natural language processing tasks, and generative models using TensorFlow and Keras frameworks.
- Natural Language Processing (NLP): This course covers text preprocessing, sentiment analysis, topic modeling, named entity recognition, and language generation. Using tools like spaCy, NLTK, and Hugging Face Transformers, students will build end-to-end NLP pipelines for real-world applications.
- Computer Vision and Image Processing: Focused on image manipulation and object detection, this course explores convolutional neural networks, edge detection, feature extraction, and object recognition techniques. Students will use OpenCV and PyTorch to develop computer vision systems.
- Cybersecurity Principles: This foundational course covers cryptographic protocols, network security, authentication mechanisms, intrusion detection systems, and secure coding practices. Students will gain hands-on experience through labs simulating real-world cybersecurity challenges.
- Network Security: An advanced elective focusing on protecting networks from threats like malware, DDoS attacks, and man-in-the-middle attacks. The course includes penetration testing, firewall configuration, and security auditing techniques using tools like Wireshark and Metasploit.
- Robotics and Automation: Students learn about robotic kinematics, control systems, sensor integration, and AI-driven decision-making. The lab component involves building and programming robots for various environments such as manufacturing floors or disaster response scenarios.
- Structural Analysis: This course teaches students how to analyze structures under load, including beams, trusses, and frames. Topics include bending moment diagrams, deflection calculations, and stability analysis using structural engineering principles.
- Power System Analysis: Designed for electrical engineering students, this course covers power flow analysis, short-circuit calculations, protection systems, and stability studies in power grids. Students will use industry-standard software like MATLAB/Simulink to simulate real-world scenarios.
- Renewable Energy Systems: This elective explores solar, wind, hydroelectric, and biomass energy conversion technologies. Students will study energy storage solutions, grid integration strategies, and environmental impact assessments related to renewable energy projects.
Project-Based Learning Philosophy
At Akal University Bathinda, project-based learning is central to the engineering education philosophy. It fosters critical thinking, problem-solving abilities, and teamwork among students by immersing them in real-world challenges that mirror industry expectations.
Mini Projects
Throughout the first three years, students undertake mini-projects that are integrated into their coursework. These projects typically last 2-3 months and involve designing, prototyping, testing, and documenting a solution to a given problem. Mini-projects are evaluated based on technical execution, innovation, teamwork, and presentation quality.
Final-Year Thesis/Capstone Project
The capstone project in the final year is a comprehensive endeavor that spans 6 months and requires students to collaborate with faculty mentors and industry partners. The project must demonstrate mastery of the core engineering concepts learned throughout the program, along with advanced skills in research methodology, data analysis, and report writing. Students present their findings at an internal conference and may be invited to submit papers for publication in peer-reviewed journals.
Faculty Mentorship
Each student is assigned a faculty mentor who guides them through the project lifecycle, from initial idea generation to final implementation. Mentors provide technical support, feedback on progress, and advice on career development. Regular meetings ensure continuous progress tracking and timely resolution of issues.