Course Structure Overview
The engineering program at Alard University Pune is structured over eight semesters, with each semester designed to build upon previous knowledge while introducing new concepts and applications. The curriculum emphasizes a balanced blend of theoretical foundations, practical laboratory work, and real-world problem-solving through project-based learning.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Prerequisites |
|---|---|---|---|---|
| I | ENG101 | Engineering Mathematics I | 3-1-0-4 | - |
| I | ENG102 | Physics for Engineers | 3-1-0-4 | - |
| I | ENG103 | Chemistry for Engineers | 3-1-0-4 | - |
| I | ENG104 | Computer Programming | 2-0-2-3 | - |
| I | ENG105 | Engineering Drawing | 1-0-3-2 | - |
| I | ENG106 | English Communication Skills | 2-0-0-2 | - |
| I | ENG107 | Workshop Practice | 0-0-4-2 | - |
| II | ENG201 | Engineering Mathematics II | 3-1-0-4 | ENG101 |
| II | ENG202 | Basic Electrical Engineering | 3-1-0-4 | - |
| II | ENG203 | Engineering Mechanics | 3-1-0-4 | - |
| II | ENG204 | Data Structures and Algorithms | 3-1-0-4 | ENG104 |
| II | ENG205 | Introduction to Materials Science | 3-1-0-4 | - |
| III | ENG301 | Engineering Mathematics III | 3-1-0-4 | ENG201 |
| III | ENG302 | Thermodynamics | 3-1-0-4 | ENG202 |
| III | ENG303 | Fluid Mechanics | 3-1-0-4 | ENG203 |
| III | ENG304 | Digital Logic and Computer Organization | 3-1-0-4 | ENG104 |
| III | ENG305 | Signals and Systems | 3-1-0-4 | ENG201 |
| IV | ENG401 | Control Systems | 3-1-0-4 | ENG305 |
| IV | ENG402 | Electromagnetic Fields and Waves | 3-1-0-4 | ENG202 |
| IV | ENG403 | Probability and Statistics | 3-1-0-4 | ENG201 |
| IV | ENG404 | Microprocessors and Microcontrollers | 3-1-0-4 | ENG304 |
| IV | ENG405 | Engineering Economics | 3-1-0-4 | ENG201 |
| V | ENG501 | Design and Analysis of Algorithms | 3-1-0-4 | ENG204 |
| V | ENG502 | Computer Networks | 3-1-0-4 | ENG304 |
| V | ENG503 | Software Engineering | 3-1-0-4 | ENG204 |
| V | ENG504 | Operating Systems | 3-1-0-4 | ENG304 |
| V | ENG505 | Database Management Systems | 3-1-0-4 | ENG204 |
| VI | ENG601 | Artificial Intelligence | 3-1-0-4 | ENG501 |
| VI | ENG602 | Machine Learning | 3-1-0-4 | ENG501 |
| VI | ENG603 | Deep Learning | 3-1-0-4 | ENG602 |
| VI | ENG604 | Natural Language Processing | 3-1-0-4 | ENG602 |
| VI | ENG605 | Computer Vision | 3-1-0-4 | ENG602 |
| VII | ENG701 | Embedded Systems | 3-1-0-4 | ENG404 |
| VII | ENG702 | Internet of Things | 3-1-0-4 | ENG404 |
| VII | ENG703 | Cybersecurity Fundamentals | 3-1-0-4 | ENG502 |
| VII | ENG704 | Cloud Computing | 3-1-0-4 | ENG502 |
| VII | ENG705 | Big Data Analytics | 3-1-0-4 | ENG505 |
| VIII | ENG801 | Capstone Project | 0-0-6-6 | ENG701 |
| VIII | ENG802 | Research Methodology | 2-0-0-3 | - |
| VIII | ENG803 | Professional Ethics and Social Responsibility | 2-0-0-2 | - |
| VIII | ENG804 | Entrepreneurship and Innovation | 2-0-0-2 | - |
| VIII | ENG805 | Internship | 0-0-0-3 | - |
Advanced Departmental Electives
The program offers a rich selection of advanced departmental electives designed to deepen students' understanding and prepare them for specialized roles in their chosen fields.
Artificial Intelligence
This elective explores advanced AI techniques including reinforcement learning, neural architecture search, and generative adversarial networks. Students engage with cutting-edge research papers and implement novel algorithms using Python frameworks like TensorFlow and PyTorch.
Machine Learning
This course delves into supervised and unsupervised learning methods, ensemble models, time series forecasting, and advanced optimization techniques. Emphasis is placed on applying ML to real-world problems in finance, healthcare, and automation.
Deep Learning
Focusing on deep neural architectures such as CNNs, RNNs, LSTMs, and Transformers, this course teaches students how to design, train, and deploy complex models for image recognition, natural language processing, and audio analysis.
Natural Language Processing
This elective covers text preprocessing, sentiment analysis, language modeling, machine translation, and question answering systems. Students build applications using libraries like spaCy and Hugging Face Transformers.
Computer Vision
Students learn to detect and classify objects in images, perform image segmentation, and generate synthetic data. Practical applications include autonomous vehicles, medical imaging, and augmented reality systems.
Embedded Systems
This course focuses on designing embedded software for microcontrollers, real-time operating systems, and low-power hardware platforms. Students work with ARM Cortex-M series processors and develop IoT-based solutions.
Internet of Things (IoT)
Exploring connectivity protocols, sensor integration, edge computing, and cloud integration, this elective prepares students for building scalable IoT ecosystems across industries such as agriculture, manufacturing, and smart cities.
Cybersecurity Fundamentals
This course covers network security, cryptography, ethical hacking, and incident response. Students simulate attacks using tools like Kali Linux and learn how to secure enterprise environments from evolving threats.
Cloud Computing
Students explore cloud platforms like AWS, Azure, and Google Cloud, learning about virtualization, containerization (Docker, Kubernetes), and serverless computing. Projects involve deploying scalable web applications in the cloud.
Big Data Analytics
This elective introduces students to big data technologies such as Hadoop, Spark, and Kafka. Students analyze large datasets using Python and SQL, and gain insights into predictive analytics and data visualization.
Project-Based Learning Philosophy
At Alard University Pune, project-based learning is central to the engineering education experience. From semester one, students engage in hands-on projects that bridge theory with practice, reinforcing classroom concepts through real-world applications.
Mini-Projects
Each student undertakes two mini-projects during their undergraduate journey—one in the second year and another in the fifth year. These projects are evaluated based on design quality, technical execution, teamwork, and presentation skills.
Final-Year Capstone Project
The final-year capstone project is a significant component of the program, requiring students to conceptualize, develop, and present an innovative solution to a real-world challenge. Projects are guided by faculty mentors and often lead to patent filings or startup ventures.
Project Selection Process
Students choose projects based on their interests, career aspirations, and available resources. Faculty mentors provide guidance in selecting relevant topics, ensuring alignment with industry needs and academic rigor.