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Fees
₹8,00,000
Placement
92.0%
Avg Package
₹6,50,000
Highest Package
₹12,00,000
Fees
₹8,00,000
Placement
92.0%
Avg Package
₹6,50,000
Highest Package
₹12,00,000
Seats
120
Students
1,200
Seats
120
Students
1,200
The Computer Applications program at Alard University Pune is structured into eight semesters over four academic years. Each semester includes core subjects, departmental electives, science electives, and laboratory sessions designed to build comprehensive technical competencies.
| Semester | Course Code | Course Title | Credit Structure (L-T-P-C) | Pre-requisites |
|---|---|---|---|---|
| Semester I | CS101 | Introduction to Computer Programming | 3-0-2-4 | None |
| CS102 | Mathematics I | 3-0-2-4 | None | |
| CS103 | Physics for Computer Science | 3-0-2-4 | None | |
| CS104 | Chemistry for Engineers | 3-0-2-4 | None | |
| CS105 | English Communication Skills | 3-0-2-4 | None | |
| CS106 | Computer Workshop | 0-0-4-2 | None | |
| CS107 | Introduction to Problem Solving | 3-0-2-4 | CS101 | |
| CS108 | Basic Electronics and Circuits | 3-0-2-4 | None | |
| CS109 | Introduction to Computing Systems | 3-0-2-4 | CS101 | |
| CS110 | Programming Lab | 0-0-4-2 | CS101 | |
| Semester II | CS201 | Data Structures and Algorithms | 3-0-2-4 | CS107 |
| CS202 | Mathematics II | 3-0-2-4 | CS102 | |
| CS203 | Object-Oriented Programming | 3-0-2-4 | CS101 | |
| CS204 | Digital Logic and Computer Organization | 3-0-2-4 | CS108 | |
| CS205 | Database Management Systems | 3-0-2-4 | CS101 | |
| CS206 | Computer Graphics and Multimedia | 3-0-2-4 | CS103 | |
| CS207 | Operating Systems | 3-0-2-4 | CS101 | |
| CS208 | Software Engineering | 3-0-2-4 | CS103 | |
| CS209 | Microprocessors and Microcontrollers | 3-0-2-4 | CS108 | |
| CS210 | Programming Lab II | 0-0-4-2 | CS110 | |
| Semester III | CS301 | Advanced Data Structures and Algorithms | 3-0-2-4 | CS201 |
| CS302 | Mathematics III | 3-0-2-4 | CS202 | |
| CS303 | Web Technologies | 3-0-2-4 | CS203 | |
| CS304 | Computer Networks | 3-0-2-4 | CS204 | |
| CS305 | Artificial Intelligence | 3-0-2-4 | CS201 | |
| CS306 | Cryptography and Network Security | 3-0-2-4 | CS205 | |
| CS307 | Data Mining and Warehousing | 3-0-2-4 | CS205 | |
| CS308 | Mobile Application Development | 3-0-2-4 | CS203 | |
| CS309 | Embedded Systems | 3-0-2-4 | CS209 | |
| CS310 | Lab Session III | 0-0-4-2 | CS210 | |
| Semester IV | CS401 | Machine Learning | 3-0-2-4 | CS305 |
| CS402 | Mathematics IV | 3-0-2-4 | CS302 | |
| CS403 | Cloud Computing | 3-0-2-4 | CS304 | |
| CS404 | Software Testing and Quality Assurance | 3-0-2-4 | CS208 | |
| CS405 | Distributed Systems | 3-0-2-4 | CS304 | |
| CS406 | Human Computer Interaction | 3-0-2-4 | CS206 | |
| CS407 | Big Data Analytics | 3-0-2-4 | CS307 | |
| CS408 | Internet of Things (IoT) | 3-0-2-4 | CS309 | |
| CS409 | Research Methodology | 3-0-2-4 | CS201 | |
| CS410 | Lab Session IV | 0-0-4-2 | CS310 | |
| Semester V | CS501 | Advanced Machine Learning | 3-0-2-4 | CS401 |
| CS502 | Deep Learning | 3-0-2-4 | CS401 | |
| CS503 | Advanced Cybersecurity | 3-0-2-4 | CS306 | |
| CS504 | DevOps and CI/CD | 3-0-2-4 | CS404 | |
| CS505 | Blockchain Technologies | 3-0-2-4 | CS306 | |
| CS506 | Mobile and Web Application Development | 3-0-2-4 | CS303 | |
| CS507 | Advanced Data Science | 3-0-2-4 | CS307 | |
| CS508 | Quantum Computing | 3-0-2-4 | CS201 | |
| CS509 | Game Development | 3-0-2-4 | CS206 | |
| CS510 | Lab Session V | 0-0-4-2 | CS410 | |
| Semester VI | CS601 | Capstone Project I | 3-0-2-4 | CS501 |
| CS602 | Capstone Project II | 3-0-2-4 | CS601 | |
| CS603 | Advanced Research in AI | 3-0-2-4 | CS502 | |
| CS604 | Security Auditing and Penetration Testing | 3-0-2-4 | CS503 | |
| CS605 | Agile Development Practices | 3-0-2-4 | CS404 | |
| CS606 | Cloud Native Applications | 3-0-2-4 | CS403 | |
| CS607 | Advanced Database Systems | 3-0-2-4 | CS305 | |
| CS608 | Advanced Human Computer Interaction | 3-0-2-4 | CS506 | |
| CS609 | Research Paper Writing and Presentation | 3-0-2-4 | CS409 | |
| CS610 | Lab Session VI | 0-0-4-2 | CS510 | |
| Semester VII | CS701 | Internship and Industry Exposure | 3-0-2-4 | CS601 |
| CS702 | Advanced Topics in Computer Science | 3-0-2-4 | CS501 | |
| CS703 | Research and Innovation | 3-0-2-4 | CS609 | |
| CS704 | Advanced Capstone Project | 3-0-2-4 | CS701 | |
| CS705 | Specialized Elective I | 3-0-2-4 | None | |
| CS706 | Specialized Elective II | 3-0-2-4 | None | |
| CS707 | Specialized Elective III | 3-0-2-4 | None | |
| CS708 | Specialized Elective IV | 3-0-2-4 | None | |
| CS709 | Capstone Presentation | 3-0-2-4 | CS704 | |
| CS710 | Lab Session VII | 0-0-4-2 | CS610 | |
| Semester VIII | CS801 | Final Capstone Project | 3-0-2-4 | CS704 |
| CS802 | Industry Integration and Portfolio Development | 3-0-2-4 | CS701 | |
| CS803 | Placement Preparation Workshop | 3-0-2-4 | None | |
| CS804 | Advanced Elective I | 3-0-2-4 | None | |
| CS805 | Advanced Elective II | 3-0-2-4 | None | |
| CS806 | Advanced Elective III | 3-0-2-4 | None | |
| CS807 | Advanced Elective IV | 3-0-2-4 | None | |
| CS808 | Graduation and Final Presentation | 3-0-2-4 | CS801 | |
| CS809 | Research Thesis Proposal | 3-0-2-4 | CS609 | |
| CS810 | Lab Session VIII | 0-0-4-2 | CS710 |
Departmental electives play a crucial role in allowing students to explore specialized areas within Computer Applications. These courses are designed to provide advanced knowledge and practical skills that align with current industry demands.
This course delves into the mathematical foundations of machine learning algorithms, including supervised, unsupervised, and reinforcement learning techniques. Students learn to implement models using popular frameworks like TensorFlow and PyTorch, with hands-on projects involving image recognition, natural language processing, and recommendation systems.
This elective focuses on advanced security concepts including penetration testing, vulnerability assessment, digital forensics, and incident response. Students gain expertise in securing networks, databases, and cloud environments, preparing them for roles in cybersecurity consulting and threat analysis.
Students learn to automate software delivery pipelines using tools like Jenkins, Docker, Kubernetes, and GitLab CI. The course emphasizes collaboration between development and operations teams, enabling students to build scalable deployment processes that ensure rapid and reliable software releases.
This course explores distributed ledger technologies, smart contracts, consensus mechanisms, and cryptocurrency systems. Students work on projects involving blockchain application development, token economics, and decentralized finance (DeFi) platforms, gaining insights into the transformative potential of blockchain beyond cryptocurrencies.
Students study containerization, microservices architecture, and cloud-native development using platforms like AWS, Azure, and Google Cloud. The course covers designing scalable applications that leverage cloud services for high availability, fault tolerance, and cost optimization.
This elective focuses on advanced statistical modeling, predictive analytics, data visualization, and machine learning in enterprise contexts. Students learn to extract actionable insights from large datasets using Python, R, and SQL, with real-world case studies covering financial analysis, marketing optimization, and healthcare analytics.
This course examines user-centered design principles, usability testing, prototyping, and interaction design. Students work on projects involving mobile apps, web interfaces, and assistive technologies, developing skills to create intuitive and accessible digital experiences for diverse user groups.
This cutting-edge course introduces quantum mechanics concepts and their application in computing. Students learn about quantum algorithms, quantum programming using Qiskit and Cirq, and potential applications in cryptography, optimization, and drug discovery, preparing them for emerging careers in this field.
This course covers advanced topics in database design, query optimization, transaction management, and NoSQL databases. Students gain expertise in designing efficient data architectures and implementing robust systems that handle large-scale data processing and analytics requirements.
Students learn to create immersive gaming experiences using game engines like Unity and Unreal Engine. The course covers 3D modeling, animation, physics simulation, and user interface design, with projects ranging from simple mobile games to complex virtual reality experiences.
The department's philosophy on project-based learning emphasizes experiential education that bridges theory and practice. Projects are structured to simulate real-world challenges, encouraging students to apply learned concepts in innovative ways while developing essential teamwork and communication skills.
Throughout the program, students engage in mini-projects that span various domains of computer applications. These projects typically last 2-3 months and involve problem-solving, research, design, implementation, and evaluation phases. Each project is guided by a faculty mentor who provides technical support, feedback, and industry insights.
The final-year capstone project represents the culmination of the student's learning journey. Students choose a topic aligned with their specialization or personal interests, working closely with a faculty advisor to develop a comprehensive solution or research contribution. The project must demonstrate originality, technical depth, and practical applicability.
Students select projects through a collaborative process involving faculty advisors, industry partners, and personal interests. The selection considers feasibility, relevance to current trends, and alignment with career goals. Faculty mentors are assigned based on expertise areas and project requirements, ensuring personalized guidance throughout the development cycle.
