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MCA in Cloud Computing at Invertis University
Bareilly, Uttar Pradesh
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About the Specialization
What is Cloud Computing at Invertis University Bareilly?
This Cloud Computing program at Invertis University focuses on equipping students with expertise in designing, deploying, and managing scalable cloud infrastructure and applications. Given India''''s rapid digital transformation, there''''s a significant demand for cloud-skilled professionals, making this program highly relevant for mastering cutting-edge cloud technologies and methodologies through dedicated elective tracks.
Who Should Apply?
This program is ideal for BCA or B.Sc./B.Com./B.A. graduates with mathematics, seeking entry into the booming cloud industry. It also caters to working professionals aiming to upskill in cloud technologies or career changers looking to transition into cloud architecture, development, or security roles within the dynamic Indian IT landscape.
Why Choose This Course?
Graduates of this program can expect to pursue career paths such as Cloud Engineer, Cloud Architect, Cloud Security Analyst, or DevOps Engineer in India. Entry-level salaries typically range from INR 4-7 LPA, with experienced professionals earning upwards of INR 15-30 LPA in major Indian tech hubs, aligning with global cloud certifications and robust growth trajectories.
Student Success Practices
Foundation Stage
Master Programming & Data Structures Fundamentals- (Semester 1-2)
Develop a strong command over core programming languages like C and Java, along with fundamental data structures and algorithms. Consistently practice coding problems on platforms like HackerRank and LeetCode to build robust problem-solving abilities crucial for all advanced computer science domains.
Tools & Resources
HackerRank, LeetCode, GeeksforGeeks, NPTEL courses on Data Structures and Algorithms
Career Connection
This foundation is essential for cracking technical interviews, building efficient software solutions, and serves as the bedrock for any specialized role in IT.
Build a Strong Mathematical & Logical Foundation- (Semester 1-2)
Focus on Discrete Mathematics, Logic, and Algorithm Design to enhance analytical and critical thinking. Actively participate in university-level coding competitions and problem-solving challenges to apply theoretical knowledge to practical scenarios, improving logical reasoning skills.
Tools & Resources
NPTEL courses on Discrete Mathematics, Competitive programming platforms, Academic journals for problem sets
Career Connection
Critical for advanced roles in AI/ML, Data Science, and complex system architecture, which often involve intricate logical constructs and mathematical modeling.
Engage in Peer Learning & Collaborative Projects- (Semester 1-2)
Form study groups and work on small collaborative programming projects using version control systems like Git/GitHub. This approach fosters teamwork, communication skills, and exposes students to diverse problem-solving methodologies early in their academic journey.
Tools & Resources
GitHub, GitLab, Google Docs for collaborative coding
Career Connection
Develops vital soft skills for working in modern agile development teams, enhances personal portfolio with collaborative works, and prepares for industry-standard development practices.
Intermediate Stage
Deep Dive into Cloud Electives & Certifications- (Semester 3)
Actively choose and excel in the Cloud Computing elective (MCA-E011). Simultaneously pursue fundamental cloud certifications like AWS Cloud Practitioner, Azure Fundamentals, or Google Cloud Digital Leader to validate theoretical knowledge with industry-recognized credentials and clearly demonstrate a specialization path.
Tools & Resources
Official AWS, Azure, GCP documentation and training, Udemy, Coursera, Exam practice platforms
Career Connection
This provides a direct pathway to entry-level cloud roles, showcasing a proactive approach to specialization and immediate industry readiness to potential employers.
Hands-on with Cloud Platforms- (Semester 3)
Utilize free-tier services of major public cloud providers (AWS, Azure, GCP) to deploy basic applications, manage virtual machines, and understand fundamental networking and storage concepts. Participate in cloud-focused workshops and bootcamps to gain practical experience beyond classroom learning.
Tools & Resources
AWS Free Tier, Azure Free Account, Google Cloud Free Tier, Docker (introduction), Kubernetes (basics)
Career Connection
Essential practical experience that bridges academic learning with real-world cloud deployment scenarios, making students highly desirable and job-ready for various cloud engineering roles.
Explore DevOps & Automation Basics- (Semester 3)
Begin exploring basic DevOps principles and automation tools relevant to cloud environments. Understand concepts like Continuous Integration/Continuous Deployment (CI/CD), Infrastructure as Code (IaC), and containerization, which are integral to modern cloud operations and efficiency.
Tools & Resources
Git and GitHub Actions, Jenkins (basic concepts), Terraform (introductory modules), Ansible (introductory modules)
Career Connection
These are highly valued skills in cloud engineering and DevOps roles, significantly increasing employability and efficiency in managing and deploying cloud resources and applications.
Advanced Stage
Undertake a Comprehensive Cloud-focused Major Project- (Semester 4)
For the Minor and Major Projects (MCA-452, MCA-453), design and implement a complex cloud-native application or a significant cloud infrastructure project. Focus on scalability, security (integrating MCA-E021: Cloud Security learnings), and cost optimization, ensuring thorough documentation and a strong presentation.
Tools & Resources
Full suite of AWS/Azure/GCP services, Advanced CI/CD pipelines, Cloud security scanning tools, Performance monitoring tools
Career Connection
A strong, well-executed project acts as a capstone, showcasing deep technical expertise, innovative problem-solving, and practical application skills to potential employers for advanced cloud roles.
Target Advanced Cloud Certifications & Interview Preparation- (Semester 4)
Beyond fundamental certifications, aim for associate-level cloud certifications (e.g., AWS Solutions Architect Associate, Azure Developer Associate). Simultaneously, dedicate significant time to interview preparation, focusing on cloud architecture, system design, and behavioral questions specific to cloud roles and India''''s tech landscape.
Tools & Resources
Official certification guides, Interview prep platforms (Educative, InterviewBit), Mock interviews with industry mentors
Career Connection
Distinguishes candidates for specialized cloud roles, directly impacting placement success and opening doors to higher-paying opportunities and accelerated career growth.
Contribute to Open Source Cloud Projects or Internships- (Semester 4)
Actively seek out internships in cloud engineering or related fields to gain real-world experience. If an internship isn''''t immediately feasible, contribute to open-source cloud projects (e.g., Kubernetes, OpenStack, cloud-native tools) to gain collaborative development experience and expand your professional network.
Tools & Resources
GitHub for open-source contributions, Professional networking events, University placement cell for internship opportunities
Career Connection
Provides invaluable practical exposure, significantly enhances your résumé, and often leads to full-time employment opportunities upon graduation by demonstrating initiative and practical skills.
Program Structure and Curriculum
Eligibility:
- Passed BCA/ Bachelor Degree in Computer Science Engineering or equivalent Degree. OR Passed B.Sc./ B.Com./ B.A. with Mathematics at 10+2 Level or at Graduation Level (with additional bridge Courses as per the norms of the University). Obtained at least 50% marks (45% marks in case of candidates belonging to reserved category) in the qualifying examination.
Duration: 2 years (4 semesters)
Credits: 98 Credits
Assessment: Internal: 30%, External: 70%
Semester-wise Curriculum Table
Semester 1
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MCA-101 | Professional Communication | Core | 4 | Communication Process, Oral Communication, Written Communication, Group Discussion, Presentation Skills |
| MCA-102 | Data Structures using C | Core | 4 | Introduction to Data Structures, Arrays, Stacks and Queues, Linked Lists, Trees and Graphs, Sorting and Searching |
| MCA-103 | Object-Oriented Programming using Java | Core | 4 | OOP Concepts, Java Basics, Classes and Objects, Inheritance and Polymorphism, Exception Handling, Multithreading and GUI Programming |
| MCA-104 | Computer Organization and Architecture | Core | 4 | Basic Computer Operations, CPU Design, Memory Organization, Input/Output Organization, Parallel Processing |
| MCA-105 | Discrete Mathematical Structures | Core | 4 | Set Theory, Relations and Functions, Logic and Propositional Calculus, Combinatorics, Graph Theory, Algebraic Structures |
| MCA-151 | Data Structures using C Lab | Lab | 2 | Array Operations, Stack/Queue Implementation, Linked List Operations, Tree Traversals, Graph Algorithms, Sorting Algorithms |
| MCA-152 | Object-Oriented Programming using Java Lab | Lab | 2 | Class and Object Programs, Inheritance and Polymorphism, Exception Handling Programs, Multithreading Applications, GUI Development |
| MCA-153 | Professional Communication Lab | Lab | 2 | Listening Skills, Speaking Practice, Reading Comprehension, Writing Practice, Interview Skills, Role Plays |
Semester 2
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MCA-201 | Operating Systems | Core | 4 | Introduction to OS, Process Management, CPU Scheduling, Deadlocks, Memory Management, Virtual Memory, File Systems |
| MCA-202 | Database Management System | Core | 4 | DBMS Concepts, ER Model, Relational Model, SQL Queries, Normalization, Transaction Management, Concurrency Control |
| MCA-203 | Design and Analysis of Algorithms | Core | 4 | Algorithm Analysis, Divide and Conquer, Greedy Methods, Dynamic Programming, Graph Algorithms, NP-Completeness |
| MCA-204 | Computer Networks | Core | 4 | Network Models, Physical Layer, Data Link Layer, Network Layer, Transport Layer, Application Layer, Network Security |
| MCA-205 | Artificial Intelligence | Core | 4 | AI Introduction, Problem Solving Techniques, Knowledge Representation, Machine Learning Basics, Expert Systems, Natural Language Processing |
| MCA-251 | Operating Systems Lab | Lab | 2 | Shell Programming, Process Creation, CPU Scheduling Simulation, Memory Management Simulation, File System Operations |
| MCA-252 | Database Management System Lab | Lab | 2 | SQL Queries, PL/SQL Programming, Database Design, Stored Procedures, Triggers, Cursor Operations |
| MCA-253 | Design and Analysis of Algorithms Lab | Lab | 2 | Sorting Algorithms, Graph Algorithms, Dynamic Programming Problems, Greedy Algorithms, Time Complexity Analysis |
Semester 3
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MCA-301 | Python Programming | Core | 4 | Python Basics, Data Structures in Python, Functions and Modules, Object-Oriented Python, Exception Handling, File I/O and Database Connectivity |
| MCA-302 | Software Engineering | Core | 4 | Software Development Life Cycle, Requirement Engineering, Software Design Principles, Software Testing, Software Maintenance, Project Management |
| MCA-303 | Machine Learning | Core | 4 | Introduction to ML, Supervised Learning, Unsupervised Learning, Regression and Classification, Model Evaluation, Deep Learning Basics |
| MCA-E011 | Cloud Computing | Elective (Cloud Computing Specialization) | 4 | Cloud Computing Concepts, Cloud Service Models (IaaS, PaaS, SaaS), Virtualization Technology, Cloud Platforms (AWS, Azure, GCP Overview), Cloud Security Fundamentals, Cloud Deployment Models |
| MCA-351 | Python Programming Lab | Lab | 2 | Basic Python Programs, Data Structure Implementation, OOP in Python, File Handling, Database Interaction |
| MCA-352 | Machine Learning Lab | Lab | 2 | Data Preprocessing, Supervised Learning Models, Unsupervised Learning Models, Model Evaluation Metrics, ML Libraries (Scikit-learn) |
| MCA-353 | Web Technology Lab | Lab | 2 | HTML5 and CSS3, JavaScript, Web Servers, PHP Basics, Database Integration, Web Application Development |
Semester 4
| Subject Code | Subject Name | Subject Type | Credits | Key Topics |
|---|---|---|---|---|
| MCA-401 | Data Science | Core | 4 | Data Science Lifecycle, Data Collection and Cleaning, Exploratory Data Analysis, Data Visualization, Predictive Analytics, Big Data Concepts |
| MCA-E021 | Cloud Security | Elective (Cloud Computing Specialization) | 4 | Cloud Security Fundamentals, Data Security in Cloud, Identity and Access Management, Network Security in Cloud, Compliance and Audits, Cloud Security Best Practices |
| MCA-451 | Data Science Lab | Lab | 2 | Data Cleaning and Transformation, Statistical Analysis, Data Visualization Tools, Machine Learning for Data Science, Case Studies |
| MCA-452 | Minor Project | Project | 4 | Project Planning, Literature Review, System Design, Implementation, Testing and Debugging, Documentation and Presentation |
| MCA-453 | Major Project | Project | 10 | Advanced Project Management, Research Methodology, Innovative Solution Design, Large-scale Implementation, Comprehensive Testing and Validation, Thesis Writing and Defense |
