The M.Tech in Data Science and Cloud Computing at HRIT University is a two-year postgraduate program designed to equip students with advanced knowledge and skills in data analytics and cloud technologies. This program integrates the principles of data science with cloud computing, enabling students to effectively handle large data sets, develop predictive models, and deploy scalable applications in a cloud environment.
The curriculum encompasses a range of subjects, including Data Mining, Machine Learning, Big Data Analytics, Cloud Architecture, and Distributed Systems. Students will gain hands-on experience through projects and case studies, focusing on real-world applications of data science and cloud computing in various sectors such as finance, healthcare, and e-commerce. Additionally, the program emphasizes the importance of data ethics and privacy, preparing graduates to address challenges in data management responsibly.
Programme Educational Objectives
- PEO-1: Graduates will establish themselves as skilled professionals, leveraging their expertise in Data Science and Cloud Computing to develop innovative solutions for real-world challenges.
- PEO-2: Graduates will apply their knowledge and skills to conduct impactful research and drive technological advancements in interdisciplinary areas.
- PEO-3: Through strong Industry-Academia partnerships, graduates will be highly employable and capable of becoming successful entrepreneurs in the data and cloud domains.
- PEO-4: Graduates will demonstrate professional ethics and leadership qualities while contributing to sustainable, socially responsible solutions in industry and research environments.
Programme Outcomes (POs)
- PO1: Engineering knowledge – Apply advanced mathematics, data science, and cloud computing principles to solve complex technical problems.
- PO2: Problem analysis – Formulate, investigate, and analyze problems in data management, analytics, and cloud system architecture using foundational engineering knowledge.
- PO3: Design/development of solutions – Design effective and innovative data-driven and cloud-based solutions that meet safety, societal, and environmental requirements.
- PO4: Conduct investigations – Employ research methodologies to analyze data sets, optimize algorithms, and derive meaningful insights for technological development.
- PO5: Modern tool usage – Master state-of-the-art tools for cloud computing, machine learning, big data analytics, and IT infrastructure management.
- PO6: The engineer and society – Evaluate societal, legal, and ethical issues associated with data privacy, cloud security, and data-centric applications.
- PO7: Environment and sustainability – Contribute to solutions that address the sustainability of cloud services and data practices in today’s environmental context.
- PO8: Ethics – Uphold the highest standards of professional ethics in dealing with sensitive data and cloud infrastructure management.
- PO9: Individual and teamwork – Work effectively in teams to develop and deploy integrated data science and cloud computing solutions.
- PO10: Communication – Articulate complex ideas and present data-driven solutions through well-crafted reports and presentations.
- PO11: Project management and finance – Demonstrate project management skills, ensuring efficient cloud deployments and budget-conscious data solutions.
- PO12: Lifelong learning – Commit to continuous learning in this ever-evolving field, staying updated with new trends and technologies.
Program Specific Outcomes (PSOs)
- PSO1: Develop and innovate in data science and cloud computing domains, applying research-driven insights to societal and technological challenges.
- PSO2: Build and optimize data-driven systems that leverage cloud infrastructure, artificial intelligence, machine learning, and cybersecurity.
- PSO3: Employ best practices in software development to create scalable, efficient, and secure cloud-based applications that meet business objectives.
The M.Tech in Data Science and Cloud Computing at HRIT University prepares students to become leaders in the data-driven economy, equipping them with the skills necessary to excel in an evolving technological landscape.
