Post Graduate Diploma in Big Data

Programme Educational Objectives

After completion of the program 

PEO-01: Graduates will establish themselves as skilled data professionals by applying big data technologies and analytics tools to solve real-world business challenges across various domains. 

PEO-02: Graduates will engage in continuous learning and adapt to emerging technologies, methodologies, and tools in the rapidly evolving field of big data and data science. 

PEO-03: Graduates will demonstrate leadership, teamwork, and effective communication in multidisciplinary environments, contributing to organizational growth and innovation. 

PEO-04: Graduates will practice their profession with integrity, adhering to ethical principles and data governance standards, while considering societal and environmental impacts in their data-driven decisions. 

Programme Outcomes (POs)

PO-01: To apply big data frameworks, tools, and techniques such as Hadoop, Spark, and NoSQL to store, process, and analyze large-scale datasets. 

PO-02: To demonstrate competence in analyzing complex datasets using statistical methods, machine learning models, and data visualization tools to derive actionable insights. 

PO-03: To develop efficient solutions using programming languages like Python, R, and SQL for data manipulation, analysis, and automation of workflows. 

PO-04: To design and implement real-time data pipelines and analytics using technologies like Apache Kafka, Spark Streaming, and cloud-native services. 

PO-05: To deploy and manage big data solutions on cloud platforms such as AWS, Azure, and Google Cloud, ensuring scalability, performance, and security. 

PO-06: To create interactive dashboards and reports using tools like Tableau and Power BI to support business intelligence and decision-making. 

PO-07: To understand and apply ethical principles, legal considerations, and governance standards in the collection, storage, and use of data. 

PO-08: To identify complex business problems and develop data-driven strategies using structured analytical approaches and critical reasoning. 

PO-09: To present data insights and technical findings clearly and concisely to diverse audiences through reports, visualizations, and oral presentations. 

PO-10: To function effectively in multidisciplinary teams, managing tasks, timelines, and resources to deliver successful data science projects and capstone solutions. 

Programme Specific Outcomes

PSO-1: To design and implement scalable big data solutions using distributed computing frameworks like Hadoop, Spark, and Hive to handle large volumes of structured and unstructured data. 

PSO-2: To develop and apply machine learning models to extract predictive insights and automate decision-making processes across diverse domains. 

PSO-3: To architect, deploy, and manage end-to-end data analytics workflows on cloud platforms such as AWS, Azure, and GCP, ensuring reliability, scalability, and security. 

Student handbook

• V1-PU_Student Handbook_2025_26.pdf

Program Regulations

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USP

• One-Year Intensive Industry-Aligned Program: A fast-track, full-time diploma designed to equip you with practical big data skills and certifications in just one year. 
• Hands-on Learning with Real-World Projects: Work on live datasets, industry case studies, and a capstone project that mirrors real-world big data challenges. 
• Master In-Demand Tools & Technologies: Gain expertise in top tools and platforms: Hadoop, Spark, Python, R, SQL, Power BI, Tableau, AWS, Azure, and Google Cloud. 
• End-to-End Data Pipeline Skills: From data ingestion and processing to machine learning and business intelligence—learn the entire lifecycle of big data. 
• Faculty from Academia & Industry: Benefit from the combined wisdom of experienced academicians and industry veterans who bring real-world insights into the classroom. 
• Career-Driven Curriculum with Placement Support: Resume building, interview prep, career counselling, and placement assistance tailored to high-growth data roles. 
• Cloud-Native Training Environment: Learn to work in cloud ecosystems with hands-on experience deploying data solutions on AWS, Azure, and GCP. 
• Industry-Recognized Certifications: Earn certifications that are valued by employers and enhance your credibility in the job market. 
• Future-Ready Skills in AI & ML: Develop strong foundational skills in machine learning and predictive analytics, opening doors to AI-focused roles. 
• High-Demand Career Pathways: Get prepared for roles like Data Engineer, Big Data Analyst, BI Developer, ML Engineer, and more.