Instructor Profile:
Dr. Kiran RameshraoKaware
Assistant Professor and Academic Coordinator, Department of Mechanical Engineering, Sandip University
Dr. Kiran RameshraoKaware is a distinguished Assistant Professor and Academic Coordinator in the Mechanical Engineering Department at Sandip University, where he brings over 15 years of extensive teaching and research experience to his role. He holds a Ph.D. from Visvesvaraya National Institute of Technology (VNIT), Nagpur, with a specialization in low and high-velocity impact on composites, finite element analysis, and vibration analysis.
Throughout his academic career, Dr.Kaware has made significant contributions to the field of mechanical engineering, publishing over 30 research papers, 10 of which are indexed in prominent databases such as Scopus and the Science Citation Index (SCI). His research endeavors have garnered substantial support, securing several industry grants aimed at fostering innovative research projects. Dr.Kaware’s dedication to maintaining high research quality is evident in his active role as a reviewer for various academic journals, where he assesses submissions and contributes to the scholarly community.
Dr.Kaware is deeply committed to student development and academic excellence. He provides specialized training and expert lectures, ensuring that his students receive a comprehensive and enriching educational experience. His approach to education emphasizes not only the acquisition of technical knowledge but also the development of critical thinking and problem-solving skills essential for success in the engineering field.
In addition to his teaching responsibilities, Dr.Kaware plays a pivotal role in academic coordination, where he leads initiatives to enhance curriculum delivery and student engagement. His leadership in research and dedication to fostering a supportive learning environment have established him as a respected figure within the mechanical engineering community.
Dr. Kiran RameshraoKaware’s commitment to education, research, and student development positions him as an invaluable asset to Sandip University and the broader academic landscape. His passion for advancing knowledge and innovation continues to inspire both his colleagues and students alike.
Course Name: Big Data Overflow
Module 1: Introduction to Big Data
- Understanding Big Data: Definition and characteristics of Big Data, Types of Big Data: Structured, Unstructured, and Semi-structured
- The Big Data Ecosystem: Overview of Big Data technologies and tools, Data storage solutions: Hadoop, NoSQL databases
- Data Sources and Collection: Sources of Big Data: Social media, IoT, transactions, etc. Techniques for data collection and integration
Module 2: Big Data Processing and Analytics
- Data Processing Techniques: Batch processing vs. real-time processing, Introduction to Apache Spark and Apache Flink
- Data Analytics: Descriptive, predictive, and prescriptive analytics, Data mining techniques and algorithms
- Tools and Frameworks for Analytics: Overview of data analytics tools: R, Python, Tableau, Utilizing machine learning for Big Data analytics
Module 3: Big Data Challenges and Solutions
- Challenges in Big Data Management: Data quality, data privacy, and security issues, Scalability and data governance
- Solutions and Best Practices: Strategies for effective data management, Implementing data governance frameworks
Module 4: Future Trends in Big Data
- Emerging Technologies: The impact of artificial intelligence and machine learning on Big Data, The role of edge computing and cloud services
- Big Data in Industry: Applications of Big Data across sectors: healthcare, finance, retail, etc., The future of Big Data analytics and its implications
- Ethical Considerations and Data Responsibility: Understanding ethical issues in Big Data usage, Promoting responsible data practices in organizations
This course outline provides a comprehensive framework for understanding the multifaceted world of Big Data, equipping participants with the knowledge and skills to navigate and leverage its vast potential.
