Data Analytics

Mohiuddin Ahmed attained his PhD from UNSW Australia and currently working as Lecturer in Canberra Institute of Technology with the department of ICT & Library Studies. His research interests include Big Data Analytics, Machine Learning, Network Security, IoT and HealthCare. He is exploring Deep Learning for a sensible solution for Big Data Analytics. He has made practical and theoretical contribution for data summarization for network traffic analysis. His research also has a high impact on financial fraud detection, critical infrastructure protection (SCADA systems, Smart Grid), information security against DoS attacks and complicated health data (heart disease, nutrition) analysis. He has published a number of journals and conferences papers in reputed venues of computer science. Mohiuddin holds a Bachelor of Science Degree in Computer Science and Information Technology with High Distinction from Islamic University of Technology, OIC.Al-Sakib Khan Pathan received his PhD degree (MS leading to PhD) in computer engineering in 2009 from Kyung Hee University, South Korea. He received a BSc degree in computer science and information technology from the Islamic University of Technology, Bangladesh, in 2003.He is currently an Associate Professor at the Computer Science and Engineering (CSE) department, Southeast University, Bangladesh. He was an assistant professor in the Computer Science Department at the International Islamic University Malaysia, Malaysia. Until June 2010, he served as an assistant professor in the Computer Science and Engineering Department at BRAC University, Bangladesh. Prior to holding this position, he worked as a researcher at the Networking Lab, Kyung Hee University, South Korea, up to August 2009. His research interests include wireless sensor networks, network security, and e-services technologies.

• Part 1: Introduction to Data Analytics. 1. Techniques. 2. Classification. 3. Clustering. 4. Anomaly Detection. 5. Pattern Mining. Part 2: Tools for Data Analytics. 6. R. Hadoop. 7. Spark. 8. Rapid Miner. Part 3: Applications. 9. Health Care. 10. Internet of Things. 11. Cyber Security. Part 4: Futuristic Applications and Challenges.