Essential Research Tools—Learn effective data collection and more.
The IEEE RESPRO Comprehensive Research Program is a structured initiative designed to empower participants with the skills and knowledge required for research excellence. Phase 1 focuses on building a solid foundation by introducing key aspects of research methodology,
paper writing and practical tools. Through a series of interactive workshops, this programme equips attendees with essential techniques to navigate the academic landscape effectively. Following the success of the first two workshops, Workshop 3 of Phase 1, Essential Research Tools—Learn Effective Data Collection and More, enhanced participants' capabilities. This session introduces critical steps and strategies for conducting effective research and achieving academic success. Key areas were covered include:
- Data Collection Techniques: Introducing methods for accurate and reliable data gathering.
- Streamlined Workflow: Demonstrating how to optimize research processes for better productivity.
- Research Tools Overview: Exploring essential software and tools for data analysis and visualization.
- Data Management Skills: Teaching participants how to organize, store, and manage research data effectively.
- Effective Analysis: Providing strategies to interpret research findings and derive meaningful conclusions.
- Workflow Optimization: Highlighting advanced techniques to improve research productivity and accuracy.
Future plans for the IEEE RESPRO Comprehensive Research Program include organizing Phases Two and Three, which will delve deeper into advanced research-based techniques
Date and Time
Location
Hosts
Registration
- Date: 04 Jan 2025
- Time: 08:30 PM to 11:00 PM
- All times are (UTC+06:00) Astana
- Add Event to Calendar
- Starts 01 January 2025 12:00 AM
- Ends 04 January 2025 12:00 AM
- All times are (UTC+06:00) Astana
- No Admission Charge
Speakers
Nahiyan Bin Noor
Essential Research Tools - Learn Effective Data Collection and More
Biography:
𝗡𝗮𝗵𝗶𝘆𝗮𝗻 𝗕𝗶𝗻 𝗡𝗼𝗼𝗿 is an intermediate data analyst with the RTEC team at the Institute for Digital Health & Innovation, 𝗨𝗻𝗶𝘃𝗲𝗿𝘀𝗶𝘁𝘆 𝗼𝗳 𝗔𝗿𝗸𝗮𝗻𝘀𝗮𝘀 𝗳𝗼𝗿 𝗠𝗲𝗱𝗶𝗰𝗮𝗹 𝗦𝗰𝗶𝗲𝗻𝗰𝗲𝘀 (𝗨𝗔𝗠𝗦). He has been an integral part of projects focused on applying machine learning algorithms to diagnose diseases using eye conjunctive images.
Email:
Address:United States