Registration Fee: 500 INR / 25 USD

Last Date of Registration: 10 Nov. 2024

Event Date: 19-25 Nov, 2024 · 19:00-21:00 IST

Overview:

The Faculty Development Programme (FDP) aims to provide a comprehensive understanding of interdisciplinary applications of computing in both basic and applied sciences. Using MATLAB as the core tool, the program will introduce participants to numerical methods, simulation techniques, data analysis, machine learning, optimization, and more. This program is designed to enhance computational skills and promote interdisciplinary research in STEM fields.

Objectives:

• Equip faculty with advanced computational skills using MATLAB.
• Introduce interdisciplinary applications of computing in basic and applied sciences.
• Develop problem-solving skills using simulation and computational tools.
• Foster collaboration and knowledge sharing among participants from various disciplines.

Target Audience:

Faculty members, researchers, and professionals in STEM fields, including those from:

• Physics, Chemistry, Mathematics
• Biology, Environmental Science
• Engineering (Mechanical, Electrical, Civil, etc.)
• Computer Science

Topics to be Covered:

1. 1. Introduction to MATLAB for Scientific Computing
   • Overview of MATLAB environment and basic operations.
   • Matrix manipulations, plotting, and data visualization.
2. 2. Numerical Methods and Optimization
   • Solving equations, integration, differentiation.
   • Optimization techniques for applied problems in science and engineering.
3. 3. Interdisciplinary Applications of MATLAB in Basic Sciences
   • MATLAB for physics, chemistry, and biological systems simulations.
   • Solving ordinary and partial differential equations.
4. 4. Interdisciplinary Applications in Applied Sciences
   • MATLAB for engineering and technology solutions.
   • Signal processing, image processing, and control systems using MATLAB.
5. 5. Data Analysis and Visualization
   • Handling large datasets and performing statistical analysis.
   • Techniques for data visualization and interpretation in research.
6. 6. Machine Learning and AI with MATLAB
   • Basics of machine learning algorithms and their applications in science.
   • Hands-on exercises using MATLAB’s Machine Learning Toolbox.
7. 7. Simulations and Modeling for Real-world Problems
   • Implementing models for interdisciplinary problems in various fields.
   • Case studies: Environmental modeling, computational fluid dynamics, etc.

Organized by

MathTech Thinking Foundation, Fazilka, INDIA

About MTTF Click here