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Research Simulation Essential; A Practical Approach

Introduction

Research Simulation Essentials: A Practical Approach is a hands-on course designed for students, researchers, and professionals who aim to simulate, model, and visualize research data using Python and MATLAB. The course integrates essential components of the research pipeline — including data preprocessing, data modeling, machine learning, deep learning, and advanced data visualization —to build accurate and insightful research simulations. Emphasis is placed on both scientific and applied domains, helping participants bridge theory with computational practice.

Objectives

  • Preprocess and clean complex datasets for simulation and analysis
  • Develop and test data-driven models using Python and MATLAB
  • Apply machine learning and deep learning techniques to research data
  • Create meaningful visualizations for research reporting and publications
  • Simulate real-world scenarios across various domains using computational methods
  • Build reproducible research workflows and simulation pipelines

Career Path

  • Research Associate / Analyst
  • AI/ML Research Assistant
  • Simulation Engineer
  • Academic Researcher (STEM fields)
  • PhD or Postgrad Project Developer
  • Research Publication & Thesis Automation Expert

Fee Structure Research Simulation Essential; A Practical Approach

Research Simulation Essential; A Practical Approach
Duration 12 Weeks
Total Semester 1
Total Package 20,000
At Admission Time 20,000
Additional Charges at the time of Admission 0
Examination Fee 0
Total Amount (At Admission) 20,000
Installment 0 * 2
Additional Charges at the time of Admission
Web Portal fee per year for Learning Management Syste 0
Library Security Fee (Refundable) 0
Student Card 0
Library & Magazine Fund 0
Total Additional Charges 0
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