Expert Training

Data‑Driven Global Optimization Methods and Applications

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Learn data driven optimization methods to solve complex problems using mathematical models, algorithms, and real-world applications.

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Additional information

Additional information

Authors

Huachao Dong & Peng Wang & Jinglu Li

Publisher

Expert Training

Published On

2025-05-19

Language

English

File Format

16.81 MB, PDF

Rating

⭐️⭐️⭐️⭐️⭐️ 4.93

Description

 

Data Driven Global Optimization methods form the core of this advanced course, introducing learners to powerful techniques for solving complex, real-world optimization problems at scale. Designed for students, researchers, and professionals, this course blends theory with hands-on applications so that, from the very beginning, you understand not only what these methods are, but also why and how they are used across industries.

Course Overview

Modern decision-making increasingly relies on data. Therefore, this course focuses on global optimization methods that explicitly leverage data to guide search, improve efficiency, and enhance solution quality. Moreover, you will explore deterministic and stochastic approaches, surrogate-based models, and adaptive algorithms that scale to high-dimensional problems. As a result, you will gain a strong conceptual foundation while also building practical skills.

In addition, the course emphasizes applications in engineering, machine learning, economics, and operations research. Consequently, learners can immediately relate abstract methods to real optimization challenges. Throughout the course, instructors actively demonstrate how data transforms classical optimization into intelligent, adaptive systems.

What You Will Learn

  • Understand the principles of global optimization and why local methods often fail
  • Apply data-driven models such as surrogate functions and response surfaces
  • Analyze uncertainty, noise, and constraints in real-world optimization problems
  • Implement scalable algorithms for high-dimensional and expensive functions
  • Evaluate optimization performance using practical metrics and benchmarks

Furthermore, each topic builds progressively, so you can confidently advance from fundamentals to advanced applications.

Applications and Use Cases

Data-driven global optimization plays a critical role in many domains. For example, engineers use it to design efficient systems, while data scientists apply it to hyperparameter tuning in machine learning models. Similarly, economists rely on these methods for policy optimization under uncertainty. Because of this versatility, the skills you gain remain highly transferable.

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Who Should Enroll

This course suits graduate students, researchers, engineers, and professionals who want to solve complex optimization problems using data. Whether you aim to strengthen your academic background or enhance your industry skill set, this course equips you with practical, future-ready expertise. Ultimately, you will be prepared to tackle challenging optimization tasks with confidence and clarity.

Additional information

Authors

Huachao Dong & Peng Wang & Jinglu Li

Publisher

Expert Training

Published On

2025-05-19

Language

English

File Format

16.81 MB, PDF

Rating

⭐️⭐️⭐️⭐️⭐️ 4.93

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