An Introduction to Optimization for STEM Students

🎉 Master the Art of Optimization with "An Introduction to Optimization for STEM Students" 📚

Course Overview: Dive into the fascinating world of optimization techniques that are essential for Science, Technology, Engineering, and Mathematics (STEM) students. This comprehensive course will equip you with a solid foundation in optimization methods, taught at an undergraduate level, and introduce you to the practical applications of these techniques using both Fortran90 and Python programming languages.

What You'll Learn:

• One-Dimensional Unconstrained Problems:

  • Newton and Secant Methods: Discover how these methods solve one-dimensional optimization problems efficiently.

  • Golden Search Bracketed Method: Learn this reliable method for finding maximum/minimum values in one dimension.

• Multi-Dimensional Unconstrained Problems:

  • Univariate Search Techniques: Explore methods to tackle more complex, multi-dimensional search spaces.

  • Steepest Ascent Method: Understand how this method navigates the multi-dimensional landscape to find the next step.

  • Newton’s Method for Multi-Dimensional Problems: Gain insight into extended versions of Newton's method suitable for multiple variables.

• Constrained Problems:

  • Lagrange Multiplier Method: Master the powerful technique to solve problems with both equality and inequality constraints.

Practical Applications & Tools:

• Solve real-world problems using optimization methods.
• Downloadable course notes to guide your learning journey.
• Access to fully functional computer codes in both Fortran95 and Python, ready for use, modification, or as a starting point for your projects.

Why Enroll?

• Expert Instruction: Learn from Robert Spall, an experienced instructor in numerical methods and optimization.
• Interactive Learning: Apply what you learn with practical examples that bring theory to life.
• Flexible Coding Practice: Choose your preferred programming language—whether it's Fortran90 or Python—and apply the concepts directly.
• Easy-to-Access Materials: Download course notes and codes to study at your own pace, on any device.

Who Should Take This Course? This course is designed for sophomore or junior level STEM students with a background in calculus and some programming experience, particularly in languages such as Fortran90, C, C++, Python, MatLab, etc. If you're looking to enhance your numerical methods skill set and apply optimization techniques in real-world scenarios, this course is for you!

🔍 Key Takeaways:

• Understand a variety of optimization algorithms and their applications.
• Apply numerical optimization methods in Python and Fortran90.
• Gain the confidence to tackle optimization problems in STEM fields.

Enroll Now to Secure Your Spot in This Invaluable Learning Experience! 🚀

Course Highlights:

• Foundational Knowledge: Covering essential optimization techniques for STEM students.
• Versatile Coding Skills: Learn through hands-on practice with Fortran95 and Python codes.
• Comprehensive Resources: Benefit from downloadable course notes and codes.
• Real-World Applications: Apply what you learn to solve actual problems in science, technology, engineering, and mathematics.

Don't Miss Out on the Opportunity to Elevate Your Skills with Optimization Techniques! 🎓

Module Breakdown:

1. One-Dimensional Unconstrained Problems

   • Newton and Secant Methods
   • Golden Search Bracketed Method

2. Multi-Dimensional Unconstrained Problems

   • Univariate Search Techniques
   • Steepest Ascent Method
   • Newton’s Method for Multi-Dimensional Problems

3. Constrained Optimization Problems

   • Lagrange Multiplier Method for Equality Constraints
   • Lagrange Multiplier Method for Inequality Constraints

4. Example Problems and Applications

• Solve problems using the methods covered in the course.

Ready to embark on this optimization journey? Click 'Enroll' to get started today! 🌟