SNUx: Introduction to Optimization
|
A self-contained course on the fundamentals of modern optimization with equal emphasis on theory, implementation, and application. We consider linear and nonlinear optimization problems, including network flow problems and game-theoretic models in which selfish agents compete for shared resources. We apply these models to a variety of real-world scenarios.
About this course
A self-contained course on the fundamentals of modern optimization with equal emphasis on theory, implementation, and application. We consider linear and nonlinear optimization problems, as well as closely related fields such as network flow models and game-theoretic models in which selfish agents compete for shared resources. We apply these models to real-world scenarios such as routing problems in urban railway management.
The first four weeks of the course consider linear programming (LP). LP is the most fundamental example of convex programming. Despite its simplicity, a wide range of practical problems can be formulated using LP, and LPs can be solved using efficient algorithms, meaning that LP is of both theoretical and practical importance. We highlight this point in week 3, when we examine the relation between the duality theories of LP and classic problems in game theory, such as the minimax theorem, and study the relationship between solving optimization problems and predicting how rational agents participate in competitive games. In week 4, we explore the minimum cost flow problem, a fundamental network model, and how the simplex method can be tailored to its unique features. Weeks 5 through 7 consider nonlinear, especially convex, optimization problems, also known as nonlinear programs (NLP). We derive the optimality criteria for NLP, and through them understand the connection between LP and NLP. We look at a variety of solution algorithms for NLPs with and without constraints.
Finally, in week 8, we put everything together to solve a game-theoretic problem called the routing problem. We simulate a modern subway system, with selfish agents who compete to minimize their travel costs, and use this model to predict the impact of new railway construction on train congestion.
At a Glance:
Institution: SNUx
Subject: Computer Science
Level: Introductory
Prerequisites:
None
Language: English
Video Transcript: English
Associated skills:Natural Language Processing, Forecasting, Algorithms, Convex Optimization, Nonlinear Programming, Network Flow, Linear Programming, Simplex Algorithm, Game Theory, Network Model, Network Routing
User Reviews
Be the first to review “SNUx: Introduction to Optimization”
Related Products
Microsoft Cognitive Services: Bing Autosuggest
Providing a real-time search experience for your users by suggesting terms as they type can set your app apart! Bing Autosuggest makes those terms intelligent based off of machine learning and geolocation. Find out how to use it in this course.
Advanced NLP with spaCy
Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.
LinuxFoundationX: Data and AI Fundamentals
Learn the fundamentals of Artificial Intelligence with a combination of AI fundamentals and an overview of the rich Linux Foundation AI & Data projects ecosystem. It is well-suited for any kind of AI adopter, regardless of the professional background and level of technical knowledge.
UMontrealX: Deep Learning Essentials
Do you want to learn how machines can learn tasks we thought only human brains could perform? Then take this Deep Learning course developed by IVADO, Mila and Université de Montréal: an extensive overview of the essentials of deep learning, this ground-breaking technology already prevalent in our lives and spanning all sectors.
Introduction to Large Language Models
This is an introductory level micro-learning course that explores what large language models (LLM) are, the use cases where they can be utilized, and how you can use prompt tuning to enhance LLM performance. It also covers Google tools to help you develop your own Gen AI apps.
Microsoft Azure Cognitive Services: Translator Text API
Are you looking to quickly add the capabilities of AI-based language translation? Look no further than the powerful Azure Cognitive Services APIs. This course will show you how you can easily add them to your application.
There are no reviews yet.