Workshops and Seminars

Open source scientific computing environments built around the Python programming language have expanded rapidly in recent years. They now form the dominant paradigm in artificial intelligence and many fields within the natural sciences. Economists can greatly enhance their modeling and data processing capabilities by exploiting Python's scientific ecosystem. This course will cover the foundations of Python programming and Python scientific libraries, discuss their connection to economic applications, and also investigate how Python is being used as the major language of AI.

The recent surge in artificial intelligence research and investment has driven emergence of groundbreaking scientific computing environments in recent years, each equipped with advanced features like automatic differentiation, parallel computing capabilities, and just-in-time compilation. This workshop will deliver a concise survey of these evolving AI-driven computational tools and explore their potential applications within economic research and analysis, demonstrating how the accelerated pace of AI development is creating new opportunities for computational economics.

Several important new scientific computing environments have appeared in recent years, generated by demand from and investment in artificial intelligence. This workshop will provide a brief overview of these environments and their features, including automatic differentiation, parallel computing, and just-in-time compilers. We will discuss how these tools might be applied to economic applications.

Several important new scientific computing environments have appeared in recent years, generated by demand from and investment in artificial intelligence. This workshop will provide a brief overview of these environments and their features, including automatic differentiation, parallel computing, and just-in-time compilers. We will discuss how these tools can be applied to a range of economic applications. When possible, attendees should bring laptops to the seminar.

Several new open source scientific computing environments have appeared in recent years, generated by demand from and investment in artificial intelligence and related fields. Economists can greatly enhance their modeling and data processing capabilities by exploiting these new computational tools. This workshop will provide a brief overview of core topics, including automatic differentiation, parallel computing, and just-in-time compilers. We will discuss how these tools can be applied to a range of economic applications.

Open source scientific computing environments built around the Python programming language have expanded rapidly in recent years. They now form the dominant paradigm in artificial intelligence and many fields within the natural sciences. Economists can greatly enhance their modeling and data processing capabilities by exploiting Python's scientific ecosystem. This course will cover the foundations of Python programming and Python scientific libraries, as well as showing how they can be used in economic applications for rapid development and high performance computing.

Open source scientific computing environments built around the Python programming language have expanded rapidly in recent years. They now form the dominant paradigm in artificial intelligence and many fields within the natural sciences. Economists can greatly enhance their modeling and data processing capabilities by exploiting Python's scientific ecosystem. This course will cover the foundations of Python programming and Python scientific libraries, as well as showing how they can be used in economic applications for rapid development and high performance computing.

This workshop will give an overview of Python's high performance computing capabilities and how they can be used for economic modeling. We will cover JIT compilers, automation differentiation, cloud computing and GPUs. Attendees should bring their own laptop, but no software installs are necessary.

This workshop will give an overview of Python's high performance computing capabilities and how they can be used for economic modeling. We will cover JIT compilers, automation differentiation, cloud computing and GPUs. Attendees should bring their own laptop, but no software installs are necessary.

Computational methods and scientific computing are becoming increasingly central to research, analysis and policy work in economics, finance and social science.

This is an introductory workshop for students and policy makers who are interested in learning about the evolution of modern scientific computing tools and how they can be applied to economic problems. The main language used in the workshop will be Python, although other languages will also be discussed.

Topics will include simulation, vectorization, JIT compilers, and parallelization.

Computational methods and scientific computing are becoming increasingly central to research, analysis and policy work in economics, finance and social science.

This is an introductory workshop for students and policy makers who are interested in learning about the evolution of modern scientific computing tools and how they can be applied to economic problems. The main language used in the workshop will be Python, although other languages will also be discussed.

Topics will include simulation, vectorization, JIT compilers, and parallelization.

Computational methods and scientific computing are becoming increasingly central to research, analysis and policy work in economics, finance and social science.

This is a workshop for students and policy makers who are interested in learning about the evolution of modern scientific computing tools and how they can be applied to economic problems. The main language used in the workshop will be Python, although other languages will also be discussed. Topics will include simulation, vectorization, JIT compilers, and parallelization.

This is the homepage for the QuantEcon scientific and high performance computing workshops to be held at the Central Bank of Chile in September 2022.