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## Problem-Solving with Julia - the SICP Way -
- A self-study guide with Pluto -

This is a personal learning-diary when exploring Julia by exploiing SICP. I used Lisp and especially Scheme regularly from time to time. I loved Scheme for its elegance and minimalism. But for production purposes in various scientic projects I had to use other languages for pragmatic reasons, like Fortran, Prolog, R, Javascript, Bugs, Stan, WebPPL and even Python. But I was always looking for a language as elegant as Scheme but with a greater usability and usefulness. Several year ago David Barber gave advice to give Julia a try. In the end I stumbled across the fascinating probabilistic programming languages Gen and Turing, both embedded in Julia. That was the starting point to deal with Julia to have a solid fundament for modeling in Gen and Turing.
This is a personal learning-diary when exploring Julia by exploiting SICP. I used Lisp and especially Scheme regularly from time to time. I loved Scheme for its elegance and minimalism. But for production purposes in various scientic projects I had to use other languages for pragmatic reasons, like Fortran, Prolog, R, Javascript, Bugs, Stan, WebPPL and even Python. But I was always looking for a language as elegant as Scheme but with a greater usability and usefulness. Several year ago David Barber gave advice to give Julia a try. In the end I stumbled across the fascinating probabilistic programming languages Gen and Turing, both embedded in Julia. That was the starting point to deal with Julia to have a solid fundament for modeling in Gen and Turing.

Here we present transpilations of SICP-Scheme-scripts into Julia as well as alternatives exploiting idiomatic JULIA constructs within a Pluto.jl-embedding. Pluto.jl offers reactive notebooks very suitable for educational purposes.

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