There are some programming systems that allow construction of software without actually typing in code such as "Blocks" which you can see/try on trinket.io:
But such systems are intended to give an introduction to programming rather than for serious products and so don't usually support expert systems. In the example above you can switch to seeing your code in python.
Expert Systems, on the other hand, need a lot more than If..Else constructs, in fact most these days use a probabilistic approach given this information there is the percentage chance of ... - they generally need a lot of code and include the capability to be "trained" and are only considered "Expert" once they have been trained see Deep Learning.
That said the Python programming language is reasonably easy for a beginner to start making progress in and has a number of resources available for constructing expert systems or experimenting in deep learning that make it possible to construct an expert system with very few lines of coding on your part.
- SciKit Learn Machine Learning in Python
- Keras Deep Learning library for Theano and TensorFlow
- OpenCV Open Source Computer Vision includes modules for constructing such systems.
- PyCLIPS PyCLIPS is an extension module for the Python language that embeds full CLIPS functionality in Python applications.
- Rulu provides a Pythonic, declarative interface for building rule-based expert systems.
- Caffe Deep Learning Framework While Caffe itself isn’t a Python library, it does provide bindings into the Python programming language.
- Theano building blocks for neural networks
- Lasagne lightweight library used to construct and train networks in Theano
- Blocks a different one Blocks is a framework that helps you build neural network models on top of Theano.
Some examples in Python as can be seen in the PyImageSearch blog: