The ultimate goal of science is to find the causes
behind complex phenomena
and to change systems at will
For example, one problem in molecular biology
is to understand and manipulate genes that are
the cause of complex diseases
The value of causal discovery has been known since ancient times.
Centuries ago, people asked why does the Sun shine everyday
or why things fall down
Today, we still ask all sorts of questions
such as why the universe has structure
or why some people develop diseases like cancer
What if you had a tool to reprogram cells to attack cancer?
Incredibly, all these questions are similar in essence
they are all related to a chain of cause and effect
that can be changed with access to the right information.
In this course, we will introduce a framework to properly ask and approximate, in some
sense, optimal answers to these questions from an algorithmic perspective
We will present established concepts and methods from mathematics
particularly the theories of computation and information
that can be used to unveil causes and steer systems
We will also have fun with our personal AI assistant, AlgoDyn
that will ask us questions throughout the course about everything you
wanted to know but you didn't dare to ask.
AlgoDyn will also answer some of your most pressing questions
for everybody to enjoy
We will explore surprising applications
to graphs and networks in areas such as biology
and, unlike mainstream tools in statistics and
traditional machine learning
the tools based on algorithmic complexity will
give us access to a set of methods
to find ultimate causes
to unveil generating mechanisms, and to produce
mechanistic models
fundamental in science.
For example, by using these tools, we have shown
that the human mind is
best equipped to produce randomness
when we reach the age of 25
The course will enable students
to view life from a computational perspective
and will empower them to use these powerful tools
in the form of a novel algorithmic calculus
to better understand and
manipulate complex systems
The course will have several units
the first ones devoted to the basics needed
to understand the more advanced topics.
The course itself will be self-contained
but it will be mostly devoted and driven by
results and research rather than based on a
textbook, so you will
experience the feeling of doing science.
Unlike other online courses,
here we will translate current cutting-edge
research into understandable and applicable knowledge today
We will introduce you to the use of our methods in the Wolfram Language.
You will learn to write your own code
and perform practical explorations
on networks, images, and biological data.
You will be able to apply all these ideas and methods to areas as diverse
as economics, psychology, ecology, physics,
chemistry, biology, and virtually any other area of science.
At the end of the course,
we will be giving away some
memorabilia from the London Mathematical Society,
also some books from Springer relevant to the course, and even some
Wolfram Mathematica licenses to people finishing
the course on top of their class
We hope that you enjoy our course.
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