  This chapter is a tutorial on techniques and results in free convex algebraic
geometry and free real algebraic geometry (RAG). The term free refers to the
central role played by algebras of noncommutative polynomials R<x> in free
(freely noncommuting) variables x=(x_1,...,x_g). The subject pertains to
problems where the unknowns are matrices or Hilbert space operators as arise in
linear systems engineering and quantum information theory.
  The subject of free RAG flows in two branches. One, free positivity and
inequalities is an analog of classical real algebraic geometry, a theory of
polynomial inequalities embodied in algebraic formulas called
Positivstellens\"atze; often free Positivstellens\"atze have cleaner statements
than their commutative counterparts. Free convexity, the second branch of free
RAG, arose in an effort to unify a torrent of ad hoc optimization techniques
which came on the linear systems engineering scene in the mid 1990's.
Mathematically, much as in the commutative case, free convexity is connected
with free positivity through the second derivative: A free polynomial is convex
if and only if its Hessian is positive. However, free convexity is a very
restrictive condition, for example, free convex polynomials have degree 2 or
less.
  This article describes for a beginner techniques involving free convexity. As
such it also serves as a point of entry into the larger field of free real
algebraic geometry.
