To someone like me, i.e. me, who knows nothing of this, and never heard of Einstein's field equations before, wikipedia looks actually useful.
It is an equation between two tensors of type (0,2). (I have been calling them type (2,0)), i.e. 2-covariant tensors, linear combinations of dx^j(tens)dx^k.
Since the dot product is such a tensor, I think of such a tensor as a generalization of a dot product, i.e. a generalization of a Riemannian metric. Since it defines a bilinear pairing on pairs of tangent vectors, it tells us something about the shape of space.
The left side is a sum of two terms, each of which is derived from the given Riemannian metric on space, more precisely it is entirely determined (up to some constant multipliers) by that metric and its first and second derivatives. Thus the left side is a certain measure of the geometric curvature of space.
This is set equal to a tensor on the right side that is called the "stress-energy" tensor, something apparently determined by matter, radiation, and force fields, in space(time). Thus the equation says a certain geometric measure of the shape of space(time) is determined by the physical attributes or content of space(time).
This equation involves three tensors, so to understand it, one should address each one of them individually. One of the tensors is just (a scalar multiple of) the Riemannian metric tensor, so the first place to start is understanding that.
Then the second tensor on the same side, is the "Einstein" tensor, which is determined by the metric, and its first and second derivatives. It involves a certain "averaging" of the Riemann curvature tensor. I.e. it is a sum of the "Ricci" curvature, and the "scalar" curvature multiplied by the metric. Both of these curvatures are computed as a sort of "trace" starting from the Riemann curvature tensor.
I.e. thinking of that Riemann curvature tensor as a sort of matrix whose entries are bilinear forms, the Ricci curvature is the trace of that matrix, hence itself a bilinear form. Then thinking of that bilinear form as the composition of the metric with a linear map in the first variable, one further takes the trace of that map, a scalar.
In coordinates, one gets the (0,2) Ricci curvature as a contraction of the (1,3) Riemann curvature; and then one gets a scalar by further contracting this (0,2) tensor against the "inverse" of the metric (0,2) tensor, which apparently makes it a (2,0) tensor.(?) [as a mathematician, it looks to me as if matrix transposes are involved, rather than matrix inverses.]
Apparently, the thing to focus on, after the metric tensor, is the Riemann curvature tensor, and then its descendants, the Ricci and scalar curvatures. Finally one would study the stress -energy tensor.
I would suggest studying closely the covariant derivative, and how it leads to the Riemann curvature operator, and finally how that operator is expressed using tensor notation. I.e. in a sense, tensors are just a notation to express this concept, and understanding the concept seems to be the more crucial matter.
To a simple person like myself, second order mixed partial derivatives are equal in flat Euclidean space, but not in curved space. Thus the difference in the values obtained by taking second derivatives in different orders in two given directions, measures curvature of space in the direction of the plane they span.
A careful, intrinsic, elaboration of this idea, using "covariant derivatives", defines the Riemann curvature operator, which can be expressed as a tensor of "type (1,3)", hence contracts to a tensor of type (0,2), and further, using the metric, to a scalar.
As a quick check on the equations, what happens if the space is geometrically flat? Then it seems the Einstein tensor is zero, since it measures the curvature. Thus the left side seems to reduce to a constant multiple of the metric. What then is the right side, the stress energy tensor? Why is it also a multiple of the metric?
Apologies for posting on something I do not know anything at all about. This is obviously just speculation. Thanks to you all for introducing me to what tensors are used for in real life.