This paper studies event-triggered consensus control for heterogenous nonlinear multi-agent systems. We present a new distributed nonlinear event-triggered control algorithm integrating basic radial basis function neural network with event-based control. We show that it can handle any unknown dynamics linear in the control input, achieving practical consensus without Zeno behaviour. A numerical example is provided to highlight the effectiveness of the proposed algorithm in terms of learning the unknown nonlinear dynamics.