There is a growing gap between how graduate students in psychology and neuroscience are trained and what they actually need to know to do cutting edge work. We see two fundamental issues driving this gap. First, most training programs do not expose students to the latest computational tools. Second, an even greater challenge is to supplement the traditional reductionist approach to studying the elements of brain, cognition, and behavior in isolation, to integrating how these elements interact as a cohesive complex system. This entails considering not just which elements in a network interact, but also the content of the interaction, and the dynamics of how this information flows through the network over time. This general issue is present in multiple domains, with an accompanying need for similar tools: neurophysiologists studying spiking activity in ensembles of single neurons, cognitive neuroscientists studying whole-brain activity levels, and social psychologists studying group interactions. Thus, our summer program aims to provide integrated training of network methods at the circuit, whole-brain, and social network levels. The overall format has short lectures in the morning, followed by hands-on tutorial-style labs, and a hackathon in which students will collaboratively work on projects with faculty. Themes running through the curriculum include open tools and data, data visualization, statistical modeling, and model comparison.