See organizers’ website for details Overview  A brief history of ANNs (Artificial Neural Networks) and an explanation of the intuition behind them. This part aims to give the audience a conceptual understanding with few mathematical barriers, and no programming requirements. Step-by-step construction of a very basic ANN. Although the code will be written in Python, it will be intuitive enough for programmers of other languages to follow along. Using the popular Python library scikit-learn, an ANN will be implemented on a classification problem. High-level libraries reduce the work for a researcher implementing ANN down to tuning a set of parameters, which will be explained in this part. Prior knowledge: D-Lab's Python for Everything or R Fundamentals and an interest in machine learning. Technology requirement: To follow along in parts 2 and 3, it is suggested to install Python via Anaconda. Instructions can be found here.

See organizers’ website for details In this workshop, Digital Learning Services staff will share the top tips we've gleaned from our combined decades of experience supporting faculty and instructors with DIY media content. We'll cover everything from setting up your recording space to utilizing free tools and resources to maximize your digital media workflows. If you’re an instructor looking to create video or audio content for online lectures, flipped classroom activities, blended learning materials, tutorial videos, this workshop is for you.

See organizers’ website for details Mike Holmes is CSO of Ambys Medicines, a Bay Area company pioneering the novel application of cell and gene therapies to reverse liver disease progression and restore liver function. Prior to Ambys, Mike worked at Sangamo, most recently as its senior vice president and chief technology officer. Mike received his Ph.D. in molecular and cell biology from the University of California, Berkeley, and he completed postdoctoral training in the lab of Gerald Rubin.