CS106A Programming Methodology | Introduction to the engineering of computer applications emphasizing modern software engineering principles: program design, decomposition, encapsulation, abstraction, and testing in the Python programming language.
CS230 Deep Learning | Learned the foundations of Deep Learning, how to build neural networks, and how to lead successful machine learning projects. Topics covered include: Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more.
CEE 260D Remote Sensing of Hydrology | Topics covered include the hydrologic cycle, relevant sensor types and the electromagnetic spectrum, active/passive microwave remote sensing (snow, soil moisture, canopy water content, rainfall), thermal sensing of evapotranspiration, gravity and hyperspectral methods, as well as an introduction to data assimilation and calibration/validation approaches for hydrologic variables.
ESS 239 Data Science for Geoscience | This course provided an overview of the most relevant areas of data science (applied statistics, machine learning & computer vision) to address geoscience challenges, questions and problems. Using actual geoscientific research questions as background, principles and methods of data scientific analysis, modeling, and prediction were covered. Data science areas covered include: extreme value statistics, multi-variate analysis, factor analysis, compositional data analysis, spatial information aggregation models, spatial estimation, geostatistical simulation, treating data of different scales of observation, spatio-temporal modeling (geostatistics). Application areas covered include: process geology, hazards, natural resources.
CEE 266F Stochastic Hydrology | This course introduced the statistical methods used in hydrology for data analysis, risk and uncertainty analysis, and simulation. Topics include: flood and drought frequency, time series analysis, rainfall-runoff modeling, and lake water quality. Methods include: applied probability theory, extreme value theory, parameter estimation, regression, time series analysis, transfer functions, Bayesian methods.
CEE 265A Resilience, Sustainability and Water Resource Development | Sustainability and resilience concepts are illustrated using cases studies involving water development agencies in the US and other counties. These studies illustrate the role of political, social, economic, and environmental factors in decision making. Topics include multipurpose dams, structural and non-structural flood control measures, and drought management strategies. The course also examines the work of international aid organizations and NGOs in promoting sustainability and resilience in water resources development.
CEE 266A Watersheds and Wetlands | Introduction to the occurrence and movement of water in the natural environment and its role in creating and maintaining terrestrial, wetland, and aquatic habitat. Hydrologic processes, including precipitation, evaporation, transpiration, snowmelt, infiltration, subsurface flow, runoff, and streamflow. Rivers and lakes, springs and swamps. Emphasis is on observation and measurement, data analysis, modeling, and prediction.
CEE 278A Air Pollution Fundamentals | The sources and health effects of gaseous and particulate air pollutants. The influence of meteorology on pollution: temperature profiles, stability classes, inversion layers, turbulence. Atmospheric diffusion equations, downwind dispersion of emissions from point and line sources. Removal of air pollutants via settling, diffusion, coagulation, precipitation, Mechanisms for ozone formation, in the troposphere versus in the stratosphere. Effects of airborne particle size and composition on light scattering/absorption, and on visual range.