Course 1: Data Analytics for COVID19 Research
This technology track course relates to learning to analyze ‘big data’ related to the COVID19 pandemic. The crisis arising from this pandemic has redefined our view of our world, and engineers have to understand it in order to solve problems as they arise. Conversely, public officials have been setting rules to ‘flatten the curve’, which has altered human activity and industrial progress. In this course, you will interact with raw data from COVID19-related online sources to learn about: (i) tracking the pandemic while minimizing societal harm, and (ii) conducting cost-benefit engineering analysis of human and industrial activity, including the environment (e.g. air and water quality). The skills learned will help participants explore data analytics, and technical decision making, while exploring how engineers apply these skills in healthcare analytics, big data, and cutting-edge research careers.
Course 2: Data Detectives – Learning data mining, data visualization, and data science in consumer markets
Ever wonder how retailers have enough inventory when you need it most? Applying the fundamentals of machine learning and statistics, we can use computer models to explore how markets change and potentially predict how different markets will perform. Over the course of the week, you will learn how to use R programming to visualize and analyze data in one of five markets. The markets of choice are sports, music, fashion, and/or commercial goods and services. Even while in high school, this course will teach you to think like an algorithmic CEO. You will learn skills in market research, data analysis, and statistical learning. This course will give you hands-on experience to understand how technology companies are using data to transform our world and consumer experiences.
Course 3: Deep Learning – Deploying AI and Python code to maintain Smart Cities
How will smart cities deploy image recognition technology to automatically find damaged buildings, bridges, and structures? They mix ‘big data’ with artificial intelligence (AI). This course will give you some basic skills in Python while learning to use computers to scan image data sets of when building, bridges, and other structures are damaged. It will also arm you with the knowledge to understand one of the hottest concepts in machine learning, called deep learning. Civil Engineers design, construct, and maintain infrastructure that allows society to function effectively. They also apply math and science to develop smart city solutions. In this project, you will design and implement a neural network algorithm capable of classifying images as damaged (easy) and then their corresponding damage level (difficult). Take this course to learn the same frontier AI techniques that ‘smart city’ engineers will employ in the field.
Course 4: Learning Python while solving mechanical engineering problems
This technology track course gives high school students early exposure to how mechanical engineers learn to code in Python to solve important engineering problems. For example, engineers develop computer codes to predict problems from how long iPhones can stay cool when processing to what’s the best new solar cell for this location. NASA, Tesla, and food companies like Proctor & Gamble have to be able to use computers to predict how heat flows through solid materials similar to how electrical current flows through wires. During this course, each student will learn how to solve thermal energy problems like a mechanical engineer. Students will develop their own Python code to model temperature changes when cooking meat. Using this code, students will be able to predict the amount of time needed for the meat to reach a safely cooked temperature. After the code development is complete, each student will have the opportunity to set up an experiment at home to test the temperature prediction of cooking meat and verify the code predictions. This type of work will give students real experience solving real engineering problems.
Course 5: Computational Modeling in Bioengineering
This technology track course introduces the student to how computer modeling can be applied in the field of bioengineering. The topics will include modeling of cell membranes, cell mechanics, and cell sensing. Some concepts which will be taught relate to how the hairs in our ears have sensors and help us to hear and maintain our balance. High school students will learn how to computationally model nerve function, e.g., advancing technologies to help the hearing impaired. Students will be exposed to how biomedical devices are designed and how bioengineering models can help tackle disease.
Course 6: 3D Solid Modelling and 3D Printing
This technology track course provides an introduction to the use of computer-aided design (CAD) for the engineering design processes. Computer-aided design (CAD) software is to be utilized to create solid and rapid prototyping (3D-printing) models. The course will introduce the basic principles that show how engineers using solid CAD modelling and 3D-printing to create new technologies and solve societal problems. For example, the lead instructor also leads the technology team at Rice University that is manufacturing personal protection equipment (PPE) for Houston healthcare workers. By taking this course, students will learn to design, conduct basic engineering analysis, and manufacture components with 3D printing technology.
Course 7: Internet of Things (IOT) with Machine Learning & Python
This course will focus on exposing students to Applied Machine Learning (ML) Concepts and the Internet of Things (IOT), by way of hands on modules that leverage real time sensors. Through this course, students will gain exposure to ML concepts, code examples in Python and MySQL, and deploy their code to a cloud environment for testing. The course will provide background knowledge and move directly in application. Students will walk away with understanding as to how each of these technologies are applied in Industry, as well as seeing the underlying connection to core subjects.
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