Courses tagged with "Nutrition" (6413)

This is a graduate course on the design and analysis of algorithms, covering several advanced topics not studied in typical introductory courses on algorithms. It is especially designed for doctoral students interested in theoretical computer science.

Advanced Analytic Methods in Science and Engineering is a comprehensive treatment of the advanced methods of applied mathematics. It was designed to strengthen the mathematical abilities of graduate students and train them to think on their own.

Ready to level-up your skills as an Android developer? In this course, you will learn how to make your app production-ready by developing a variety of different sample apps, each designed to showcase advanced capabilities of the Android platform, including fragments, widgets, media playback, and testing. You’ll learn how to create UI tests using the Espresso framework, to leverage third-party libraries and services like ExoPlayer and Firebase Cloud Messaging, and use Google APIs to make your app aware of its location. By the end of the course, you’ll know how to publish your own app to the Google Play Store, where you can reach and engage users across the globe.

The course includes survey and special topics designed for graduate students in the brain and cognitive sciences. It emphasizes ethological studies of natural behavior patterns and their analysis in laboratory work, with contributions from field biology (mammology, primatology), sociobiology, and comparative psychology. It stresses mammalian behavior but also includes major contributions from studies of other vertebrates and of invertebrates. It covers some applications of animal-behavior knowledge to neuropsychology and behavioral pharmacology.

Gain a deeper understanding of Spark by learning about its APIs, architecture, and common use cases.  This statistics and data analysis course will cover material relevant to both data engineers and data scientists.  You’ll learn how Spark efficiently transfers data across the network via its shuffle, details of memory management, optimizations to reduce compute costs, and more.  Learners will see several use cases for Spark and will work to solve a variety of real-world problems using public datasets.  After taking this course, you should have a thorough understanding of how Spark works and how you can best utilize its APIs to write efficient, scalable code.  You’ll also learn about a wide variety of Spark’s APIs, including the APIs in Spark Streaming. 

Biomass is the only renewable feedstock which contains the carbon atoms needed to make the molecules to create chemicals, materials and fuels. However, the majority of our current scientific and industrial knowledge on conversion is based on processing fossil feedstocks. In this course we explore the relevant fundamental knowledge on (bio)catalytic conversion in order to produce (new) biobased building blocks, chemicals and products.

The design of an effective (catalytic) process for the conversions of biobased feedstocks to desired products is the core of this course. Unique for bioconversion is the presence of the elements O,N, P, S and the large quantities of water.

We therefore will explore:

• microbial, biochemical and chemical (i.e., catalytic) conversion routes.
• how to use catalysts, either heterogeneous, homogeneous or biocatalysts function in order to optimize the process of conversion. We discuss how these catalysts can be tuned and their specific advantages and disadvantages for biobased conversions.
• the influence of the reactor choice as an inevitable asset in the process. We discuss how to describe the productivity of catalytic processes depending on the choice of the reactor and how the choice of the reactor can add to the stability of the conversion process.

The knowledge you gain allows you to design processes specifically targeted on biomass based conversions as well offering an opportunity to interact with chemist, engineers and scientists who mainly focus on the traditional fossil based conversions.

In a biorefinery a complex biobased feedstock is separated and processed in such a way that sustainability and application opportunities are maximized. In this course we will focus on tools and techniques to efficiently disentangle, separate and convert different biomass based feedstocks into simpler (functional) components.

First we will discuss available techniques and processes for biomass activation/disentanglement and separation.

Next we explore how to design a biorefinery taking into account feedstock and sustainable energy use. Therefore we will dive into:

• mass and energy balances;
• design of biorefinery process units to obtain multiple products from one type of biomass;
• how to recover energy and resources in the biorefinery system;
• evaluation of the designed system with respect to sustainability and economic criteria;
• evaluation of criteria for successful implementation (operational and investment costs).

This course analyzes the functions of a complex variable and the calculus of residues. It also covers subjects such as ordinary differential equations, partial differential equations, Bessel and Legendre functions, and the Sturm-Liouville theory.

Advanced Cardiac Life Support (ACLS) will prepare you to respond to life-threatening emergencies in the adult population with advanced interventions. This ACLS course is based on the latest guidelines, which focus on doing several tasks simultaneously as part of a group process that enables efficiency and minimizes error. At the completion of this course, students will be prepared to take the certification exam for Advanced Cardiac Life Support (ACLS).

5.33 focuses on advanced experimentation, with particular emphasis on chemical synthesis and the fundamentals of quantum chemistry, illustrated through molecular spectroscopy. The written and oral presentation of experimental results is also emphasized in the course.

Acknowledgements

The materials for 5.33 reflect the work of many faculty members associated with this course over the years.