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  • Drones for Agriculture: Prepare and Design Your Drone (UAV) Mission

    Drones for Agriculture: Prepare and Design Your Drone (UAV) Mission

    Description We are all getting familiar with the image of a drone in the sky. Although flying a drone is fun, drones are not toys. More and more UAVs or drones are used by governments and companies to gain answers and insights on nature, agricultural and metropolitan challenges among other fields. For example, small Drones/UAVs…

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  • Linear Algebra – Foundations to Frontiers

    Linear Algebra – Foundations to Frontiers

    Description Linear Algebra: Foundations to Frontiers (LAFF) is packed full of challenging, rewarding material that is essential for mathematicians, engineers, scientists, and anyone working with large datasets. Students appreciate our unique approach to teaching linear algebra because: It’s visual. It connects hand calculations, mathematical abstractions, and computer programming. It illustrates the development of mathematical theory.…

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  • Death 101: Shaping the Future of Global Health

    Death 101: Shaping the Future of Global Health

    Description This global health and life sciences course enables learners to investigate health problems affecting large populations – the whole world in fact! By understanding the big numbers in global mortality and their causes and distributions you will learn how to think numerically about global health. We will use real data from real people to…

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  • String Processing and Pattern Matching Algorithms

    String Processing and Pattern Matching Algorithms

    Description The world and internet are full of textual information. We search for information using textual queries and read websites, books and e-mails. These are all strings from a computer science point of view. To make sense of all this information and make search efficient, search engines use many string algorithms. Moreover, the emerging field…

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  • Quantitative Biology Workshop

    Quantitative Biology Workshop

    Description Do you have an interest in biology and quantitative tools? Do you know computational methods but do not realize how they apply to biological problems? Do you know biology but do not understand how scientists really analyze complicated data? 7.QBWx: Quantitative Biology Workshop is designed to give learners exposure to the application of quantitative…

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  • Biochemistry: Biomolecules, Methods, and Mechanisms

    Biochemistry: Biomolecules, Methods, and Mechanisms

    Description Do you want to prepare for medical school, study a STEM field, become a research scientist, or transition to a career in the booming biotechnology industry? Or maybe you just want to understand the chemical reactions that govern life itself. Join Professor Yaffe, an MIT professor and practicing surgeon, as he guides you through…

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  • Introduction to Probability

    Introduction to Probability

    Description Probability and statistics help to bring logic to a world replete with randomness and uncertainty. This course will give you tools needed to understand data, science, philosophy, engineering, economics, and finance. You will learn not only how to solve challenging technical problems, but also how you can apply those solutions in everyday life.With examples…

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  • Statistical Inference and Modeling for High-throughput Experiments

    Statistical Inference and Modeling for High-throughput Experiments

    Description In this course you’ll learn various statistics topics including multiple testing problem, error rates, error rate controlling procedures, false discovery rates, q-values and exploratory data analysis. We then introduce statistical modeling and how it is applied to high-throughput data. In particular, we will discuss parametric distributions, including binomial, exponential, and gamma, and describe maximum…

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  • Introduction to Linear Models and Matrix Algebra

    Introduction to Linear Models and Matrix Algebra

    Description Matrix Algebra underlies many of the current tools for experimental design and the analysis of high-dimensional data. In this introductory data analysis course, we will use matrix algebra to represent the linear models that commonly used to model differences between experimental units. We perform statistical inference on these differences. Throughout the course we will…

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  • Statistics and R

    Statistics and R

    Description We will learn the basics of statistical inference in order to understand and compute p-values and confidence intervals, all while analyzing data with R. We provide R programming examples in a way that will help make the connection between concepts and implementation. Problem sets requiring R programming will be used to test understanding and…

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