Dr. Kyle Bradbury brings experience in machine learning and statistical modeling to energy problems. He completed his Ph.D. at Duke University, with research focused on modeling the reliability and cost trade-offs of energy storage systems for integrating wind and solar power into the grid. Kyle holds a M.S. in Electrical Engineering from Duke University where he specialized in statistical signal processing and machine learning, and a B.S. in Electrical Engineering from Tufts University. He has worked for ISO New England, MIT Lincoln Laboratories, and Dominion.
Coursera
Discover how to harness the full potential of Python for data science by mastering the Pandas library in this engaging course. Designed for those looking to refine their data analysis techniques, you'll learn essential skills like cleaning, sorting, and storing data effectively. This course is perfect for anyone aiming to become a proficient data scientist.
Coursera
Embark on a comprehensive introduction to Python programming designed for beginners. This course covers essential skills like algorithmic thinking, Python syntax, code testing, debugging techniques, and modular code development. Ideal for those new to coding who aspire to build a career in software engineering, web development, or data science.
Coursera
Embark on a journey to become proficient in Data Science with our beginner-friendly course focusing on NumPy, sets, and dictionaries. This course is designed for aspiring programmers looking to break into the dynamic field of data science. Whether you're aiming to be a data scientist, software developer, data analyst, machine learning engineer, data engineer, or database administrator, this course provides the essential skills needed to succeed.