Welcome to Forethought India One-on-One Courses. Our program is designed to provide students with the skills and knowledge necessary to excel in their chosen profession. Our instructor for this course is Researcher Pramit Saha at University of Oxford.
"Magnetism Mastery: Fundamentals and Applications" is a comprehensive course designed to provide a deep understanding of magnetism, from its foundational principles to its diverse and innovative applications. Over the course of multiple engaging lectures, students will delve into the core concepts of magnetism, exploring topics such as magnetic fields, properties of magnetic materials, electromagnetic induction, and the mathematical foundations of Maxwell's equations. As the course progresses, it delves into advanced subjects like magnetic resonance imaging (MRI), electromagnetic waves, superconductivity, biomagnetism, and even the fascinating field of spintronics. The course also covers the practical applications of magnetism in technologies ranging from medical diagnostics and transportation systems to data storage and particle accelerators. With an emphasis on both theory and real-world relevance, this course equips learners with the knowledge and skills necessary to harness the power of magnetism in various scientific and technological domains. Whether you're a novice or a seasoned professional, "Magnetism Mastery" will enrich your understanding of this captivating field and empower you to contribute to cutting-edge innovations.
At the end of the program, students will receive a certificate & performance letter by the eductor indicating that they have completed the program and acquired the necessary skills and knowledge to excel in their chosen profession.
Magnetism Mastery: Fundamentals and Applications, by Pramit Saha at Oxford
Pramit Saha is a 3rd year doctoral candidate in the Oxford Biomedical Image Analysis (BioMedIA) cluster, Department of Engineering Science, at the University of Oxford. He completed Master of Applied Science from the Electrical and Computer Engineering Department, University of British Columbia, Vancouver. His research interest centers around Deep Learning (particularly self-supervised/semi-supervised/federated/domain adaptation), Computer Vision, Medical Image Analysis, and Neural Motor Control.