My Journey as an Accelerated Master’s Student at George Mason University
As I approach the end of my second semester in George Mason University’s Bachelor’s Accelerated Master’s (BAM) program, I am reflecting on the exciting and challenging experiences I have had in the past few months. As a transfer student from Bennett University in India, BAM has allowed me to save a year by starting my master’s in my senior year of undergrad. This semester, I have taken courses in Natural Language Processing, Computer Vision, Engineering Seminars, Internet of Things, and Computer Network Architecture and Protocol. In this post, I want to share my experiences from the spring semester.
In the Natural Language Processing course, I learned how to create machine learning-based NLP models for text creation, question answering, and multilingual NLP. I also researched ChatGPT to better understand NLP and its applications. This education has prepared me for complex problems in the NLP sector.
The Computer Vision course taught me practical skills, such as generating panoramic images, making 3D reconstructions, and identifying objects during training. I also learned how to critically evaluate research articles and use technologies such as Blender. Overall, this course provided me with a solid foundation for future studies and employment in computer vision.
I completed a career development course in Electrical and Computer Engineering, which gave me insights into career paths, continuous education, new engineering advancements, professionalism, and financial planning. I also improved my presenting and interviewing skills and expanded my professional network.
The IoT course provided me with a broad understanding of the ideas, technologies, and challenges involved in developing IoT solutions, including sensors, microcontrollers, communication protocols, networking, and cloud computing. This course provided me with a solid foundation for further studies in the field.
In the Computer Network Architecture and Protocol course, I learned about the terminologies, functions, and principles of network elements, communication methods, network topologies, performance metrics, protocols, and standards. This course equipped me with the knowledge and skills needed to evaluate and build network systems.
I also participated in various projects, including a waste management system, emotion detection through the visual bag of words, a research paper on network intrusion detection using Generative Adversarial Networks, and a research article on GPT.
Furthermore, I had the opportunity to participate in a hackathon at the University of Maryland. My teammates and I worked on a project called “BitTales,” which used CockroachDB and machine learning techniques to analyze user behavior on social media platforms. Our project received recognition in two categories: “Best Use of CockroachDB” and “Best ML Hack.” This experience allowed me to apply my skills in a practical setting and enhance my teamwork and problem-solving abilities. Overall, it was a valuable experience that I am proud to have been a part of.
