Courses
30+ Coursera courses alongside my degree. These are the specializations and individual courses that shaped my interests most, in my own words, with verification links where Coursera provides one.
In this specialization I focused on creating robust embedded solutions, starting with the fundamentals of embedded hardware and operating systems. I then explored web connectivity and security measures essential for protecting embedded systems from vulnerabilities. My studies included the development of real-time systems to ensure timely and reliable responses in critical applications. In the capstone project, I applied these principles to create an autonomous runway detection system for IoT, demonstrating my ability to integrate security and functionality in embedded systems. This specialization honed my problem-solving skills and prepared me for advanced tasks in both academic and industrial settings.
In my IoT specialization, I delved into the fundamentals of the Internet of Things and embedded systems. I explored the Arduino platform, mastering C programming and interfacing techniques to build responsive hardware projects. I also studied the Raspberry Pi, learning Python to create versatile applications and interact with various sensors and actuators. The capstone project allowed me to integrate these skills, resulting in the design and deployment of a unique IoT device. This practical experience involved programming microcontrollers and connecting them to control and monitor the physical world, equipping me with the expertise to develop innovative IoT solutions.
This specialization spans four courses, providing a thorough exploration of IoT technology. Beginning with IoT Devices, I gained familiarity with foundational concepts and practical experience through a project simulating a vehicular network. Advancing to IoT Communications, I delved into RF communication, mesh networking, and distributed algorithms to enhance device connectivity. In IoT Networking, the focus shifted to enterprise IoT, addressing challenges in network infrastructure and protocols crucial for device connectivity to the internet. Finally, in IoT Cloud, I explored decentralized network topography and essential cloud technologies with an emphasis on security infrastructure.
Finishing this course, led by Professors Shimon Schocken and Noam Nisan, was a transformative experience. It covered the entire spectrum of computer science, starting with the fundamentals of Boolean Logic and Sequential Logic, progressing through Small Scale Integration, Computer Architecture, Assemblers, Virtual Machines, Compilers, Operating Systems, and Applications. What made it exceptional was the hands-on nature of the course, actually designing and constructing these components. It gave me a profound understanding of how computers work, equipping me with invaluable knowledge to navigate the complex world of modern computing.
This course, led by instructor Shawn Hymel, was a valuable and comprehensive introduction to the exciting fields of embedded machine learning and computer vision. It covered essential topics such as feature extraction, model training, model evaluation, and anomaly detection, along with the practical aspects of deploying machine learning models on embedded systems. The exploration of Convolutional Neural Networks for image classification, plus concepts like data augmentation and transfer learning, gave a well-rounded understanding of computer vision techniques, and the introduction to object localization, detection, and segmentation made it a great foundation for anyone starting out in these fields.
As part of this specialization I worked on a hands-on project that involved taking a location as input, using APIs to retrieve its coordinates, storing the data in a SQL database, and presenting it on a Flask API-powered map. This project reinforced my Python skills and showed how to seamlessly integrate different technologies into one working solution. Skills covered included data structures, web scraping (urllib, sockets, Beautiful Soup), RESTful APIs, relational databases (sqlite3), and data visualization.
This specialization covers a comprehensive range of topics essential for understanding and implementing cybersecurity measures effectively. It begins with incident detection and response, detailing the lifecycle of an incident and the tools needed to document and manage one, then moves into the foundations of a security career, core skills, and job responsibilities. It advances into practical automation with Python for security tasks, understanding assets, threats, and vulnerabilities, and risk mitigation using frameworks like NIST, alongside Linux, SQL, network fundamentals, and CISSP domains for managing security risk.