Deep Theoretical Knowledge
One of the most important takeaways from my master’s degree was the deep theoretical knowledge that I acquired during my studies. Through courses such as stochastic information processing which taught me about Kalman Filters and their peers, control theory for MIMO-systems, courses about embedded system design as well as courses about actuation, sensing and processing in robotic systems, I gained a strong foundation in areas, that I never had thought of being able to understand beforehand.
Understanding the underlying principles and mathematical models allows me to tackle complex problems and approach them with a comprehensive perspective while also improving my confidence in my own technical abilities.
The Karlsruhe Institute of Technology (KIT), where I did my master’s degree, has a lot to offer and a plethora of very knowledgeable professors. If robotics and everything that surrounds it is your thing, check out KIT as a potential university.
Alongside theoretical knowledge, my studies provided lots of opportunities for hands-on experience. I had the time and opportunity to delve into FPGA development and machine learning on the edge with quantized neural networks.
These practical projects enhanced my understanding of real-world applications and enabled me to bridge the gap between theory and implementation. Working on these projects sharpened my technical skills, honed my problem-solving abilities, and exposed me to the challenges faced in industry settings.
During my master’s thesis, I had access to devices that cost thousands of dollars like oscilloscopes and thermal chambers which was an interesting experience.
Here, KIT, even though they had a relatively broad offer, tries to keep you inside the realms of theory. Only a relatively small amount of your total credit points is allowed to come from practicals and seminars, while most of it must come from lectures. Universities provide you with theory and for the most part, you will need to find your own practical applications for what you learn.
Dedication, Autonomy and Confidence
During my master’s degree, I encountered numerous challenges, including particularly demanding tests and the completion of a master’s thesis.
These experiences taught me the value of dedication and autonomy – and gave me the confidence that I can do things when I set my mind to it. Despite encountering difficult tests, I remained determined and resilient, putting in the necessary effort to overcome obstacles.
I can’t say it was always easy. There were times where I wanted to quit it all, I even had some interviews with companies and talked to student services but in the end, I pulled through. Now, that I have my diploma I understand that sometimes, you just must bite your teeth and pull through and that “not quitting” may be the best thing to do.
KIT has some easy courses to offer but I have never shied away from a challenge and their harder courses will definitely pick your brain. So, if you’re up for a challenge KIT might be for you.
Furthermore, working independently on my master’s thesis allowed me to cultivate self-reliance and boosted my confidence in my research and technical abilities. This combination of qualities has not only been essential to my academic success but will also be invaluable in my professional pursuits.
One crucial lesson I learned throughout my master studies was the significance of asking questions. As I had some computer background already, my bachelor’s wasn’t too difficult, and I can’t remember asking a single question during lectures.
Only during my bachelor’s thesis did I get the impression that I really don’t “know it all”, which made this a very difficult time. In a field as dynamic and ever-evolving as computer science, curiosity and a thirst for knowledge are vital.
By actively seeking clarification and asking questions during or after lectures and all throughout my master’s thesis, I was able to deepen my understanding of complex topics. Asking questions not only helped me grasp concepts more effectively but also fostered a collaborative learning environment. I was under the impression that, whenever I started asking questions, others would follow up with more question.
I didn’t shy away from asking “stupid” questions, as they often turned out to not be as uninformed as I thought them to be, and I felt like I gave others the opportunity to ask their “stupid” questions in turn which I often found interesting and gave a new perspective on the topic.
Most of the time, professors at KIT simply tried their best to answer the questions. There were times when they ridiculed students for their questions, which is a shame, but don’t let that turn you away from asking questions. It merely says something about the professor and nothing about the person asking the question.
The Path is not a Straight Line
When I started my master’s degree, I thought I had it all figured out. I created a whole plan on what courses I’d take in what semesters. I would have probably even asked a professor to give me a subject for a final thesis if I had had the guts. At KIT you must pick two majors from a list of 16 different topics, which do have some courses in common while differing in others.
But one semester after the other, the plan changed, I removed courses from my plan, added new courses and even changed one of my majors. As I got a better understanding of what I wanted, what I didn’t want and how the whole university system worked, I tailored the courses I took to what interested me the most, and even what interested me changed semester after semester.
Don’t get me wrong: Making that plan in the first place was very useful and I completed about 50% of it, but when I learned that I didn’t have to stick to it I gained a lot of freedom.
In conclusion, my master’s degree in computer science provided me with deep theoretical knowledge in various areas such as stochastic information processing, control theory, embedded system design, and robotics.
The hands-on experience I gained through projects and access to advanced devices enhanced my practical skills and problem-solving abilities. I learned the importance of dedication, autonomy, and gained confidence in overcoming challenges.
Asking questions and fostering a collaborative learning environment proved vital in deepening my understanding. Overall, my master’s degree equipped me with the necessary skills and knowledge to embark on a successful career in computer science and even though it was hard at times, I am glad I finished it.