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Algorithms I - Princeton - Coursera review

Jan 05, 2025 am 08:31 AM

Algorithms I - Princeton - Coursera review

This is a submission for the 2025 New Year Writing challenge: Retro’ing and Debugging 2024.

I started the Algorithms Part I course from Princeton University on Coursera, and I think the content is solid. I mean, it is literally taught by the guy who wrote THE book on algorithms, Robert Sedgwick.

The course covers most of what is needed to understand algorithms. It serves as a great guide to what you need to learn. However, I do have some qualms with how the course is taught and how the content is presented in the book.

Achievements Made

Taking this course allowed me to build a foundational understanding of algorithms. I became familiar with key concepts such as sorting, searching, and data structures like stacks and queues. Completing the assignments was a rewarding experience, as I had to push through initial confusion to arrive at working solutions. Additionally, learning to translate algorithms into JavaScript with the help of AI tools was a significant achievement that enhanced my programming versatility.

Lessons Learned

One of the most important lessons I learned is the value of breaking complex topics into manageable parts. By leveraging ChatGPT and Claude.ai, I was able to translate dense Java-based explanations into JavaScript, which I am more comfortable with. This process not only improved my understanding of the material but also showed me the importance of finding resources that complement my learning style. Another lesson was the importance of persistence—many algorithms seemed overwhelming at first but made sense with repeated exposure and practice.

Challenges Faced

First, the lectures were excruciatingly boring. Robert’s voice is so monotone that it became difficult to pay attention. Nowadays, content is often presented in visually engaging ways using striking graphics and interactive slides that clearly illustrate how an array is being rearranged or how nodes are connected. This course, however, simply displays a static slide for the duration of the lecture.

Secondly, the book is very text-heavy from start to finish, with complicated sentences. Since I was new to Java, that might have contributed to my struggle. I ended up using ChatGPT and Claude.ai to help break down the information. They translated the algorithms into JavaScript and explained the concepts step by step, which made them much easier to grasp.

Third, I’ve read that many of the algorithms in the course are implemented in a way that feels unnecessarily complicated. For instance, the course frequently uses while loops with true as a condition and then includes a lot of if statements with break inside. This style can be hard to follow and seems less than ideal.

Reflection

While this course is highly rated, I found it dull, and the book’s heavy text presentation didn’t help. That said, I am proud of the skills I developed through persistence and creative problem-solving. Perhaps once I’ve gained more experience with Java, I’ll revisit the course and approach it with a fresh perspective. Overall, this experience has reinforced the importance of tailoring resources to fit my learning style and using modern tools to bridge gaps in understanding.

If any of you read this far and are thinking of taking this course, feel free to drop a comment or if you have taken the course I'm curious to know your thoughts as well.

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