Name: Hate Data Structures And Algorithms? Turn It Into A Habit
Uploaded: 2022-04-19
Duration: 1 min 8 s
Description: Set aside 30 minutes, 2-3 times a week, to build a regular habit out of learning data structures and algorithms

Hate Data Structures And Algorithms? Turn It Into A Habit

Set aside 30 minutes, 2-3 times a week, to build a regular habit out of learning data structures and algorithms.

Related resources:
- [[Taro Top 10] Effective Interview Prep](https://www.jointaro.com/playlist/HLBYxJI7D1j8STolrwum/)
- [[Taro Top 10] Finding A Tech Job](https://www.jointaro.com/playlist/E6R0wVJ5EyCfVnVrlfno/)

Set aside 30 minutes, 2-3 times a week, to build a regular habit out of learning data structures and algorithms

The computer science concept we all love to hate. However, it is vital to master them to pass tech interviews, especially those at Big Tech.

Tech has one of the highest rates of job switching, making this skill incredibly high-leverage and vital to master. Understand what it takes to convince companies you are strongly competent.

[Masterclass] How To Ace Your Big Tech Interview - Data Structures And Algorithms

Data structures and algorithms (often abbreviated as "DSA") is an infamous staple of the software engineer interview experience. Data structures and algorithms problems are the most well-known for being part of the FAANG interview process, especially for Google.

Here are our Top 5 favorite points from this masterclass (in no particular order):
- **DSA prep is insanely high ROI** - In fact, the return on investment for time spent on DSA studying makes it one of the highest yield activities any human can do period. If you haven't worked at FAANG / Big Tech before, switching into it is likely to increase your pay by 50%+. If you're in the US, this will often mean a raise of $50k+. So the next time you're feeling burnt out from DSA studying, keep this very bright light at the end of the tunnel in mind.
- **Leetcode and Glassdoor are all you need** - DSA studying is a solved problem. You can use other, newer tools if you want, but the old-school ones still work just fine. Glassdoor in particular is naturally very effective given the "Big" nature of "Big Tech". Go through the recent data points from Glassdoor if you're interviewing for Big Tech and make sure you have a good grip on recurring recent problems.
- **Learning DSA is all about pattern recognition** - For 80%+ of DSA problems, there will be some 1-2 liner "trick" that represents the whole solution. For example, the "trick" to 2 sum is "Look for the difference and use a set/dictionary". It is not scalable to memorize solutions as code - Look for patterns and remember solutions as that high-level insight.
- **Communicate, communicate, communicate** - Since FAANG companies are so huge, there are naturally going to be far more stakeholders on every project, making alignment far more important. Because of this, Big Tech companies will often closely judge your communication skills during the interview. Don't just code in silence - Even if you get the right answer, you may still fail for not maintaining a dialogue with your interviewer.
- **Don't forget about space** - Most people are aware of big O run-time complexity, but candidates often forget about space complexity. Make sure to talk about both when you analyze your solution. As a side note, remember that a recursive solution will *not* be O(1) space.

Related resources:
- [How Alex Got Into Meta With 0 Prior Leetcode Experience](https://link.jointaro.com/SbNwqoPDmroJTsE37)
- ["How do I balance my time between studying DSA and fleshing out my portfolio?"](https://link.jointaro.com/7dw5k5yheTK5qx2D7)
- ["Should I quit to prep for interviews?"](https://link.jointaro.com/xgiQFNmwS7QgBUdV7)
- [Presentation slides](https://docs.google.com/presentation/d/13uLUHDvZifjp2aVClGsW29nfuVpQYvrkGLP8cej0R_k/edit#slide=id.p)