DSA Crash Course [Part 80] - Non Adjacent Sum Walkthrough

In this lesson, Alvin walks through the python implementation for the *non_adjacent_sum* problem.

Code along and test your work in the following editor workspace: <https://structy.net/problems/non-adjacent-sum?language=py>

If you need additional support taking these DSA skills and actually applying them, take [**Alvin's**](https://www.linkedin.com/in/alvin-zablan-b73a92117/) *complete* data structures and algorithms course on [**Structy**](https://structy.net/?utm_source=taro). You can try out the concepts yourself in their interactive code editor and learn advanced DSA patterns like stack exhaustive recursion.

Use [**this link to get 20% off**](https://structy.net/purchase?promo_code=taro20) the entire Structy DSA learning experience.

Follow Alvin on LinkedIn: [**https://www.linkedin.com/in/alvin-zablan-b73a92117/**](https://www.linkedin.com/in/alvin-zablan-b73a92117/)

Become A Debugging Master [Part 8] - Write Down All The Context

One of the easiest ways to massively speed up your debugging (and make yourself look way more senior) is simple: write things down early and often. Here are the core points from the lesson:

- Don’t wait for clarity to write—writing your thoughts down is what *creates* clarity and uncovers next steps
- Always document repro steps, failed attempts, blast radius info, and hypotheses while debugging
- Writing things down improves your retention, narrows the search area, gives credit to others, and makes handing off bugs much smoother
- Even half-baked notes are powerful because they build momentum, reduce confusion, and help you communicate progress to others effectively

Asking Great Questions [Part 21] - Follow The Golden Rule

There is no free lunch, and this is certainly the case when it comes to asking favors. Favors in the tech industry are often harder to get as well given that they're higher leverage: A strong referral or a 1 on 1 meeting could easily be worth +$100. This lesson teaches you:

- What it means to follow the golden rule with your favor request question, explained with an in-depth example
- How to share equivalent value with 3 common favors that software engineers ask for
- A simple 3-step process you can use to add value to anyone and make them want to help you more, particularly when you can't return equivalent value

Measure

In the **Measure** phase of the DMAIC process, we focused on building a consistent, reliable foundation for capturing and interpreting data. This phase was critical in enabling accurate decision-making and accountability across our rapidly growing organization.

### Key Takeaways:

- **We standardized measurements across the company**: To avoid confusion and misalignment, we worked for years to unify definitions, formulas, and data structures across multiple data warehouses and teams.
- **We eliminated self-serving metrics**: Jeff Bezos directed our CFO, Warren Jensen, to form an independent analytics team that would report the unbiased truth, rather than letting individual teams present metrics that suited their own narratives.
- **We invested in strong data infrastructure**: Reliable measurement required robust systems for data capture, storage, access, and reporting—along with clear accountability for maintaining these systems.
- **We built a culture of impartial data analysis**: By establishing dedicated analysts and leaders to oversee data integrity, we ensured that our business decisions were driven by objective, consistent information—not wishful thinking.

To dive deeper into Input Metrics Mastery and learn more from Bill and Colin, follow these links:

- Take the full course at their website: <https://workingbackwards.com/>
- Buy the book: <https://www.amazon.com/Working-Backwards-Insights-Stories-Secrets/dp/1250267595>
- Bill's LinkedIn: <https://www.linkedin.com/in/bill-carr/>
- Colin's LinkedIn: <https://www.linkedin.com/in/colinbryar/>

Get The Rating You Deserve [Part 9] - Getting Stuff Done

We've discussed the importance of increasing your Luck Surface Area (LSA) to maximize the rewards for your efforts. To do this, we must focus on two key components:

- **Do impactful work:** Prioritize tasks that significantly contribute to your goals and the overall success of your team.
- **Communicate effectively:** Clearly articulate your work, its impact, and your aspirations to relevant stakeholders. This includes both celebrating successes and openly discussing challenges.

Remember, effective communication is crucial. Avoid the pitfalls of assuming your work speaks for itself or only sharing successes. Be proactive in seeking alignment with your manager and team, and don't shy away from difficult conversations.

If you want to get personalized support from Yogi, you can reach out to him at [coaching@yogisharma.com](mailto:coaching@yogisharma.com) or schedule an introductory call to dive into your situation at <https://tinyurl.com/meetyogi>.

[Part 7] Meta Intern Success Series - Succeeding As A Remote Intern

- Learning speed is severely nerfed by remote work, which is awful for you as an intern since this is when learning speed is the most important. It's important to keep this mind as you navigate your internship.
- Attend all team events, even the less formal ones (i.e. non-offsite) like team lunch. It's extremely important to build relationships and social capital in this environment where everyone is more isolated.
- Have 2 to 3 1:1s with your non-intern manager peers.
- Match the working hours of your team if you're in different time zones. It's absolutely vital that you always get blocked ASAP, and this is way harder when you're operating on a different time scale. This could be painful, but it will be worth it.
- Do virtual coworking whenever you can. The idea is that everyone joins a video call and just works, no meeting agenda or anything. The idea is to mimic an in-person working environment as much as possible. This creates peer pressure for you to be productive and makes it seamless for you to ask for help (just say something on the call!).

How to Crack System Design Interviews - Part 5: Reviewing Your Solution

This section of the system design interview focuses on identifying and evaluating trade-offs within the proposed design. Here's how we navigate this:

- **Start with non-functional requirements:** We begin by analyzing how non-functional requirements, such as durability, influence design choices and user experience.
- **Analyze access patterns:** We consider how users interact with the system, examining the frequency of different requests and their impact on optimization strategies.
- **Make conscious trade-offs:** Based on our analysis, we make deliberate trade-offs, such as potentially sacrificing immediate consistency for faster read operations.
- **Use precise language:** We use clear and established engineering terms to facilitate accurate communication and efficient use of interview time.
- **Remain adaptable:** We stay open to feedback from the interviewer and adjust our design based on their input, acknowledging their understanding of the system.

[Gaurav Sen](https://www.linkedin.com/in/gkcs/) has conducted 1000s of system design interviews while working at Uber and building his [YouTube channel](https://www.youtube.com/@gkcs) to 500K+ subscribers. His platform [InterviewReady](https://interviewready.io/?_aff=JOINTARO) combines video explainers, live Zoom classes, and an automated System Design Judge.

Course Roadmap

In this part of the course, we’re given a roadmap that outlines the full journey of preparing for machine learning interviews. Each section is designed to build our skills systematically and strategically, based on real-world experience and mentorship insights.

- We start with **essential ML concepts**, learning how to clearly explain high-frequency topics that appear in nearly every interview.
- We then move into **practical ML coding and modeling**, covering notebooks, EDA, model selection, feature engineering, and evaluation techniques.
- **Coding foundations** are reinforced to help us succeed in general algorithm rounds, with a focus on what companies expect from ML candidates.
- We’ll tackle **ML algorithm coding**, where we may be asked to implement algorithms like decision trees or k-means from scratch.
- **ML system design** is emphasized for senior-level roles, with frameworks and examples for building scalable systems.
- Finally, we prepare for **project deep dives and behavioral interviews**, learning how to share impactful stories, followed by crafting a personalized **study plan** that fits our timeline and goals.

If you want to learn even more from Yayun:

- Book 1 on 1 career guidance with her here: <https://calendly.com/your-friend-yayun/1on1>
- Follow her on LinkedIn: <https://www.linkedin.com/in/yayunjin/>

[Become A Go-To Person 14/18] Give Presentations To Become An Expert

A course by [Jordan Cutler](https://www.linkedin.com/in/jordancutler1/), Senior Software Engineer at Pinterest and Author of the [High Growth Engineer Newsletter](https://read.highgrowthengineer.com/)

What Big Tech Data Structures And Algorithms Interviews Generally Look Like

FAANG interviews are some of the most well-defined in the industry. However, this style of software engineer interview is often completely failed due to a lack of preparation. Here's what to expect when it comes to data structures and algorithms interviews for Big Tech.

Here are the core points from the video:
- **Phone screens are Leetcode easy and medium** - This will either be 2 easy problems or 1 medium problem. This means that if you haven't progressed to onsite rounds yet, don't spend much time on Leetcode hard problems: That's a premature optimization. Make sure you have your easy and medium problem mastery down, so you can even make it to that final round.
- **Onsites are Leetcode medium and hard** - This will either by 2 medium problems or 1 hard problem. If you receive a problem that's more on the medium side, make sure to budget your time well. There's a good chance the interviewer wants you to solve another problem on top of that.

Related resources:
- [[Masterclass] How To Ace Your Big Tech Interview - Data Structures & Algorithms](https://www.jointaro.com/lesson/V4sTACzfOh22nMVcUV3w/how-to-ace-your-big-tech-interview-data-structures-and-algorithms-7172021/) - This is the full video this clip is taken from
- [[Masterclass] How To Ace Your Big Tech Interview - System Design](https://www.jointaro.com/lesson/J3I9fTW9ulr6T9KjxpqY/how-to-ace-your-big-tech-interview-system-design-1162021/)

Foundational Ideas

In this key section of the course, we dive into the essential machine learning concepts that consistently appear across all types of ML interviews. This foundation prepares us to explain not just the “what,” but the “why” behind our choices—something interviewers value highly.

- We review core **ML paradigms** like supervised, unsupervised, and reinforcement learning, along with real-world examples to explain their use cases clearly.
- We explore **machine learning tasks** such as classification and regression, and when to apply specific evaluation metrics like precision, recall, or RMSE.
- We gain a deep understanding of **model performance** concepts—bias/variance trade-off, underfitting/overfitting—and how to recognize and address them.
- We cover **validation strategies**, data leakage prevention, and the right use of metrics beyond just accuracy, such as AUC-ROC and F1 score.
- We enhance our skills in **feature engineering**, **optimization algorithms** (like SGD and Adam), **model selection reasoning**, and **dimensionality reduction** techniques like PCA and UMAP.
- We also touch on **LLM fundamentals**—such as Transformers and encoder-decoder architectures—to stay current with emerging trends.
- Most importantly, we practice explaining all of this in a way that connects to real-world problems and highlights our decision-making skills.

If you want to learn even more from Yayun:

- Book 1 on 1 career guidance with her here: <https://calendly.com/your-friend-yayun/1on1>
- Follow her on LinkedIn: <https://www.linkedin.com/in/yayunjin/>

Get The Rating You Deserve [Part 8] - Engaging In Conflicts

**In this section, we'll delve into the importance of effectively managing conflicts in the workplace.**

- **The Benefits of Conflict Resolution:** We'll explore how resolving conflicts can save time, build stronger relationships, and enhance career growth.
- **Key Strategies for Conflict Resolution:** We'll discuss essential strategies such as empathetic negotiation, non-violent communication, and the importance of focusing on common ground.
- **Recognizing Conflict:** We'll discuss the importance of identifying early signs of conflict, such as changes in body language and emotional state.
- **Avoiding Common Pitfalls:** We'll highlight common mistakes people make when dealing with conflict, such as avoidance and blame, and provide strategies to overcome them.
- **Practical Tips:** We'll share actionable advice, such as practicing mindfulness, active listening, and seeking win-win solutions.

If you want to get personalized support from Yogi, you can reach out to him at [coaching@yogisharma.com](mailto:coaching@yogisharma.com) or schedule an introductory call to dive into your situation at <https://tinyurl.com/meetyogi>.

Break Into Tech And Become A Software Engineer [Part 24] - Wrapping Up

In this final lesson, Brian provides key insights and encouragement as you wrap up your journey into software development.

This lesson covers:

- The importance of recognizing that everyone's timeline for getting hired is unique, and consistent effort on your technical skills will prepare you for success
- Building a supportive community or "tribe" through building in public, which will help you grow and find accountability
- Staying committed to learning and growing even after getting hired, as career development is a long-term game, and keeping your skills sharp will open doors for better opportunities

If you need extra help breaking into tech, join Brian's exclusive, cohort-based bootcamp (just 10 students per batch). Use this special link for $800 off: <https://www.parsity.io/taro>

Connect with Brian on LinkedIn: <https://www.linkedin.com/in/brianjenney/>

Become An Open Source Master [Part 24] - Anticipate Common Pushback

- We might get pushback on our pull requests if we don't address all edge cases or introduce performance regressions.
- Follow the project's coding conventions and make sure our code is clean and well-tested.
- Be gracious and adaptable when contributing to someone else's project.

Taro discussions about testing: 

- [What are your thoughts about Test Driven Development?](https://www.jointaro.com/question/SYwVplJYcyO8Sr7PLT2j/what-are-your-thoughts-about-test-driven-development-do-you-think-it-adds-value-in-your-career/)
- [Automated vs manual UI testing?](https://www.jointaro.com/question/frpv5BLQ63ZqvmDcTIkY/automated-vs-manual-ui-testing/)

Connect with James:

- GitHub: <https://github.com/jamesgpearce>
- Twitter (X): <https://twitter.com/jamespearce>

How Effectively Do Big Tech Engineers Perform In Startups?

In this lesson we talk about how engineers from big tech companies perform when transitioning to startups, and what hiring managers should look for when bringing in FAANG talent.

- **The sweet spot is 2-6 years of big tech experience** — engineers in this range bring the best of both worlds: they've been screened for talent and learned strong software engineering fundamentals at top companies, but haven't spent so long there that they've become rigid in their thinking or problem-framing approaches that may not apply in a startup environment.
- **Very senior big tech hires often struggle with the transition** — engineers who've spent many years at large companies can develop highly specific ways of doing things that don't translate well to startup constraints, making cultural and operational fit more challenging despite their technical depth.
- **Big tech experience becomes an asset when there's a specific scaling need** — senior hires excel when the startup has a concrete problem that matches their domain expertise, such as building infrastructure for massive consumer scale or managing rapidly exploding engineering teams, where their direct experience from companies like Facebook becomes immediately applicable.

Become A Debugging Master [Part 19] - Go Deeper: Follow Through

Related courses:

- [Ask Great Questions That Get Great Answers Quickly](https://www.jointaro.com/course/ask-great-questions-that-get-great-answers-quickly/)
- [Level Up Your Code Quality As A Software Engineer](https://www.jointaro.com/course/level-up-your-code-quality-as-a-software-engineer/)

DSA Crash Course [Part 84] - Counting Change Walkthrough

In this lesson, Alvin walks through the python implementation for the *counting_change* problem.

Code along and test your work in the following editor workspace: <https://structy.net/problems/counting-change?language=py>

If you need additional support taking these DSA skills and actually applying them, take [**Alvin's**](https://www.linkedin.com/in/alvin-zablan-b73a92117/) *complete* data structures and algorithms course on [**Structy**](https://structy.net/?utm_source=taro). You can try out the concepts yourself in their interactive code editor and learn advanced DSA patterns like stack exhaustive recursion.

Use [**this link to get 20% off**](https://structy.net/purchase?promo_code=taro20) the entire Structy DSA learning experience.

Follow Alvin on LinkedIn: [**https://www.linkedin.com/in/alvin-zablan-b73a92117/**](https://www.linkedin.com/in/alvin-zablan-b73a92117/)

[Timeless Career Advice] Promos and Relationships

[Become A Go-To Person 15/18] - Other Ways To Build Expertise

Build Deep Relationships Quickly In Tech [Part 6] - You're Going To Get Burned

Networking isn't all sunshine and roses - You're going to go through a lot of pain as well. This lesson teaches you:

- Why many relationships fall apart
- Why you shouldn't let a failed relationship turn you off networking forever
- A tactical, mathematical framework to minimize risk and maximize upside when it comes to networking
- How to identify if a relationship isn't going anywhere and should be cut off

Tech Career Growth Videos

Our instructional videos provide software engineers with insights needed for career growth. Masterclasses go incredibly in-depth on a specific tech topic while case studies are real examples from established engineering leaders.