Amazon Behavioral Interview [Part 27] - Recovering From A Bad Decision (Answer)

This video segment describes a situation where the interviewee made a mistake in their role at American Express.

- **Identified the Mistake:** The interviewee implemented a new incentive system for customer care professionals that rewarded them for saving high-value customers while neglecting lower-value customers. This led to:

  - **Cherry-picking of customers:** Customer care professionals prioritized high-value customers, leading to long wait times for lower-value customers.
  - **Negative customer experience:** Long wait times resulted in poor customer satisfaction and potentially damaged brand reputation.
  - **Missed revenue opportunities:** Neglecting lower-value customers, particularly early-tenure customers, resulted in missed opportunities for future revenue growth.

- **Learned from the Mistake:** The interviewee learned the importance of:

  - **Considering all stakeholders:** Involving customer care professionals in the decision-making process.
  - **Thinking long-term:** Considering the long-term value of customers, not just their immediate spending.
  - **Gathering diverse perspectives:** Seeking input from former team members to identify potential pitfalls.

- **Implemented Corrective Actions:**

  - Revised the incentive system to account for customer lifetime value.
  - Implemented measures to improve call center response times and reduce wait times.
  - Developed a system to identify and address cases of long wait times for customers.

This example demonstrates the interviewee's: 

- ***Self-awareness:*** *Acknowledging and taking responsibility for their mistake.* 
- **Problem-solving skills:** Identifying the root cause of the issue and implementing corrective actions. 
- ***Learning agility:*** *Learning from the mistake and applying those learnings to future projects.* 
- **Focus on customer experience:** Prioritizing customer satisfaction and long-term customer relationships. 
- **Continuous improvement:** Continuously refining processes and seeking ways to improve performance.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

Amazon Behavioral Interview [Part 25] - Working Outside Of Your Domain (Answer)

This video segment describes a situation where the interviewee took on a project outside their core responsibilities to improve employee engagement at Google.

- **Identified a Problem:** The interviewee noticed that employee engagement scores were low, particularly regarding the perception of fair and transparent promotions.
- **Took Initiative:** The interviewee proactively identified this issue and proposed a solution: creating an anonymous feedback system to gather data on employee perceptions of promotion fairness.
- **Implemented a Solution:** The interviewee worked with HR to develop and implement the "Perfolution" system, which collected anonymous feedback from employees on promotion decisions.
- **Achieved Positive Results:** The system successfully gathered valuable data, which was then used to identify areas for improvement in promotion processes. This resulted in a significant improvement in employee engagement scores related to promotion fairness.
- **Demonstrated Initiative and Collaboration:** This example demonstrates the interviewee's initiative, problem-solving skills, and ability to collaborate effectively with other teams (HR) to achieve a positive impact.

This example effectively demonstrates the interviewee's: 

- ***Proactive approach:*** *Identifying a critical issue and taking the initiative to address it.* 
- **Problem-solving skills:** Developing and implementing a creative solution to gather data and identify areas for improvement. 
- ***Collaboration and teamwork:*** *Effectively collaborating with HR to implement the solution and address the identified issues.* 
- **Focus on employee engagement:** Demonstrating a commitment to improving employee satisfaction and well-being. 
- **Ability to drive positive change:** Successfully implementing the solution and achieving a significant improvement in employee engagement scores.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

Amazon Behavioral Interview [Part 23] - Sacrificing Short-Term For Long-Term (Answer)

This video segment describes a situation where the interviewee had to make a difficult decision to sacrifice short-term gains for long-term value.

- **Identified the Problem:** The interviewee inherited a team with three regional teams operating independently, leading to inefficiencies and hindering the team's ability to scale and meet growing demands.
- **Made a Difficult Decision:** The interviewee made the difficult decision to transition the team from a regional model to a globally aligned model. This decision faced significant resistance from the team, leading to setbacks and the loss of some team members.
- **Overcame Challenges:** Despite the challenges, the interviewee successfully implemented the new model, resulting in significant improvements:
  - Reduced resolution times from seven hours to two hours.
  - Increased customer satisfaction (CSAT) significantly.
  - Improved operational efficiency and team productivity.
- **Learnings and Reflections:** The interviewee acknowledged that they could have improved their communication and change management strategies. They recognized the importance of more proactively communicating the need for change and the potential benefits of the new model to the team.

This example demonstrates the interviewee's ability to: 

- **Identify and address systemic issues:** They recognized the limitations of the existing system and proposed a solution to improve efficiency and effectiveness. 
- **Make difficult decisions:** They made a difficult decision despite facing resistance from their team. 
- **Overcome challenges:** They successfully navigated the challenges of the transition, including team resistance and operational hurdles. 
- **Focus on long-term value:** They prioritized long-term benefits for the team and the organization, even when it meant short-term disruption.
- **Learn from experience:** They identified areas for improvement in their communication and change management strategies.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

Amazon Behavioral Interview [Part 21] - Disagreeing With Your Manager (Answer)

This video segment describes a situation where the interviewee disagreed with their manager's directive to implement a 15-minute response time for customer escalations.

- **Identified the Conflict:** The interviewee recognized that the 15-minute response time was unrealistic and impractical for their team, considering factors such as:

  - **Global Time Zones:** Many customers were located in different time zones, making immediate contact difficult.
  - **Internal Coordination:** Coordinating with internal stakeholders, such as sales teams, was necessary before contacting customers.
  - **Complexity of Escalations:** Resolving complex escalations often required significant internal investigation and coordination.

- **Proposed an Alternative Solution:**

  - The interviewee proposed a more realistic goal: contacting the customer within one hour of receiving the escalation.
  - They emphasized the importance of internal coordination and collaboration with sales teams.
  - They introduced a key performance indicator (KPI) of "time to first response" within one hour, focusing on a 90th percentile target.

- **Navigated Challenges:**

  - The interviewee faced resistance from both their manager and their team.
  - They effectively addressed the concerns of the sales team by improving communication and coordination.
  - They gathered data to support their proposed solution and successfully presented it to their manager.

- **Achieved Positive Outcomes:**

  - The team successfully met the 90th percentile target for time to first response.
  - Customer satisfaction improved.
  - The interviewee demonstrated effective communication, negotiation, and problem-solving skills.

This example demonstrates the interviewee's ability to: ***Challenge assumptions:*** *They questioned the feasibility of the 15-minute response time and proposed a more realistic alternative.* **Collaborate effectively:** They worked with their team and other stakeholders to address the challenges and implement the new approach. ***Drive positive change:*** *They successfully implemented a new process that improved customer satisfaction and team efficiency.* **Demonstrate resilience:** They persevered despite initial resistance from their manager and their team.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

Amazon Behavioral Interview [Part 19] - Taking An Unpopular Stance (Answer)

This video segment describes a situation where the interviewee took an unpopular stance in a meeting with leadership.

- **Identified the Conflict:** The interviewee disagreed with the company's decision to significantly shift resources from the US to India for customer support, primarily driven by cost-cutting measures.
- **Presented an Alternative Solution:** Despite the potential for backlash, the interviewee proposed an alternative solution:
  - While acknowledging the cost-effectiveness of hiring in India, they suggested leveraging the "Year Up" program to hire underrepresented talent in the US, aligning with the company's diversity and inclusion goals.
- **Faced Opposition:** The interviewee faced strong opposition from the CFO, who was primarily focused on cost-cutting measures and reacted negatively to the alternative proposal.
- **Continued to Advocate:** Despite the initial setback and lack of immediate recognition, the interviewee continued to advocate for the inclusion of the "Year Up" program.
- **Achieved Partial Success:** While the initial proposal was largely dismissed, the company eventually implemented a limited version of the "Year Up" program, demonstrating the long-term impact of the interviewee's advocacy.

This example highlights the interviewee's: ***Proactive Approach:*** *They identified a potential solution that aligned with company values.* **Courage and Persistence:** They were willing to express their dissenting opinion despite potential negative consequences. ***Focus on Long-Term Impact:*** *They demonstrated a commitment to long-term goals, such as diversity and inclusion, even when faced with immediate pressures.* **Ability to Learn and Adapt:** They acknowledged the limitations of their initial approach and demonstrated a willingness to adapt and find alternative solutions.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

Amazon Behavioral Interview [Part 17] - Handling Unclear Expectations From Leadership (Answer)

This video segment describes a situation where the interviewee faced conflicting demands from leadership: the need to drive customer satisfaction and improve resolution times while also maintaining employee engagement and retention.

Here are the key takeaways:

- **Identified the Conflict:** The interviewee recognized the conflicting demands from leadership regarding customer satisfaction metrics and employee well-being, particularly during a challenging period with COVID-19.
- **Navigated the Challenges:**
  - **Open Communication:** They fostered open communication with their team, actively seeking feedback and addressing concerns.
  - **Prioritized Employee Well-being:** Despite the pressure to meet performance metrics, they prioritized employee well-being by:
    - Implementing measures to reduce stress, such as virtual happy hours and flexible work arrangements.
    - Actively listening to employee feedback and addressing their concerns.
  - **Balanced Priorities:** They successfully navigated the competing demands by finding a balance between meeting performance targets and maintaining employee morale.
- **Demonstrated Leadership:** The interviewee demonstrated strong leadership by:
  - Proactively addressing the challenges and seeking solutions.
  - Effectively communicating expectations and priorities to their team.
  - Building trust and fostering a supportive team environment.

This example highlights the interviewee's ability to navigate complex situations, prioritize competing demands, and effectively lead and motivate their team.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

Amazon Behavioral Interview [Part 15] - Going Above and Beyond For A Customer (Answer)

This video segment describes a situation where the interviewee went above and beyond to help a dissatisfied customer.

- **Identified a Customer Issue:** The interviewee encountered a platinum card customer who was extremely upset because their car, which was damaged while skiing, was not covered by the card's rental insurance due to a specific exclusion in the terms and conditions.
- **Went Above and Beyond:** Despite the company policy, the interviewee recognized the customer's frustration and proactively sought a resolution. They:
  - Investigated the issue and identified the relevant policy.
  - Engaged with internal stakeholders, including the product team and a senior executive, to advocate for the customer.
  - Successfully secured approval for a $4,000 statement credit to cover the repair costs.
  - Further impressed the customer by arranging for a check to be mailed directly, providing a more tangible and personalized gesture of goodwill.
- **Achieved Positive Outcomes:**
  - The customer was highly satisfied with the resolution and even became a testimonial for the company.
  - The company retained a valuable customer who was initially considering canceling their card.
  - The incident led to a review of the policy and improved communication regarding the scope of rental car insurance coverage.

This example demonstrates the interviewee's commitment to customer satisfaction, their ability to navigate internal processes, and their proactive approach to resolving customer issues.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

Amazon Behavioral Interview [Part 13] - Delivering Results (Answer)

In this video, the speaker describes a situation where they had to implement a new process quickly to improve internal communication and efficiency. Here are the key takeaways in 3 bullet points:

- **Identified a Problem:** The speaker's team was facing issues due to multiple channels for internal stakeholders to submit escalations. This created confusion and made it difficult to track issues.
- **Implemented a Solution:** The speaker quickly developed a plan to create a single point of entry (\[email address removed\]) for all escalations. This streamlined the process and ensured that issues were not falling through the cracks.
- **Achieved Results:** The new process was successfully launched within a tight deadline. While there was some initial resistance from some stakeholders, the speaker was able to address concerns and ultimately achieve nearly 100% compliance.

Overall, the speaker's experience highlights the importance of being adaptable and resourceful in a fast-paced work environment. It also demonstrates the value of clear communication and collaboration in achieving successful outcomes.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

Amazon Behavioral Interview [Part 5] - Stakeholder Management (Answer)

This video segment focuses on the interviewee's approach to stakeholder management.

- **Experience:** The interviewee highlights their experience managing global and cross-functional teams, emphasizing their ability to navigate complex situations with multiple stakeholders.
- **Example: Prioritizing Customer Support:** The interviewee describes a specific example at Tableau where they led an initiative to change the customer support prioritization system. This involved gathering input from various stakeholders (sales, support, finance) and addressing their concerns.
- **Challenges:** The interviewee acknowledges the challenges of balancing the needs of different stakeholders, particularly the conflict between prioritizing high-value enterprise customers and maintaining support for smaller businesses.
- **Strategies:** To address these challenges, the interviewee emphasizes the importance of:
  - Understanding the goals and priorities of each stakeholder.
  - Using data and facts to support decisions.
  - Building consensus through clear communication and collaboration.
  - Seeking support from key leaders (e.g., the Chief Revenue Officer) to help address resistance from certain stakeholders.
- **Key Takeaway:** Effective stakeholder management requires strong communication, active listening, and the ability to navigate conflicting priorities while maintaining a focus on overall business objectives.

Learn more about Alan's job search program, Kadima Careers, using this [discount link](https://signup.kadimacareers.com/mQBsDvu).

Get The Rating You Deserve [Part 19] - Conclusion

**In this course, we’ve explored strategies for increasing our impact and achieving long-term success.**

We covered three key areas:

- **Understanding Impact Dynamics:** We learned how to create value and communicate it effectively to others.
- **Increasing Luck Surface Area:** We explored strategies for getting things done and sharing our work with the world.
- **Building an Empowering State:** We discussed the importance of cultivating a positive mindset, building strong relationships, and prioritizing self-care.

By applying these principles, we can improve our professional and personal lives. If you have any questions or would like to delve deeper into these concepts, please don’t hesitate to reach out.

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**](https://tinyurl.com/meetyogi).

Get The Rating You Deserve [Part 17] - Think Long Term

**In this section, we explored the importance of maintaining a long-term perspective in our careers.**

To cultivate a long-term mindset, we should:

- **Set long-term goals:** Define clear and ambitious goals for the next five, ten, or even twenty years.
- **Align short-term actions with long-term goals:** Make decisions that align with our long-term vision.
- **Build a strong personal brand:** Develop a reputation for reliability, integrity, and expertise.
- **Cultivate meaningful relationships:** Build and maintain strong relationships with colleagues, mentors, and sponsors.
- **Continuously learn and grow:** Invest in personal and professional development to stay ahead of the curve.

By adopting a long-term perspective, we can make more strategic decisions, increase our resilience, and achieve greater fulfillment in our careers.

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>.

Paper Reading: Llama 2: Open Foundation and Fine-Tuned Chat Models

Session led by [Mike A](https://www.linkedin.com/in/malik-mike-a-32b63818b/)

Join us for the second installment of our three-part paper reading series on the LLaMA series of Large Language Models (LLMs).

In this session, we will dive into **Llama 2**, the second iteration in the LLaMA family of models, introduced by Meta AI in mid-2023. This follow-up to the original LLaMA models brings significant advancements, offering foundational and fine-tuned versions with parameter counts ranging from 7B to 70B. Llama 2 models set new benchmarks in helpfulness and safety, showcasing impressive capabilities in dialogue-based tasks and outperforming many open-source alternatives.

We will explore the innovations behind the **Llama 2** models, focusing on their **pretraining methodology**, the **fine-tuning process** that incorporates Reinforcement Learning with Human Feedback (RLHF), and the novel techniques Meta AI used to enhance model safety and alignment. Particular emphasis will be placed on the **Llama 2-Chat models**, optimized for multi-turn conversations, along with references to their performance on real-world safety benchmarks.

This session will be an insightful discussion of how the Llama 2 models have helped to close the gap between open-source and closed-source systems like ChatGPT, examining their architecture, training data, and the steps taken to ensure responsible release and deployment. We'll highlight key takeaways from Meta AI's comprehensive evaluation of these models and discuss how they are still reshaping the landscape of open-source AI.

Whether you're a researcher, developer, or AI enthusiast, this paper reading will offer you an in-depth understanding of the **Llama 2** models and their contributions to the ongoing development of LLMs. This is a unique opportunity to review cutting-edge advancements in **LLM safety**, **dialogue optimization**, and their impact on the future of open-source AI systems.

Mark your calendars for an informative hour of "Llama 2: Open Foundation and Fine-Tuned Chat Models," as we continue to chart the progress of AI language models and explore the innovations that continue to shape the future of the field!

[https://lmarena.ai/\
https://github.com/meta-llama/llama](https://lmarena.ai/￼https://github.com/meta-llama/llama)

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/)

DSA Crash Course [Part 78] - Max Path Sum Walkthrough

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

Code along and test your work in the following editor workspace: <https://structy.net/problems/max-path-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/)

DSA Crash Course [Part 74] - Minimum Change Walkthrough

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

Code along and test your work in the following editor workspace: <https://structy.net/problems/min-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/)

DSA Crash Course [Part 65] - Minimum Island Approach

In this lesson, Alvin explores the strategy to solving the following interview problem:

> Write a function, *minimum_island*, that takes in a grid containing Ws and Ls. W represents water and L represents land. The function should return the size of the smallest island. An island is a vertically or horizontally connected region of land.
>
> You may assume that the grid contains at least one island.

```
grid = [
['W', 'L', 'W', 'W', 'W'],
['W', 'L', 'W', 'W', 'W'],
['W', 'W', 'W', 'L', 'W'],
['W', 'W', 'L', 'L', 'W'],
['L', 'W', 'W', 'L', 'L'],
['L', 'L', 'W', 'W', 'W'],
]

minimum_island(grid) # -> 2
```

```
grid = [
['L', 'W', 'W', 'L', 'W'],
['L', 'W', 'W', 'L', 'L'],
['W', 'L', 'W', 'L', 'W'],
['W', 'W', 'W', 'W', 'W'],
['W', 'W', 'L', 'L', 'L'],
]

minimum_island(grid) # -> 1
```

```
grid = [
['L', 'L', 'L'],
['L', 'L', 'L'],
['L', 'L', 'L'],
]

minimum_island(grid) # -> 9
```

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/)

DSA Crash Course [Part 64] - Island Count Walkthrough

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

Code along and test your work in the following editor workspace: <https://structy.net/problems/island-count?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/)

DSA Crash Course [Part 62] - Shortest Path Walkthrough

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

Code along and test your work in the following editor workspace: <https://structy.net/problems/shortest-path?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/)

DSA Crash Course [Part 60] - Largest Component Walkthrough

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

Code along and test your work in the following editor workspace: <https://structy.net/problems/largest-component?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/)

DSA Crash Course [Part 48] - Tree Min Value Walkthrough

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

Code along and test your work in the following editor workspace: <https://structy.net/problems/tree-min-value?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/>

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.