From Medicine to Machine Learning: How Public Learning Turned into a Career

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Transcript

The transcripts are edited for clarity, sometimes with AI. If you notice any incorrect information, let us know.

Pastor’s background and early programming journey
Learning new tools and skills on the job while studying medicine
Balancing medical studies with data science work and motivation
Applying medical knowledge to data science and vice versa
Starting freelance work on Upwork and overcoming language challenges
Joining the machine learning engineering course and benefits of live cohorts
Engaging with the course community and sharing progress publicly
Using LinkedIn and social media for career growth and interview opportunities
Building reputation, structuring learning, and leveraging course projects
Volunteering and mentoring with DeepLearning.AI and Stanford Coding Place
Managing time and staying productive while studying medicine and machine learning

Pastor’s background and early programming journey

Alexey: Hi everyone, welcome to our event. This event is presented by Redox Club, a community of people who love data. We have weekly events. During the summer, they are not so frequent but we still have events. (0.0)

Alexey: If you want to find out more about our upcoming events, there is a link in the description. Click on it and check it out. Later today, we will hold a workshop about serverless deployment of machine learning models. Tomorrow we have a pre-course Q&A for our machine learning engineering course. That’s also one of the topics we will cover today with Pastor. (0.0)

Alexey: Before we start, don’t forget to subscribe to our YouTube channel to stay updated with our content. We also have an amazing Slack community where you can connect with other data enthusiasts. During today’s interview, you can ask any questions you want. A link is pinned in the live chat, so click it and post your questions. We will cover them during the interview. (0.0)

Alexey: By the way, I think the Grammarly suggestion is popping up. I haven’t used Grammarly in a while. Since I started paying for ChatGPT, I canceled Grammarly. Maybe I should update the slide. Anyway, I need to stop sharing my screen now. (0.0)

Alexey: Now I’m opening the questions we prepared. Let’s start. Are you ready? (1:34)

Alexey: This week, we will talk about learning machine learning while being a medical student and how self-learning turned into a career. We have a very special guest today, Pastor. He was a student and an active participant in one of our courses. He is also a very active member of our community. (1:34)

Alexey: I’m very happy to have him today. Pastor is a machine learning engineer and a mentor. He focuses on practical, hands-on work. While studying medicine at university, he took on a side project that introduced him to machine learning. He started sharing publicly during machine learning Zoom camp, which helped him get interviews and job offers. (1:34)

Alexey: I actually didn’t know much before, so I’m curious to learn more. Welcome, Pastor, to this interview. (1:34)

Pastor: Hi everyone. Thanks, Alex. I’m really excited about this interview. (2:50)

Alexey: Me too. I saw you have been very active, and in our courses we have a leaderboard. I think you were top in one of our courses? (2:56)

Pastor: Yes, I participated in the machine learning engineer course and I was first in my cohort. That was pretty cool. (3:10)

Alexey: Great. Before we talk more about all that, can you tell us about your career journey so far? (3:21)

Pastor: Sure. I recently graduated from medical school, so I’m a medical doctor. Throughout my career, I learned programming and started working as a statistician. Then I moved to data analyst, data scientist, and data engineering roles. (3:29)

Pastor: I went through pretty much the full data pipeline with various roles and projects. I love improving and learning new things. (3:29)

Alexey: What motivated you? Healthcare and data science don’t seem very related. How did you get into programming while being a medical student? (4:13)

Pastor: Before graduating from medical school, I graduated in social science; I am also a criminologist. I took statistics classes and was a teaching assistant. (4:37)

Pastor: When I started medical studies, I saw many opportunities to freelance in statistics and data analysis. My main motivation was to have remote work that could pay bills and was flexible enough to let me study. There are not many online roles with that flexibility. (4:37)

Pastor: Starting my journey in data was a big opportunity to keep studying while working. I also found it exciting to investigate what the data tells you. That curious mindset was a good motivator. (4:37)

Alexey: You studied criminology and did statistics as a teaching assistant. How did you get your first remote job? (5:51)

Learning new tools and skills on the job while studying medicine

Pastor: I signed up on Upwork, a freelance platform that matches you with jobs. My first project was helping someone with a statistics problem from school. It was a small project, around five dollars. (6:05)

Pastor: I found it exciting to get my first five dollars online. It surprised me that people would pay a random guy they found on a board. The project was about helping people study, and they were willing to pay small amounts to get help. (6:05)

Alexey: How did your online work progress after that? (7:05)

Pastor: After seeing people willing to pay, I started learning more and amplifying my skills. I had no background with tools; my statistics class was on SPSS, which is mostly point-and-click, so there weren’t many foundations. (7:12)

Pastor: I started using Excel, which I hadn’t known before, and got some roles using Excel. Then I saw opportunities in R, so I learned R, took many projects but they didn’t pay much, and there were few of them. (7:37)

Pastor: Later, I got a major, long-term role that required learning Python. So I started learning Python. This was before ChatGPT. Everything was through courses, documentation, and practice. I often had R code on one side of my screen and Python on the other, translating because I knew R but had to write Python. That helped me build solid foundations in Python. The pandemic also helped because everyone was looking for remote freelancers. (8:08)

Alexey: That’s interesting. From what I understood, you observed market demands, learned the skills, then applied them. First SPSS, then Excel, then R, each time picking up skills to apply in new roles. Is that correct? (9:08)

Pastor: Yes, sometimes. Often, people asked me to take projects I didn’t know how to do, but I said yes and learned quickly on the job. It was intense because I had to learn fast to meet deadlines. That environment helped me stay motivated and effective. You have to work in motivating environments to meet deadlines while understanding requirements and learning how to deliver. (9:39)

Pastor: Yes, it was a sense of seeing the market, but also learning skills while working. Since data is competitive, you can’t always say I don’t know. That might work at higher professional levels, but when starting, you sometimes have to push yourself to take unknown projects. It worked well for me because I succeeded in almost all projects. I was even one of the top-ranked freelancers on the platform. It’s hard and intense, needing early mornings and late nights learning and applying, but it’s fun. (10:21)

Balancing medical studies with data science work and motivation

Alexey: You were studying at the same time criminology and then medicine. That’s intense. I have a childhood friend who studied medicine to become a dentist. The first years learning basics common to all doctors were very intense. It’s motivating to hear you managed all that. (11:44)

Pastor: Exactly. Medical studies are demanding. Switching between two domains helped me. Sometimes you learn approaches in medicine that apply to data and vice versa. (12:25)

Pastor: I always pushed productivity and time efficiency, trying to make progress while maintaining balance. Those two fields combined well because data helped support my medical career financially. (12:25)

Pastor: I don’t think it would be possible for me to manage one domain without the other. Medical school motivated me to do more in data. So from my perspective, I can’t imagine managing one without the other. (12:25)

Applying medical knowledge to data science and vice versa

Alexey: A question came in: The remote site where you found your first job was Upwork, right? (13:48)

Pastor: Yes, Upwork. It was different times. I think I started around 2016. (13:54)

Alexey: Was it called oDesk or Elance back then? They merged later, remember? (14:06)

Pastor: I started after that. I didn’t know those earlier platforms. When I started, it was just Upwork. (14:16)

Pastor: Also, I didn’t know how to communicate well in English with people. Everything was written communication. I had to improve my English skills while working and learning. (14:29)

Pastor: I took English classes throughout my life, but speaking one-on-one in a live environment was new to me. (14:29)

Alexey: That’s not easy. I remember my first time in the States, how difficult speaking was. I was an English teacher with two degrees—computer science and teaching English. Still, coming there, I couldn’t understand a word people said. (15:13)

Pastor: You think you know until you start talking with people. (15:39)

Alexey: Yes. They were asking me to spell the name of the website, and I just spelled T-W-O-R-K. (15:47)

Alexey: What is your medical specialty? Are you a generalist? (15:47)

Pastor: I’m a generalist. I just recently graduated from medical school, so when you graduate, you don’t have a specialty yet. Then you decide which specialty to pursue. (16:00)

Alexey: I see. What are your next steps in your medical career? Do you need to work at a hospital first? (16:15)

Pastor: Yes. In my country, after graduation, you must complete one year of service in a rural community. You practice medicine there, because even after graduating, you’re still learning. (16:26)

Pastor: You cannot practice independently outside that one-year program. After completing it, you can work as an independent physician or apply to a residency program. (16:26)

Alexey: Do you have a plan for this? (17:05)

Pastor: Right now, my plan is to complete my one-year rural service. I like internal medicine, cardiology, and neurology but haven’t decided yet. (17:10)

Pastor: I’m trying to see if I can combine data and healthcare to build my career. I still need to figure out if I want to do that before or after specialization. (17:10)

Alexey: That makes sense. Specialists are in high demand in Germany. There are so few, and waiting times for cardiologist appointments can be two or three months. (17:39)

Pastor: Actually, many people I know went to Germany to practice medicine. It’s not that hard if you know German. You need to speak the language well. If you pass that, you can work there. (18:09)

Alexey: German is difficult. After living here 10 years, I still struggle with speaking it well. I work in IT, so I don’t use German daily. (18:25)

Starting freelance work on Upwork and overcoming language challenges

Alexey: One thing you mentioned is that some things from medicine you could apply to data and vice versa. What examples do you have of skills or approaches that transfer between these domains? (18:44)

Pastor: In medicine, you acquire many skills, but one that helped me most was organization. In hospitals, you always develop a plan for patients. (19:05)

Pastor: You can’t have a patient without a plan or without knowing what to do next, even in complicated or uncertain cases. Having a plan helps keep things organized. (19:05)

Pastor: This skill helps me organize projects and know what to work on every time. You also develop the ability to prepare for uncertainty because it’s common in any domain or job. (19:05)

Pastor: From data, I learned the curious mindset. Successful data people are curious; they dig deep into why things happen. (20:19)

Pastor: This helped me notice things others overlook. For example, understanding why a patient behaves a certain way or anticipating probabilities helps in medicine. (20:19)

Pastor: When a patient arrives in the emergency department, you consider demographics, epidemiology, and environmental factors to estimate the probability of diseases. (21:09)

Pastor: Ranking diseases by likelihood helps you focus on what to study and prepare for, since medicine has an overwhelming amount to learn and patients have varied backgrounds. (21:09)

Pastor: For example, a patient with abdominal pain could have anything from a heart attack to food poisoning. The most likely cause might be food poisoning, but doctors first think about critical conditions that can kill, and they try to rule those out before considering less critical causes. (21:55)

Pastor: Reranking and organizing possibilities by probability, revisiting diagnosis, and striving to be accurate is something I learned a lot from data. (21:55)

Alexey: Makes sense. Makes sense. Interesting. (22:48)

Alexey: Just relying on probability in healthcare is not enough because the most likely cause could be food poisoning, but the patient might have something more severe. You need to start with the most severe conditions and then eliminate them until you find the more probable cause. (22:48)

Pastor: Exactly. I was checking a website that uses GPT under the hood—a triage system where you type your symptoms. It evaluates your symptoms and asks questions, and you can see the logs. (23:06)

Pastor: One thing those applications fail at is reranking based on severity. They rerank just by probability. For example, a heart attack manifesting as abdominal pain is quite frequent but doesn’t appear until the 20th iteration in the system. That’s something that can be applied from data science to healthcare. (23:06)

Joining the machine learning engineering course and benefits of live cohorts

Alexey: Speaking of the machine learning Zoom camp and our machine learning engineering course, how did you find out about this course? (24:03)

Pastor: I saw a post, I think on Twitter back then. I tried to sign up but didn’t know how to manage things because I hadn’t used Slack before. I reached out to you via Twitter, and you helped me set everything up. That was really motivating because I had my first blockage there but you were very responsive. (24:17)

Alexey: I don’t check Twitter or X very often these days. If someone’s waiting for my reply there, I apologize. It’s better to contact me by email. When you go to data talks club and fill in the form with your email, you receive an automatic message from me and can reply directly. That’s the best way to reach me now. (24:54)

Alexey: Twitter is nice because I can reach people like you, Pastor, but it’s also draining. You may check something important and then find yourself half an hour later scrolling through random videos. (24:54)

Pastor: Yeah, exactly. At that time, I was trying not to do too many things because I was kind of burned out. But I saw this chance to work on a live, hands-on course. Before that, I mostly went through Udemy, Coursera, or YouTube courses to pick up skills, but I didn’t have live interaction with others learning the same things, instructors, or a fixed schedule to help me keep pace. (25:36)

Alexey: We do courses in cohorts on purpose. For me, it’s difficult to follow a self-paced course, so I understand that well. (26:31)

Pastor: That was the first time I saw that model, and now it’s mainstream. Many people do live courses and engage with platforms like Maven. It’s becoming popular. I thought platforms like Coursera or Udemy would dominate, but in fact, live courses are taking over. I found it the most helpful way to learn with others. (26:45)

Alexey: So you found the post on X, struggled a little with Slack, and I hopefully helped you. Good to hear. After joining Slack, what happened next? (27:27)

Pastor: I started going through the videos and engaging in the platform. I saw there was a leaderboard. I’m competitive and like to compete, even though you often say the leaderboard shouldn’t be the focus and learning should be the goal. (27:41)

Pastor: Still, the leaderboard helped me a lot. I tried to understand how it worked, submitted my homework, and did many posts each week. That helped because before that, I hadn’t posted on any platform. Sharing what I was learning was an amazing skill. (28:04)

Pastor: It was probably the best thing I did in my career putting my name out there. People don’t know who you are, and if you don’t market yourself, no one will do it for you unless you engage with others. That was one of the best things about the course. Being first in the cohort didn’t bring me anything by itself. What I did to reach first place is what really helped me. (28:43)

Alexey: In our courses, we encourage participants to learn in public and share their progress, which is why we have the leaderboard and give extra points for sharing on social media. Still, many people find it difficult to share their progress because they think, “I’m just a student; what I share isn’t valuable,” or they don’t want to post on social media. (29:38)

Alexey: Did you have hesitations like that? If yes, how did you overcome them? (29:38)

Pastor: I did hesitate at first, but climbing the leaderboard helped a lot. I started posting phrases like “I’m learning this and that” on ML stuff. However, I took a different approach: instead of saying “I’m learning this,” I tried to own what I was learning. For example, I explained concepts like the ROC curve, how it helps understand classifier performance, and the steps to be aware of when plotting an ROC curve in Python. (30:20)

Pastor: That kind of ownership helped me to adopt the mindset that I actually knew what I was talking about and helped market myself as an expert in the field. This was one of the best things I did transforming posts from “I’m learning this” to demonstrating professional insight. When people look at your history, they see you explaining how to do ML classification or become an ML engineer. That approach helps a lot. (31:39)

Alexey: I see. One question here: you started sharing your progress during the course, and that helped you get interviews. Can you tell us more about how that happened? (32:30)

Pastor: A few months after I started sharing online and posting MLS camp content, recruiters reached out to me. One was from Meta. That surprised me because I was just learning. I wasn’t prepared for a job at Meta but wanted to try the interview process to see how it feels and learn how to communicate with recruiters from big companies. That’s a valuable skill even if you aren’t ready for the job or think you won’t get it. (32:50)

Pastor: I wasn’t actively looking for opportunities, but a recruiter contacted me based on my LinkedIn posts. She said, “I’m from Meta. We think you’re a good fit for an ML engineer role and want to know more about you.” I went through the behavioral interview. Having a learning mindset is something they value a lot, but my skills and experience weren’t yet there. (33:47)

Pastor: It was a fun experience, and it surprised me how easy it is to get interviews. The hardest part is overcoming your fears to put yourself out there. Eventually, you might say things that aren’t totally correct, and people will point that out. If you overcome that fear and take ownership of what you post, it can really help you. (34:32)

Alexey: Thanks for sharing. The way it works on LinkedIn is that when you post, some followers or people following the same hashtags interact. If I like your post, my followers will see that I liked it. They may follow you, and when you publish your next post, their followers see it. Eventually, a recruiter sees it. (35:16)

Alexey: This is the power of social media. It’s amazing to be exposed like that. You just need to be active, but overcoming the hesitation or fear of posting something incorrect is not easy. Did you ever post something incorrect and have people point it out? How did that feel? (35:16)

Pastor: Yes, sometimes posts might be taken out of context or seem incorrect. For example, I posted a quote from the AI engineering book by Chip Huen that says AI engineering is building stuff on top of foundational models. Some people replied that it sounded like anyone with ChatGPT can be an engineer now, which is not the whole truth. (36:33)

Alexey: That’s true. AI engineering means building on top of models like OpenAI. Essentially, all you need is access to the API key, right? (37:14)

Pastor: If you simplify it to that, yes, but you still have to do a lot to make it work. I think my post wasn’t clear on that. People pointed it out, but I don’t take it personally. I try to learn from interactions. (37:27)

Pastor: Sometimes a small post and the debate it generates helps you reach more people. (37:27)

Alexey: When people comment to correct mistakes, the post gets more exposure because it’s promoted to the top of your feed. That’s how you get more visibility. (38:01)

Pastor: That’s how Stack Overflow works. (38:24)

Alexey: So what you said wasn’t really incorrect but an invitation for debate. (38:32)

Pastor: Yes. Like Stack Overflow if you post something already covered, people will point it out strictly. I had questions with negative scores because they didn’t meet guidelines. (38:38)

Pastor: But oversimplifying can help you reach out to people. It’s part of the deal. You just need to have fun with the content you post. (38:38)

Alexey: I checked my Stack Overflow reputation; I have 2,400 points. (39:17)

Pastor: That’s good. (39:30)

Alexey: Sometimes you ask a question, and five years later you see it still has value. (39:36)

Pastor: Stack Overflow wasn’t very beginner-friendly. If you didn’t know how to pose a good question, people would criticize you. (39:42)

Alexey: I never had that problem. I’ve been active on forums since early internet days, so I guess I knew the culture. (39:47)

Alexey: Back to our topic. You shared your progress during the ML Zoom camp, but you framed your posts like an expert rather than a student. You explained concepts like the ROC curve and how to evaluate classifiers from an expert perspective. That reframing helped you post more confidently. (40:06)

Alexey: Also, since you worked on platforms like Upwork, you likely wanted to attract clients and recruiters. Did this approach help with that? (40:06)

Building reputation, structuring learning, and leveraging course projects

Pastor: Yeah. Once I built my reputation, it became easier to get customers. Outside of Upwork, it was hard to find clients. After the pandemic, many lost clients and jobs became scarce, so I realized I needed to shift focus. (41:03)

Pastor: I tried your course. Before that, I didn’t even have a LinkedIn account, but I knew LinkedIn was a good place to find work. I opened an account and started posting there. (41:03)

Pastor: One interesting thing about posting online is that your audience grows with you. If you start sharing as a beginner, eventually your audience will include senior engineers who have followed you for years and might want to work with you. That’s something you need to keep in mind. (41:03)

Alexey: That’s cool. You didn’t even have a LinkedIn account before the course and created one just to post for points, right? (42:46)

Pastor: Yeah, I’m competitive. I even did two capstone projects because I missed the first week and started at a disadvantage. I climbed the leaderboard from a low position. Those two capstone projects really paid off. (42:59)

Alexey: Good work. How did you structure your work, especially sharing what you learn publicly? For me, preparing content is difficult. In our courses, we give seven points per week to encourage posting daily, but posting every day is not easy, even for longtime social media users. How did you manage that? Did you take daily notes? How did you structure your learning in public? (43:24)

Pastor: Sometimes I waited till the deadline and posted multiple times in a day. Usually, I took a lot of notes using Notion or Google Docs. Knowing I wanted to create content helped me write better notes because I was preparing something to share. (44:15)

Pastor: I didn’t overcomplicate posts. Sometimes I posted small fragments or quotes from what I learned. For example, explaining a regression model or what R-squared means can lead to many posts from just one topic. (44:15)

Pastor: I structured my posts by videos, aiming to get one post per video, which helped a lot. (44:15)

Alexey: Preparing posts requires notes, which means structuring your learning. So, not only does sharing publicly help others, it also helps you process and learn better. You probably double-check before publishing to ensure accuracy, which reinforces your learning. (45:48)

Pastor: Exactly. You go through the material thoroughly, take notes, grow followers, find recruiters, and learn better all in one process. Doing it all at once saves time because you’re not pulling from multiple places. (46:43)

Alexey: What happened after the course? You finished first on the leaderboard with many extra points and did three projects the midterm and two capstones. Did this help you after finishing? (47:23)

Pastor: Yes. I still share those projects whenever recruiters ask for proof of work or when I have projects needing examples. What stood out is that the projects include deployment, step by step, on AWS. That positions you as a cloud expert and machine learning engineer. (47:48)

Pastor: I used datasets from healthcare like skin cancer and pneumonia detection, which helped explain why I’m both a medical student and a data scientist people often ask why I combine those fields. (48:32)

Pastor: Those projects go through the full data pipeline and are interesting to me. I deployed them as a service capable of inference. Pre-ChatGPT era, you had to do everything yourself, so that was a cool aspect. (48:32)

Pastor: The projects are multi-purpose. I share them widely and am proud of them, even though I haven’t maintained or changed any code since publishing. They’re dockerized and deployed on AWS. The course teaches you to build things to last and be useful to others. Those projects helped me a lot. (49:30)

Alexey: Amazing. There was a question: after learning about machine learning, how did you obtain projects in that area? You partially answered it—sharing your learning attracted interviews, and sharing projects showcased your skills. What else did you do to get projects? (50:18)

Volunteering and mentoring with DeepLearning.AI and Stanford Coding Place

Pastor: When I started posting, I got feedback and followers on LinkedIn and X. I engaged with people and platforms like DeepLearning.AI, becoming a mentor for their courses and testing content. I also volunteered with Coding Place, a Stanford initiative that teaches coding live. Exposing yourself to the market by engaging with people helps. Doing more than average opens opportunities. (50:53)

Pastor: That extra effort helped me market myself as an expert and get projects through LinkedIn. People saw my posts about X and Y problems, then asked if I could help on projects, both freelance and full-time roles. Engaging with communities also brought people asking for help producing their projects. (51:52)

Pastor: You’d be surprised how many hiring opportunities exist outside traditional platforms like Upwork. LinkedIn and communities give broader reach. In ML Zoom Camp, many people join because they face problems needing solutions. If you engage, the chance of someone reaching out is higher. It’s not guaranteed but definitely increases your opportunities. (52:44)

Alexey: That’s amazing. Among other things, you mentioned you became an assistant for deploying AI, right? (53:48)

Pastor: Yes, as a mentor. It’s a voluntary role helping people with problems throughout courses. Being there helped me get an interview with DeepLearning.AI to work with them. Unfortunately, we couldn’t make that happen due to payment processing issues with their client, but it showed opportunities exist if you’re active on the platform. People reach out because you already know the work. (54:07)

Alexey: So you volunteered as a mentor at DeepLearning.AI and almost turned it into a paid job; you just didn’t finalize payment arrangements. You also mentioned the Stanford initiative to teach coding. What is that? (55:01)

Pastor: It’s called Coding Place, a Stanford initiative teaching coding. Every April they release a cohort, assigning volunteers to 10-15 people to teach them coding, following Stanford’s computer science curriculum for beginners. (55:24)

Pastor: I volunteer there, teach many people, provide feedback, and suggest improvements. (55:24)

Pastor: I also mention your courses because their research shows your courses have high retention. People drop out less compared to other courses. They study what helps students stay on track, and your course already implements many effective strategies. I refer to you as an example of good course design. (56:17)

Managing time and staying productive while studying medicine and machine learning

Alexey: Thank you. We should wrap up soon. Here’s a question: medical education is demanding. How did you find time to learn and work on machine learning? You partly answered this; maybe you can expand before we finish. (57:00)

Pastor: Medicine has a huge amount of content. I tried to absorb everything efficiently and avoid repeating work. Whenever I learned something from your course, I took notes and used them both for posts and to build capstone projects. (57:28)

Pastor: Of course, I worked extra hours—waking early, staying up late—which I don’t recommend. Med school was hardest during final exams and hospital rotations. One thing that helped was structuring my time and keeping to-do lists, breaking big goals into smaller steps. Instead of looking at the entire MLS camp content at once, I focused on watching specific videos per day. (57:28)

Pastor: I took opportunities to learn on the bus or on my way to school. Financial savings helped me during rotations when I couldn’t work, as I spent more than 100 hours per week in the hospital. The savings allowed me to focus on rotations without working. (58:49)

Pastor: Learning data helped me accomplish much more in medicine. I don’t think I could have done any of it otherwise. I’ve enjoyed the process as much as possible. (58:49)

Alexey: That’s really cool and motivating. Having limited time forced you to be more effective at learning. (59:53)

Pastor: Exactly. It forced me to be productive and follow the best principles. Sometimes I got tired, but being consistent is what pays off. (1:00:00)

Alexey: Consistency is key—same with running, gym, studying. Thanks a lot for joining us today, Pastor, and sharing your story. I hope it motivates many future ML Zoom Camp students. I wish you all the best in your medical and machine learning careers and whatever you choose next, since your interests are diverse. (1:00:14)

Pastor: Thank you so much, Alex, and thanks everyone. This was really fun. (1:01:02)

Alexey: Well, I’ll see you around. Bye. (1:01:07)

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