Statistics, Linear Algebra, and Breaking into Data Science
This lesson addresses a question from a medical doctor interested in transitioning into clinical data science. The discussion explores statistics, linear algebra, programming, professional development, and how individuals can strategically prepare for careers that require technical and analytical skills. :contentReference[oaicite:0]{index=0}
Why Statistics and Linear Algebra Matter
The lesson begins by examining the mathematical foundations commonly associated with modern data science.
Students interested in data science frequently encounter:
- Statistics.
- Probability.
- Linear Algebra.
- Computer Programming.
- Data Visualization.
- Scientific Computing.
The lesson argues that statistics and linear algebra serve as two of the most important mathematical foundations for understanding how data is organized, analyzed, interpreted, and communicated. :contentReference[oaicite:1]{index=1}
Statistics helps explain data. Linear algebra helps computers process data.
Changing Career Directions
A major theme throughout the lesson is career transition.
Many professionals eventually discover interests that differ from the path they originally followed.
The lesson emphasizes that changing direction does not erase previous accomplishments.
Instead, existing experience often becomes an advantage when entering a related field.
For example:
- Medical knowledge supports clinical analytics.
- Scientific training supports research.
- Professional experience supports leadership.
- Technical communication supports collaboration.
Rather than starting from zero, individuals often build upon skills they have already developed. :contentReference[oaicite:2]{index=2}
Start with Job Applications
One of the strongest recommendations presented in the lesson is to begin by studying job applications.
Students and professionals are encouraged to:
- Find five companies.
- Identify desired positions.
- Review the skills requested.
- Review the software requested.
- Review the experience requested.
- Create a learning plan from those requirements.
This process helps eliminate guesswork and allows learning efforts to focus directly on marketable skills. :contentReference[oaicite:3]{index=3}
The fastest way to discover what you need to learn is to study the jobs you eventually want.
Building Skills Takes Time
Another major point emphasized throughout the lesson is that technical skills require years rather than weeks to develop.
Examples include:
- Programming.
- Statistics.
- Data analysis.
- Professional writing.
- Scientific communication.
- Software proficiency.
While introductory exposure can happen quickly, genuine mastery requires repeated practice and long term experience. :contentReference[oaicite:4]{index=4}
Exposure Versus Mastery
The lesson introduces an important distinction:
Exposure is not the same as mastery.
Students should determine:
- Which skills require familiarity.
- Which skills require competence.
- Which skills require mastery.
Not every tool must be mastered to the same degree. Some tools require only familiarity, while others become central components of a professional career. :contentReference[oaicite:5]{index=5}
The Textbook Method
The lesson discusses a learning strategy built around textbook driven education.
The process includes:
- Identifying required skills.
- Researching those skills.
- Studying authoritative resources.
- Documenting progress.
- Teaching concepts to others.
- Building a portfolio of work.
The goal is not simply consuming information but transforming knowledge into demonstrable skills. :contentReference[oaicite:6]{index=6}
Creating Proof of Competence
A recurring theme throughout the lesson is evidence.
Employers generally want proof that applicants can perform the work they claim to understand.
Examples of proof include:
- Projects.
- Portfolios.
- Websites.
- Research papers.
- Technical writing.
- Published materials.
The lesson encourages students to document their growth rather than simply listing skills on a resume. :contentReference[oaicite:7]{index=7}
Confidence is useful, but evidence is what convinces employers.
Possible Paths into Data Science
Several possible approaches are discussed for entering a data science related field:
- Independent study.
- Professional certificates.
- Boot camps.
- Graduate programs.
- Employer sponsored training.
- Industry specific experience.
The lesson emphasizes that different individuals may choose different paths depending on their educational background, professional goals, and available opportunities. :contentReference[oaicite:8]{index=8}
The Railroad Track Analogy
One of the central analogies used throughout the lesson compares guidance to railroad tracks.
The railroad tracks do not move the train.
The individual still performs the work necessary to move forward.
However, the tracks reduce the likelihood of becoming lost or drifting away from the intended destination.
The lesson uses this analogy to explain the purpose of mentorship, structured programs, and long term planning. :contentReference[oaicite:9]{index=9}
Final Message
This lesson emphasizes that transitioning into technical fields such as data science requires patience, planning, and long term skill development. By identifying the skills employers actually request, developing those skills deliberately, and creating evidence of competence through projects and documentation, students and professionals can steadily move toward new opportunities and career goals. :contentReference[oaicite:10]{index=10}
Original Transcript
All right, little boys and girls. We have ourselves a request for information. I’m on the I’m on the Instagram comments, so you won’t see this comment on the tube of the use, but I will post as a video on the YouTube. At this very moment, I have a video going viral on Instagram. In the past couple hours, I had 400 people subscribe. I’m at almost 13,000 now. Took me a decade to crack the Instagram shell. Like for real. You guys have no idea. 10 years of Instagram posting before I got a follower. Now I Now I’m going viral. Um, Dr. Sebastian, I won’t use your last name, says, “Hello. I really liked your videos and wanted to ask for your opinion.” Now, those of you who are in college or high school, I want you to understand I’m reading a message from a doctor, a medical doctor, and they edited their comment properly. Okay, without AI, you can tell. Uh, at least I think without AI, I can usually tell, but maybe not. Whatever. So, let me read it. I’m a medical doctor and I’m about to start a fellowship in clinical data science. After watching my content, your he says your content, my content, I started thinking that uh maybe the most important foundations are statistics and linear algebra. Uh you’re going to do data science. Yes, those are two things that are probably So, so hold on before I finish. Hey Siri, define data science.
Data science is an interdicciplinary academic field that uses statistics, scientific computing, scientific methods, processing, scientific visualization. You’re doing computer work, you’re doing data science, statistics, and linear algebra. You’re making the connections. It’s it’s a it’s a pretty clear connection to make. So, the doctor says, I have a very basic programming knowledge and some statistics background from epidem epidemology. Epidemology, is that how you pronounce that? Epidem whatever in medical school. But I’d love to know your perspective on whether that this is the right path to get into clinical data science from scratch. Well, there’s a giant truck. I got my window open today. It’s summer some almost summer time. I can open the window today because it’s Memorial Day and I live downtown and I don’t have to be subjected to the everyday average noise of construction because it’s a holiday. So, I get to open my dwindle once a year, basically. Well, first of all, homie, let me address something to you. I’m not a god. I just play one on YouTube. And that’s a lowercase G god, meaning I don’t know everything. I’m the god of thunder. I’m the god of man boobs. Whatever you want to look at it, however you want to look at it. Uh, in your situation, I have no idea how to get into clinical data science. Um, I I imagine that having a medical degree will help you get into that. Uh, but I I don’t know anything about that. So, I do know, however, I do understand how to get to where you want to be. It’s the same path. Let me re let me revise that. It’s the same road for everybody, but it’s a different lane, you know? It’s like we’re all going down the same path. Just I don’t know. It’s the same It’s how to word that right. It’s the It’s this. It’s a different destination going down the same road. That’s what I would say. Uh kind of like I don’t know, Plinko like like reverse Plinko where you can choose where you’re going to end up. Um, so, so let me let me let me let me talk to you because I open the window and now all the noisy cars come by. You guys can’t hear it probably because the mic. This is a dynamic mic, so you probably can’t hear what I’m hearing, but it’s disturbing. It was all quiet and peaceful until I turn on the mic. And when I do that,
the noise comes and my dog gets antsy. So, I I get I have the opportunity right now to practice the art of patience and calmness. Because because I got psycho dog over here and noise out there and I’m trying to concentrate and focus and I want to be like so you imagine a surgeon Mr. Doctor working on a body and having unstable emotions. In order to be that level of a human, you must take emotions and remove them from the equation. saves the emotions for the bedroom. Okay. Uh anyways, Mr. Doctor, I I I respond to your question because you’re a medical doctor and you you typed it up nicely. Most most of the questions people ask me, it’s just the same thing. It’s a magic eightball situation. I don’t know anything about your field, man, at all. I know everything about math, physics, engineering, computer science. I don’t know anything about the medical field. Um I have a neighbor that he’s a medical doctor and got kicked out for smoking weed or something. I don’t know. Funny guy. I have doctor friends that are staticians and, you know, other doctor friends that are physicists, mathematicians, and medical doctors. You know, there’s some medical doctors that I met, whatever. I don’t know. But I don’t know. I don’t know what you need to do, but I know how to do it. I’ll put it that way. what you’re trying to do. It sounds to me what you’re trying to do is you’re trying to get into a field that you don’t necessarily have that much experience in. And as a medical doctor, based on your ethnicity, I imagine that your family probably forced you into it and it’s not entirely your forte. And now that you accomplish the goal that you’ve been forced into, you’re ready to branch out into what you want to do, more or less, because you did what they wanted you to do. Now you’re released. You can do what you want to do. Parents have bragging rights. My child’s a doctor. A medical doctor. A real doctor. I get to brag about my child who I’ve tormented and has gray hair now. I I see that all the time when I go to the hospital and I see a medical doctor that’s 30 years old with gray hair. I’m like, “God, your parents abused the crap out of you.” All so they can brag to their friends over cocktails how great their kid is. I meet a lot of people like this. There’s a lot of parents. It’s disgusting. Sick. It they’re they’re a threat to all of us. Arrogant, narcissistic, egotistical parents that force their kids to accomplish something that the kid’s not meant to do is dangerous for the rest of us. You don’t force an aunt to make honey because you want to live in a beehive. All right? It’s dangerous for us. My my child graduated to the beehive. They’re vomiting up honey every day. Can they make the honey? No, they eat it and they throw it up back into the honeypool. They’re a doctor. I don’t know if that’s what happened to you, but uh I just make I make the connection. I think that if you’re not going to go be a medical doctor and you want to go into data science, probably because you have an interest in science and numbers and arithmetic and whatever and I don’t know. I I you just left a couple paragraphs of information. Okay. So, I’m responding to tell you what the purpose of this is. Not that I’m suggesting to sign up for PLM Academy. You’re already accomplished. You’re fine. The purpose of Plem Academy is is you may already have a doctorate, a medical degree, whatever. And you don’t have to sign up for this, but I’m going to tell you the point of it because if you’ve already accomplished, then you don’t need to. You got a resume. You don’t know what you need to do for data science. Well, what I do with Plum Academy, what I recommend for you is I recommend you go look at five companies. This is the whole purpose of Plleum Academy. Go look at five different companies that you’re interested in working for with the degree that you are interested in seeking that are looking to hire somebody with that degree. Okay? go look at those job applications and look at the skills and qualifications required to apply for that job. And so what I do with the PLM Academy students is that’s the first thing they do is they go look at five applications for five different companies. Well, not five applications per se, but five companies and they look at five different applications from five different companies or five different companies, multiple applications from the same companies in the field they’re interested in working. They look at the skills and they look at the qualifications. You watched my video telling say talking about applied applied ma mathematics with a um minor in computer science being a a winning golden ticket for you know having a career job security and high pay and that’s true if you’re capable if you’re not capable don’t do it but in your situation so you you watched that video and I said statistics and linear algebra is very important and I tell you that what we look at what data science is statistics and computer science which is linear applications of linear algebra modern algebra abstract algebra probably a little bit maybe or just yeah I don’t abstract modern abstract algebra ring theory and stuff so in your situation my advice for you is simple do what I have my PLM academy students do go five go find five companies that you’d be interested in working for as a data science clinical data scientist and look at what the skills and qualifications are requesting and then spend the necessary time developing those skills. It can take years if you’re transitioning careers into a different path. I don’t know. I’m not sure exactly, you know, I don’t need to know. Okay? I I I just I’m just telling you that I I’m I’m trained as a mathematician. If I want to go work in data science now, I’m gonna have to spend a couple years mastering a whole bunch of random softwares and stuff in order to be able to apply for a job. Statistics. Statistics is fairly easy to learn, but it takes years to understand. Memorizing solutions and plugging a number into a box doesn’t take any time to do, but you don’t understand any of it. It takes years to understand this stuff, which is what the purpose of this company is, is to give you those years of experience. IV dripping knowledge into you slowly is very similar to like building up to bench pressing a certain amount of weight or something. You add like five pounds every week for like a year until you get to the to the desired weight that you want to bench.
You you can do the same thing on your own. You just have to slowly integrate all of this different software that you need to know. I don’t know what what I’m telling you is I don’t know what you need to know, but I know how you can find out what you need to know and I know how you can gain those skills without go getting without going and getting another degree. Uh that’s the purpose of this is like I you the kids that are actively pursuing an undergraduate degree, they look five years down the road at jobs they’re going to apply for. They look at the skills and qualifications and then they write a whole textbook over a 36-month period approximately, give or take. And that book is designed to explain to somebody else how to find that software, how to use that software, how to integrate it into application of everyday things, and then to host it on their own website for a future employer to see that they do know how to do this and they have a book explaining it that they wrote. You can do something very similar. All right? You can do something very similar. So, I don’t know what you need to know. I don’t know anything about that field. It’s not my business too, but Plym Academy creates a structure, a a guided structure so that you can find out what those things are and create a vessel that delivers the proof to a future employer that you are capable of doing those things. And uh Plum Academy is not just it’s Plum Academy is physics, language, engineering, mathematics. started it and coined this name because I’m trying to show college students how to read textbooks and prepare their resume and I just happen to be a mathematician and a physicist with engineering experience. So I focused on that but then I realized after many many comments from non plem majors that they find that my service of what I’m offering is extremely valuable and they’re interested in it. So, it can be adapted quite easily to everybody else’s goals because that’s what it is. You look at the jobs you want to apply for and you write a list of like 10 to 20 skills and softwares and things you need to have and then you write a book explaining to somebody else how to introduce yourself to those and use them. You don’t have to be an expert at it. You just on most of these companies, they want familiarity. They don’t need to see a degree in this, this, and this. They don’t need to see a certificate in this, this, and this. They need to see that you’re confident and that you can back up your confidence. That’s what I’m offering to these students. For you, you know, I I’d imagine it’s it’s not a service that you’d want to sign up for. Maybe it is. I don’t know. It’s up to you. I have a nonpleas monthly mentorship meeting. The most of the mentorship meetings we do are problem solving from textbooks. And I’m going to be integrating statistics and probability and other things, computer programming and chemistry. Over the years, I’ll be integrating everything and anything into this. I can only do so much information on my own though. But I’m not trying to teach you guys math. This is not a place to learn math, okay? Even though I say on the website, it’s a place to truly learn math. It’s not a place to be taught math. Nobody can be taught. You can only choose to learn. I’m showing you how to choose to learn. I’m showing I take textbooks I’ve never seen before. You have any idea how difficult it is to take an advanced math or physics or engineering textbook that you’ve never seen before and just open to like the middle of the book and choose a problem at random and solve it live on demand using the book and only the book. That’s what I do. We did the frobinius one solution series solutions to differential equations the other day. It’s a five hour live session of me breaking it all down putting together a formula to solve the problem and then prove that the answer is correct. That’s what I do. I show kids how to learn from the textbook properly and then you’re supposed to take that knowledge and go do it on your own. So, I do a monthly mentorship for the non- STEM, nonPLEM majors just to Q&A like, hey, I’m doing this website. I’m building this website. I’m putting this book together and you know, should I be doing this or that or I have questions on this? Mo most of the time, you don’t really need the mentorship meeting because you know what to do. I have all the step-by-step instructions on what to do. So, I don’t I mean, I don’t I don’t know. The only thing I can tell you advice-wise, look, every student that’s signs up for Plem Academy has a different career and a different educational goal. So, what they do is they look at job applications and they look at what they need to know because there’s thousands and thousands of different things that every that can be known and each individual person needs to know a little bit of like 10 to 20 different things out of that pool of thousands of things. It’s different for every single student. So for you, the best thing to do is to go look at job applications for clinical data science and find out what you need to have on your resume to get a job and then focus on understanding that stuff. It takes a long time, a very long time. You there there’s a difference between crunching through a course and getting exposure to a topic and mastering a topic. What you need to do is figure out what you need to do. Do you need exposure or do you need mastery? And then you need to find out what you need exposure to, familiarity, and what you need mastery to and do that. And you do that, it takes a long time. If it’s this is a completely foreign world to you, it probably take two to four years before you could apply for a job.
So, I don’t know. You know, that’s my my objective is I created a a rail for a train to be on and the students are the train. They still have to take the shovel and dump the coal into the fire pit to keep it moving. I’m just a I’m just a railroad track to keep them going down the correct path as they do the work. You understand? The amount of work it takes to put a railroad track down is astronomical. And then the person that is driving the train or whatever conducting still has to do the work to shovel the coal in there. Still a lot of work. But they don’t have to worry about getting to the wrong destination because I did all the work to make sure that as long as you stay on track, which you will if you follow through that you’ll get to the destination.
In your case, all you want to know is the truth. And the truth is that it takes years to develop these skills. Hence, the resume, the application says x amount of years required. Can’t just pick this stuff up on the fly. It takes years.
Go look at job applications. Find out what you need to know and start working on them. If you want to join Plleum Academy, if that’s something you’re interested in, what you do is you get instructions on writing your own textbook under my guidance. And the first thing you do before you start writing it is you go and you look at applications and you find the stuff you need help with. And then each section, chapter, subsection, everything in that book is instructions to somebody else on how to break into understanding that. Before you start doing that part, you write a research paper, a short research paper on what the software is or what the skill is and why it’s important. And you document that first before you go into using it so that you understand why you need to know what it is and why you need to know how to use it. You can do this on your own. All of you can do this on your own. I’m just the railroad track. It ensures that while you’re doing the work, you arrive at the correct destination. If you do it on your own, you might get lost. It gets dark, you can’t see the railroad track, next thing you know, you’re two miles away from it. You know, that’s kind of the point of the service. Of course, you get thousands and thousands of lessons that I make and the mentorship meetings and all that, but uh I I’m not trying to promote the that service to you. That service is for people who are interested in it. I’m just telling you that the objective of it can be done sole on on your own solely or whatever but uh from what I gather is you’re switching fields from being a medical doctor to data science in the clinical world since you have a medical background and you don’t have the appropriate math physics knowledge not physics per se but the math statistics knowledge and computer programming knowledge to go into that field right away and you’d like to and if you want if you want to get into a field like that. What I’d recommend doing is, as I said, look at the job applications for what you need to know. And then I’d go look at like boot camps, certificates, you know, short-term things that can quickly get you to understand that material and do those things. Or you could go do a second bachelor’s degree or not with your level of education, you do a master’s. You would go do a master’s degree, probably like an online program. There’s a lot out there. And the master’s degree would then completely channel you directly where you want to go. Take about two or three years or so to do it. So that’s the other option. So you can go do a master’s degree in data science with a medical doctor and a master’s degree in data science. Obviously, you’re going to be highly desired at a lot of companies for clinical stuff. that or you can apply at Epic Systems and they’ll hire you immediately and they’ll teach you everything about data science in relation to Epic Systems and they’ll pay you because they’d probably hire you in two seconds with a medical degree like that. There’s that option, too. Go work for a company that will train you in this stuff. You want to work in that field, contact Epic Systems, Verona, Wisconsin. contact them and say, “Hey, I’m a medical doctor. I want to do data science.” They’ll say, “Great. We’ll give you a quarter million dollars a year and we’ll train you to do that for Epic. That’s an option. Something like that. Your choice.” So, you know, I don’t really have much advice on this. It’s not my It’s not my specialty. And what I’m doing with Pllem Academy, it tailors you to your specialty. you’re just being guided by a professional that makes sure it comes out top-notch and correct and you work with a team of people and I supply you with with a bunch of stuff. But in your case, I mean, for you, I think going back and doing a master’s degree in data science or looking at what you need from job applications and focusing on gaining those skills or find a company that would hire you at your level of education and train you in that stuff for that company. That would be my options as far as statistics and linear algebra go. Anything related to math, statistics, computer programming, you’re going to need to know a fair amount about statistics and linear algebra. That’s what it is. It’s statistics. I run a business. I’m constantly doing statistics. How many people are interested in my service based on how many views I get? How many views do I get from people that are that are like related to my service? How many people do I have to have to sign up to make it worthwhile? How much do I need to charge? Material cost, input, output, all of these different things. There is a ton of moving pieces to a very simple business that I run. It’s it’s astronomical the amount of moving pieces there are to what I do. And it’s very basic. So, I do statistics all the time in that sense because I I need to know the averages. I need to know statistically speaking, if I do this, what’s the outcome? And then you want to have the statistics never come out the way you think they are, but you want to have the statistics to be such a heavy heavy on this side so that even if it doesn’t come out that way, it’s still enough weight to push down, you know, the goal that you’re trying to press. Probability is a different story. Linear algebra is just how you deal with technology and getting it to do what you want to do, to find things, all these different things. Linear algebra is a fascinating subject. It’s not It’s not that hard to learn. It just takes time. Long time. So, that’s that’s all I got to say to you, homie. Congratulations on being a medical doctor. You can go join the ranks of drug dealers and robbing people. Or you can join the ranks of scientists and tell the truth. It sounds to me like you want to tell the truth. Choose wisely, my child. Plumb academy. All you got to do is look at job applications. Okay, look and see what they want you to know and then go learn it. It’s all you got to do. Have a nice day. Thanks for the comment.