A Guide of how to get started in IT in 2023 - Top IT Career Paths

Video Statistics and Information

Video
Captions Word Cloud
Reddit Comments
Captions
In this video I want to give you kind of a road  map of how to get into the IT world, because if   you're watching this video you are most probably  thinking about starting your career in IT.   Well, the tech industry is currently one of  the hottest industries for the job market,   so it's completely logical that so many people are  thinking about changing careers to tech or getting   into Tech just after graduating from school or  college. And it's true that tech industry offers   lots of career opportunities, but when you are at  the very beginning of your journey it can be very   overwhelming too. It is a broad industry with so  many options, so many IT fields and professions.   There is so much to learn and often you don't  even know where to start. It's also hard to know   which IT field you will be interested in and will  eventually choose, before actually trying things   out and seeing for yourself what you enjoy doing  the most. You may even have self-doubt thinking   that it's too late to switch careers or there's  so much to learn you can never catch up with the   people, who have been in tech since early age. And  I understand all these concerns, the self-doubt,   the time pressure, insecure not knowing where and  how to start etc. And that's why with this video   I want to kind of show you various career path  in tech and give you some general guidance for   how to get started. And for every IT field, we  will see whether it's an entry-level profession,   what they actually do and what are some of their  job responsibilities as well as what skills you   need to have to get into that specific field and  some of the technologies you need to learn for it. First of all, I want to start by saying that  it's never too late to get into IT. I myself   transitioned from my marketing and business  studies and had nothing to do with IT before   not even an IT subject at school or college and  switching my career to tech was probably one of   the best decisions of my life! This field is  becoming more popular every year and it comes   with so many benefits and opportunities for  people working in this field. Plus it's an   interesting exciting and fulfilling field to be  in no matter which specialization you choose.   So let's see what are actually some of  the most popular IT professions today,   that will be even more demanded in the future,  so what options you have for IT jobs that you may   want to specialize in. Of course there are many  different statistics and rankings out there and   many names for the similar jobs, but there are  several professions that definitely stand out,   which have become the most popular. The popular  and demanded jobs in IT are usually paid very   high, so many of those rankings are also  based on salary and career growth statistics.   Based on several rankings, the most demanded  and popular IT fields that have been growing   in popularity even more over the years are:  software engineering, DevOps engineering,   cloud engineering, cyber security or security  engineering, data engineering or generally data   related professions and machine learning  engineering. And these top fields will   actually be even more demanded in the future. So  there is a lot of growth and future potential in   each one of those fields. So most of you will  probably want to get into one of those fields,   but many of you as I said may not know right now  what you want to choose exactly, maybe because   they all sound equally exciting for you or equally  overwhelming so you have no idea which one will   be a better choice or which one will be the most  interesting one for you, which is absolutely okay,   because that's exactly what I want to help  you with in this video so let's get into it! First of all, it's absolutely fine to try out  multiple things to see what you like the most.   In fact, it's a really good idea, because you  have so many opportunities, so many options,   so you want to take advantage of that and find the  one that fits you the best. However, you need to   approach this with some structure, just randomly  learning things here and there in the hope to make   sense of many things at once or even worse trying  to learn multiple of those fields at once is not a   good strategy. It will make your learning journey  difficult and it will surely make it longer as   well and you won't properly find out what field  you like the most. So let me help you structure   your learning process by laying out the map that  shows you all these professions individually and   the learning path to those as well as any overlaps  and common knowledge between them. Let's start   with the broadest and the most widely least spread  IT field, which is software engineering. I believe   it's also the easiest entry point into IT and  where most people actually start their IT careers   and that's how I started as well. A software  developer or software engineer is someone,   who develops any kind of software applications.  This can be a web application a mobile or a   desktop application, whenever you think of any  software, whether it's on your computer the mobile   phone in your smart TV. So for example, Amazon,  Netflix and all these applications you use on   your smart TV. These are all software. Or think  about smart cars, again these are applications   for navigation and some other controls of  the car. You have smart homes, software in   production machines and robots. So these are  all software developed by software engineers.   But software engineer is a very broad term itself  and covers many subfields and you can actually   specialize in any of those subfields since they  are each their own separate professions. For   example, you can become a "frontend developer",  which is basically developing the front of the   application, the part that the users see in their  browser or their phone screen or TV screen. You   can become a "backend developer" and develop  the backend part of the application, the part   that connects to the database, saves and updates  user data, processes data and so on. Or you can   become a "full stack developer". They're basically  people, who can develop both frontend and backend   parts of the application. Then you also have  categorizations like "web developer", which is   basically developing web applications that you see  in a computer or laptop browser. You have mobile   app developers, which are developing applications  for Android or iOS. You may be an "IoT developer",   which is "Internet of Things", like software in  your car for your TV the smart home, the smart   lock systems for hotels etc. And you can even  specialize in a specific technology or programming   language or even a framework. So you may choose to  become a "Java developer" a "JavaScript developer"   or maybe a "React developer". You can specialize  in Android development for mobile applications.   You can become a "Python developer". So these are  all separate career paths, because each of these   is already such a big area and field on its own.  So you can go deeper into a chosen technology or   area or you can go broader and become a full  stack engineer as I mentioned. And both have   their values. You need experts in one specific  area, but you also need people, who have a good   overview and knowledge of many things on a higher  level and that's really a personal preference,   whether you are a generalist or a specialist, so  you can decide what you like more. I am personally   a generalist. I like knowing many things and  how they fit together and integrate together   and knowing things on a high level, rather than  deepening my knowledge in one specific area,   but as I said that's a really personal preference.  However, no matter which of these professions or   subfields you choose, you have a pretty similar  entry point for all of those. You have to first   understand basics of software development and  programming. For example you take any programming   language and learn the basics of programming with  that language. Things like variables, functions,   data types and so on, because these concepts are  actually the same for every programming language,   no matter whether it's mobile, web, frontend or  backend development. I usually suggest JavaScript   as the entry point language, if you want to  get into any kind of software development,   because it can be used in frontend and backend  and even in mobile application development,   plus it's easy to learn compared to Java for  example. Once you get the basics right, the second   step will be to actually start developing simple  example projects to really understand how software   is written from scratch. The complete setup of  frontend and backend, whether it's a web or mobile   application, because that's how you really learn  the concepts behind software development. I'm a   big fan of learning anything with an example  project, rather than by book or watching some   tutorials passively. This way you're not learning  just a specific language and what features they   have, you are learning how to develop an actual  application that is usable. So depending on what   you want to specialize in, if it's web development  you can learn HTML and CSS on top of JavaScript   and start creating a little bit more complex web  applications with a database connection. If you   want to go into mobile development you can choose  one of the languages for mobile development and   practice using that language. Every language has  its advantages and disadvantages. Some of them   are cooler, some of them are more widely used, but  the important thing is that you learn the concepts   first, because you can always learn the syntax  or you can even Google the syntax, if you need   to. If you're not sure, which language you want  to choose, always go for the most popular one,   because it increases your chances to get a job  with that language and it has a large community   behind it and it has to be popular for a reason.  So as I said, instead of learning features and   syntax of a language just one by one, take an  example project either from web or think of   your own project and develop that. You will  learn way more in that process of doing it,   but it has to be simple so you don't get stuck and  overwhelmed in the process. And here's the thing,   if you are thinking: "what if I make the wrong  choice and start with the wrong thing and find   out that I don't like it at all?" Well, if you  start with backend web development for example   and after months of learning that, you realize  it's not really for you and you like mobile app   development better, that knowledge is not wasted.  You aren't starting from scratch. That knowledge   that you gained will help you switch to another  area, plus you had a chance to find out what you   like and what you didn't like. In fact, that isn't  wasted even if you decide you want to go into a   completely different area like data engineering  or cloud engineering or DevOps. And I want to   say that, the fields in software engineering are  usually the entry-level tech professions. So it's   relatively easy to get started in IT this way and  later you can always transition to another tech   area. And as I said your knowledge will never be  wasted, because lots of concepts are related and   interconnected in different areas of IT. Your  programming skills will be useful even if you   go to machine learning or DevOps engineering.  Important thing here is not to do everything   at once, as long as you build your knowledge  in tech step by step, like one area at a time,   one programming language and technology at a time  and stick to that for at least six months or so   and then move on to the next thing you should be  fine. Just don't rush from one thing to another,   trying to absorb everything at once, which I know  many of you are probably thinking to do. And if   you do want to start with this path, I actually  have a mini bootcamp for learning everything you   need to know for web development specifically,  full stack development with frontend, backend,   database connection plus even more the complete  software development and release life cycle. And   my goal was exactly to make people's entry in  IT easier and remove that fear of tackling this   scary thing of getting into tech, by making things  simpler and easier. Plus with actual real projects   to make it fun and engaging. Just a shameless plug  here for our IT beginners course. So if you want   to know more about that you can see the video,  where I explain exactly what you learn there   in detail. Now as I said, you can use knowledge  in software development in other IT fields and   software development is actually the best stepping  stone to transition to our next most popular IT   role called "DevOps engineering". So DevOps field  is rising in popularity year by year, it is the   field that I personally found extremely exciting  and some years ago from being a senior software   engineer transitioned to DevOps and if you know  my videos, you also know that my whole channel,   courses and educational programs are all about  DevOps, but very important to note here that   DevOps is not really an entry-level IT profession.  It is a bit more advanced, which means you need to   already have some engineering know-how in order to  transition into DevOps, but what is DevOps anyway?   DevOps is all about automating the processes in  the software development and release life cycle,   which means logically enough that you need to  understand those processes and the whole life   cycle first so you know what you're automating.  So DevOps is a more complex and difficult field,   which I do not recommend to start in if you  have zero IT background, but if you build   up your knowledge step by step and you find it  as interesting as I do, it can be an extremely   rewarding profession. It is a highly demanded and  also highly paid IT profession, because there is   actually a big shortage of these professionals,  probably way more than for software engineers. If   you want to know more about DevOps and what type  of person it is for and what skills you need to   become a DevOps engineer, I actually recommend  you watch my videos from my "DevOps as a career"   playlist, where I explain all of that in detail.  So after watching them you will know exactly "nope   DevOps is definitely not for me" or "yes that's  exactly what I want to do"! So make sure to check   them out, I will also link all the videos that I  mentioned here down in the description as well.   Before we move on to the next profession though,  I want to mention that lots of people transition   to DevOps not only from software development  background but also from systems administration   or test automation or network engineering role  and various other roles actually. I would say   IT professions that are becoming less demanded  or less interesting are moving towards DevOps   engineering, because it is the new hot thing and  if you don't already know about our famous DevOps   bootcamp. Two years ago we actually created the  complete educational program to teach people all   the necessary tools and concepts to become a  DevOps engineer. We have educated more than 2   500 students with this bootcamp so far, but as  I said the DevOps bootcamp is for people with   some level of IT experience or IT pre-knowledge.  And that's why we created the IT Beginners mini   bootcamp to help people with the zero background  learn the fundamentals first they need to,   to even get started into DevOps. So I created this  course actually as a prerequisite for the DevOps   Bootcamp. So if after watching the "DevOps as a  career" videos you decide you want to get into   DevOps, then these two educational programs will  be the perfectly laid out path for you to get   there in the most efficient easy and fast way. But  if you decided DevOps sounds like it's definitely   not for you, then you can consider one of the IT  professions I'm going to talk about next in this   video. So let's continue! The next IT field,  which is actually pretty related to DevOps   is cloud engineering. Very simply explained, a  cloud engineer basically builds and maintains   infrastructure in the cloud. As many companies  move from managing their own infrastructure   to using cloud platforms, Cloud Engineers are  becoming increasingly demanded. Cloud engineering   is also an entry-level profession. If you have  some basic systems administration experience,   then this will be probably the easiest IT  field to transition into, but if you're a   complete IT beginner, you can actually start  your IT journey directly here as well. So how   do you start in cloud engineering? Well in cloud  engineering, there are actually two most popular   cloud platforms out there, which are Amazon's AWS  and Microsoft's Azure. Both of them have various   certifications, which you can take to help you  get a job as a cloud engineer for that specific   cloud platform. So if you want to get started  in this, choose one of those cloud platforms   and start learning for their basic entry-level  certifications and basically specialize in that   cloud platform. I personally suggest choosing AWS,  because it is currently the biggest and most used   cloud platform. A good way to start here will be  using AWS certification programs. AWS has multiple   certifications from basic cloud practitioner to  more advanced certifications. So obviously start   with the basic AWS cloud practitioner certificate  and start learning and preparing for that. This   will give you knowledge in all important AWS  services, but more importantly in the main   concepts of cloud engineering in general. And  remember I said, when you learn one programming   language, learning another programming language  actually becomes way easier because you already   learned many of the common underlying concepts.  The same way if you at some point decide to go for   Azure after learning AWS or you find a dream job  at a dream company, who uses Google Cloud platform   instead, you can learn them way easier, because  you already have learned one Cloud platform and   the basics of cloud with that platform. In fact  learning two cloud platforms will be a major   asset, because you now have a good comparison  between them. So the best starting point will   be getting the cloud practitioner certificate  from AWS to get you the first job in this field.   Now I want to mention here that DevOps and Cloud  often fall into the same category and often they   get mixed up. However even though they have  some overlaps, they are actually two very   different fields and I plan to create a separate  video for DevOps engineer versus Cloud engineer   describing in detail what are the common tasks and  responsibilities, those overlaps as well as what   actually differentiates them. So you understand  exactly the difference between these two   fields. So be sure to subscribe and activate the  notification bell, if you don't want to miss that.   Now cloud, DevOps and software engineering fields  have one thing in common, they all need security.   When you build a cloud infrastructure you need  to secure it, when you program an application   you need to make sure it doesn't have any security  loopholes that hackers may use to hack into your   systems, when you build DevOps processes which  actually affects your application, your cloud   infrastructure and many different systems, again  you have even more security responsibilities to   make sure you don't expose passwords and secret  keys to your systems etc. This means software   developers, cloud engineers and DevOps engineers  they all have to know about security. But security   is an extremely large field and it affects every  piece and step of the software development and   release life cycle and you have security in  other IT fields as well. So we actually have   a separate dedicated profession for IT security  engineers who specialize in all things security.   As a security professional you know security  tools and technologies that help you scan and   identify security issues at different levels as  well as help fix them and also validate that other   engineers have secured their systems properly.  There are even external security companies who   provide services to other companies to secure  their systems. For example they try to hack into   their systems and see where the systems of the  company are vulnerable, because if they can hack   into them, actual hackers can also do that. So as  a security engineer you identify those vulnerable   points and advise the company how to secure them.  Also security as I said is on multiple levels,   every system, every software, that companies  using or developing needs to be secured: so   the infrastructure, the application platform, the  frontend, the backhand, database, the application   itself. So security engineers usually have a wider  cross knowledge of security on all those levels   and can plan a general strategy of securing  the complete setup using various technologies   for automating security checks and security  testing and so on. And it goes without saying   that security engineers have extreme value to the  companies, because security breach is the worst   scenario for any big known company. Cyber attacks  are becoming more and more sophisticated and for   applications, who have millions or hundreds of  millions of users and the user data obviously   the impact of the attack is huge, when data of so  many users is compromised or even think about your   online banking application. Obviously you don't  want them to have any security issues in their   system, right? For this reason there is usually a  tremendous demand for security engineers in many   industries and it's definitely going to become  even more important in the future. So if you   want to go on this challenging but very exciting  path you need to first understand the concepts of   what you are securing. So this is also not really  an entry-level IT position, you definitely need   some pre-knowledge in one of the IT fields like  network engineering, cloud engineering, software   development etc. And on top of that you'll have to  learn many security concepts and tools in order to   develop this general security strategies. When  talking about security, passwords and secret   data is a critical part, so before moving on I  want to give a shout out to Passbolt who made   this video possible. Passbolt is an open source  password manager for agile and DevOps teams and   is built for collaboration. With Passbolt you can  securely generate, store, manage and monitor your   team's credentials. The security model is built on  strong foundations such as: end-to-end encryption,   granular access rights, it is audited regularly  by third party entities, but you can actually   audit it yourself, because it's 100% open  source, even the commercial version of it.   And for maximum privacy you can deploy your own  self-hosted Passbolt server within minutes from a   Raspberry Pi to a high availability setup and then  put it behind your firewall. And also important to   note that Passbolt does not require an internet  connection to be functional. So be sure to check   them out, the link is in the video description.  Now let's move on with the next career path. One   of the hottest IT jobs, which are more in demand  than ever are data related jobs. Now why is that?   When we have software that millions and billions  of people use daily, those users produce loads of   data, right? Think about social media, the  posts and media we create and upload every   minute or every second. Think about search data  generated when millions of people search daily,   GPS data from Google Maps or other applications  that track your location, when you buy groceries   at the supermarket, when you buy stuff online.  So basically the user behavior data. All of   this is data that we humans produce daily  through our digital footprint. But apart from   this human generated data there is also massive  amounts of device generated data, such as cars,   IoT systems through sensors, production machines,  robots, logistics data, shipment tracking. So even   more data than humans generate is coming from  these sources. With all this, the data has grown   dramatically in the last years. In fact worlds  90% of the data was actually generated in the   last two years. As some sources mentioned, we  generate so much data, every single day that if   it were written down in form of books and we  could pile those books on top of each other,   we would have enough to build a bridge to the moon  and back. And because of the sheer volume of this   data, we also call it "Big Data". So that's where  the term comes from. Data has become a precious   asset of any organization, because it helps them  understand things better. Like make predictions,   political campaigns are driven by data, like  you have polls and online searches etc. Many   companies use data to optimize their processes, to  save time and money in those processes. However,   just raw data has no value to the company. Imagine  these are massive amounts of data in raw form,   generated in different formats and from different  sources. It's really difficult for humans to make   sense of data in this form. It only has value  once the data is processed, cleaned, analyzed and   visualized. So it's easy to consume for us humans  and big data related professionals are exactly   the ones, who use tools to turn these massive  amounts of data into usable and extremely valuable   information for companies. And companies can  then use these visualized data to make decisions,   make future predictions, cost optimizations and so  on. And there are various data related professions   with different tasks and responsibilities such as  data analysts, data scientists and data engineer.   So let's see comparisons between them. "Data  analyst" is basically the entry-level profession   if you want to get into this field and is the  easiest to start with. As the name suggests,   data analysts analyze and interpret data to  extract meaningful information from it. So   they need to basically make sense of the data,  like identify any patterns. The main skills they   need to have are knowledge of math and statistics  and various tools that help them in data analytics   and data visualization. But in addition to the  technical skills, data analysts must actually   have a good business and product understanding. So  they analyze the data with the goal to make good   decisions for the business and product development  and then communicate those decisions to people,   who actually need them like, product owners,  business decision makers in the company. However,   data analysts work with already processed and  prepared data. So the raw data needs to be   collected from multiple sources with different  formats and be processed first to be usable   for the data analysts. And this is something that  "data engineers" do. Data engineers need knowledge   of databases and programming to do their job and  data engineers actually build something called   "data pipelines" to collect, store and process  the data. So you can start into data engineering   by learning a programming language like Python  and its data processing frameworks and libraries,   learning databases and query language like SQL  for example and big data specific frameworks   like Apache Hadoop, which is a popular framework  that allows you to store and work with massive   amounts of data. And the third one I mentioned is  a "data scientist", which is usually the highest   paid profession among these three. Now interesting  to mention that companies often use data analysts   and data scientists job titles interchangeably.  Now they are two different professions, but there   are definitely some overlaps between those two.  And one of the overlaps is that you need to have   advanced math and statistics knowledge here as  well. So generally contrary to the popular belief,   you don't need any math or statistics knowledge  for software development and definitely not for   DevOps or cloud engineering, but in data science  or data analytics you will be working with math   and statistics a lot. This means if you want  to get started in one of those fields, the   first thing you need to learn is statistics and  the programming languages for statistics like R   or Python. However in addition to statistics, data  scientists usually require more advanced technical   skills than data analysts and that's where the  main difference between those two professions   lie. So data scientists are usually more  experienced engineers, who can create advanced   machine learning models for example and algorithms  to make future predictions. Which leads us to the   next and final hottest IT profession called a  "Machine Learning Engineer", which actually is   yet another big data related profession. We said  that data analysts and data scientists use data   to analyze trends and identify patterns and make  some decisions and predictions based on the data.   So data can be used by humans to make data-driven  decisions, but data can also be used by machines   by programs, so that clean processed data that  data engineers prepare can be fed into machines,   so they can learn from them and they can use them  for different tasks. And that's where machine   learning actually comes in. Now what is machine  learning exactly and why do machines need data,   what do they do with it? In software development  we write programs and instruct them to do   something. In machine learning, machines can  perform a task without being explicitly programmed   to do so. How do they do that? They learn how  to perform that task from large amounts of data   using algorithms, which are also called machine  learning algorithms. So machine learning is about   computers being able to think and act without  being explicitly told or programmed to do so   and there are two main parts of this process.  First one is writing the machine learning   algorithms so that machines can use them to  learn and the second part is feeding large   sets of processed data into those algorithms,  so basically using the data to train the model.   Again there are some overlaps between data  scientists and machine learning engineers that   you will encounter, they both need strong math  and statistics skills to work with data, however,   while data scientists focus on making sense of  the data, visualizing and presenting it better,   machine learning focuses on using the data for  machines to learn to carry out certain tasks.   So entry into machine learning engineering is  actually pretty similar to data science. You   need to start by learning a programming language  like Python, which has powerful machine learning   frameworks and statistics, which is a  very important part of machine learning   engineering. Now you probably already noticed  that in all those fields I actually mentioned   Python programming language and that's because  Python is a general purpose language. You can   use it in every single one of those areas,  however that does not mean that you need the   same Python knowledge in each field. Using Python  for web development is completely different from   using Python for DevOps automation or machine  learning and that's an important difference. So   first you learn the Python core with its syntax  and general programming concepts and then you   learn the specific libraries and frameworks  for each IT field on top of that Python core.   So you have completely different frameworks  and libraries for web development and machine   learning and DevOps automation, which you need to  learn for that specific field. So you basically   learn different parts of Python for each field and  that's an important thing to differentiate. Python   language just happens to have popular frameworks  for all those fields and their use cases, but of   course the Python core is the same everywhere  and if you want to learn Python core, like   syntax and programming concepts of Python, you  can definitely check our free course on Python,   which I will link right here. So we've covered  a bunch of career options in IT and I tried to   categorize them so you have a better overview and  comparison between them. So hopefully something   stood out for you where you think: "well that  field sounds pretty interesting to me so I'd   like to get into that field". Now of course when  you know approximately which direction you want   to go and what you want to start learning, the  next question becomes:"where and how do you learn   this?" Do you get a college degree in computer  science? Do you take an online course? Do you join   a data science bootcamp or a coding bootcamp or  our DevOps bootcamp? Well, I personally started my   informatics studies at a technical university, but  I was using mostly online resources for my studies   like YouTube videos and some coding websites.  And as soon as I got an internship as a software   developer in my second semester, I actually quit  my studies and used my work to learn by doing,   because at work I was actually learning way more  practical stuff that I actually needed for my   job than at the university. But learning at work  wasn't always easy, so I continued learning new   things from YouTube videos and blog articles and  online courses. I was often all over the place   trying to learn anything and everything that I  stumbled upon. I didn't really have a roadmap   that I could follow, but it was still useful in  some way. So I still think that online resources   are one of the best ways to learn, especially  in IT field, but as I said having some kind   of road map and structure definitely makes the  learning journey easier, because you don't just   learn things randomly, but you learn things in a  certain order without being distracted by massive   amounts of information. So whatever field you  want to choose: Go find a clear roadmap for that   profession. There are various articles and videos  about those roadmaps and then just try to follow   that roadmap. And of course if you decide for  DevOps, as I mentioned we have a complete roadmap   for that, even if you're starting off without  any IT background, so you don't need to do the   research, put together a learning course and find  good resources. We have done that whole work for   you. You just follow along and learn by doing  and if you know my videos I create the content   with the goal of giving practical actual usable  knowledge with easy explanations. I love helping   people learn easily without getting frustrated and  being overwhelmed. So generally as you see, you   have various options, choose an entry-level career  based on what you want to do later and you can   build on top of that. And again no knowledge is  wasted in IT, everything is still interconnected,   so if you start in software development and  later want to do DevOps or machine learning   or cloud engineering you can still benefit from  that knowledge and won't be starting from scratch   in that field. So if you don't know yet where  you want to end up you can start with any one of   those, maybe the easiest one and you can always  progress in any other direction later. I hope I   was able to help you make these important decision  for your future, you definitely made the right   decision by choosing IT in general. With that,  all the best and see you in the next video! :)
Info
Channel: TechWorld with Nana
Views: 181,290
Rating: undefined out of 5
Keywords: it career paths 2023, it career paths 2022, it career paths for beginners, how to get into it, how to get started in it, top it career paths, top tech careers, career in it, career in tech, techworld with nana, software engineering, different it careers, data science, machine learning, it security engineer, devops engineering, cloud engineering, roadmap for software engineer, roadmap for cloud engineer, roadmap for data scientist, roadmap for web developer, cyber security
Id: XmWkcePhf84
Channel Id: undefined
Length: 37min 39sec (2259 seconds)
Published: Mon Dec 19 2022
Related Videos
Note
Please note that this website is currently a work in progress! Lots of interesting data and statistics to come.