AI Engineer Roadmap | How I'd Learn AI in 2024

we are going through a gold rush companies have started investing billions of dollars in AI projects and there is one career role that is going to benefit the most out of this boom AI engineer or ml engineer in my company at lck Technologies I hire AI Engineers I have previously worked with Bloomberg and Nvidia based on my industry experience I'm going to discuss a road map with week by week study plan using free learning resources and checklist that you can use to become an AI engineer AI engineers make highest amount of salary among all the

technical roles what I'm showing you on the screen is just a range the exit salary depends on your skills and experience the company that is hiring and the location now obviously if company's paying you such a high salary they will have a high expectation therefore preparing for AI engineer requires a lot of hard work if you're looking for any shortcut then please leave this video right now because this road map will require 4 hours of dedicated study for 8 months and that will help you set a strong base the actual learning is a lifelong process

before you begin the study you need to figure out if this is the right career for you and the way you can find it out is you need to evaluate if you have interest in coding and math AI job requires strong coding and math skills and without that you cannot become a engineer so if you don't have interest or skills in any of these two then don't go for a engineer this is not the end of the road because there are other career roles as well such as AI sales representative AI product manager AI ethics

executive Etc we will not only talk about tool skills we will also discuss core skills and all learning resources associated with it once we have discussed upskilling we'll also discuss how you can show showcase your work to the world so that you can get an interview call and crack an interview in case you are confused about data scientist and AI engineer role think of it as data scientist plus software engineer is equal to AI engineer that's a very simple way of looking Ed it here is a road map PDF you can download it from video

description below requires 8 months of study 4 hours every day and the week zero starts with proper research folks there are so many scams going on in the market so if you buy a wrong course or if you learn from an instructor who doesn't have industry experience let's say or who is not legitimate then you will get into trouble nowadays you see many YouTubers many people teaching on online learning platforms they claim that their courses are the best but when you look at their background they don't have experience they just know how to talk nicely

and they conduct all kind of scams we have created couple of LinkedIn post which you can look at it and make sure you don't get into those scams we are in fact running a scam awareness program once you have done enough research week one and two will go into learning computer science fundamentals if you have computer science degree you are covered but let's say you don't have Computer Science Background then I will suggest you go through this Khan academic course which covers the basics such as bits and bites storing text and numbers basic B of

computer networks HTTP worldwide web basics of programming and so on once again look at this particular equation you need to have solid software engineering fundamentals in order to become AI engineer here is the course which is free and you need to just finish the first four modules remaining modules you can go over it if you have interest in time but the four modules are good enough enough Khan Academy is a very good platform this person teaches you very well along with the practice exercises in week three and four you will focus on python python is

the most popular programming language in the AI world today learning python is actually very easy you need to start with these basic concepts okay and we have a playlist on YouTube this is on my channel and the other playlist is on Cory shaffer's Channel you can refer to whichever tutorials you feel comfortable with in this stage I would suggest you go through only first 16 tutorials because that will cover the beginner's logic in Python and as an assignment you'll have to finish all the exercises so if you click on this link you will see all

the exercises okay so let's say there is an exercise and there is a solution link as well I know you all are sincer students so you will practice on your own and then only you will look at the exercise exercises now in this time period week three and four along with python you need to learn some soft skills which are those soft skills well you need to build a LinkedIn profile LinkedIn is the platform that will help you get a job eventually therefore you should not wait until you done with all your technical skills the

approach I suggest is in parallel you will start building LinkedIn profile and all other softes okay we have created a check list that will help you make your LinkedIn profile stronger all you have to do is follow all this guideline check check check and once you have checked all these check boxes your LinkedIn profile will look nice once you have covered the python Basics week five and six you should focus on data structures and algorithms as a ml engineer or AI engineer you will be writing programs which needs to scale so you need to know

the trade-off between memory and CPU you need to have deeper understanding on how the data structures work underneath okay and for that we have once again a YouTube playlist it's a free uh Learning Resource the playlist contains exercises as well so you can go through all the data structures and algorithm it will take you 2 weeks time period to go through all of these and also practice those exercises now this is going to be a long learning Journey it's very important that you keep yourself motivated for that I have included some inspirational videos for example

in this video I interviewed tanul Singh who was a mechanical engineer and he used Kagel platform to become ml engineer he's sharing a lot of useful tips and insights so please go through this video while you are learning your technical skills in week seven and8 now you can learn Advanced python such as what is inheritance generators iterator when you writing big programs for Enterprises which scales well or which is doing a huge volume of data processing knowing all these concepts are going to be extremely beneficial when I was at Bloomberg we were using generators and

iterators a lot because we used to deal with huge objects and when you're running a full loop it's hard to keep those objects in memory so using generator you can return it on the Fly list comprehensions are going to be super important for optimizing your program multi-threading and multiprocessing is very useful when you want to uh utilize your computer resources such as the course or even multiple processor within the computer to achieve a high throughput for this once again refer to the same playlist but in this uh you should go through video number 17 227

and all of these videos have exercises so make sure you watch the video and cover the exercises in all these videos I will be talking about Theory then we'll be writing some code and then there will be an exercise in terms of soft skills you should start following some prominent AI influencers on LinkedIn one of them is for example natin he is a head of AI services at Google and he writes posts which will talk about the current trends he will also talk about the hiring trends that he's seeing because he himself hire a lot

of AI engineers in his team I find reading his post to be extremely useful the other person is dalana she writes mainly on data science Ai and data science are kind of overlapping so therefore you can follow all the post on data science as well so follow all these influencers and spend let's say half an hour every day that way you're keeping yourself up to date and also you are becoming active on LinkedIn you should also start commenting meaningfully on those post when you comment on anybody's post what happens is your post if it is

having valuable content your post or your comment then it will get an engagement okay so let's say this post got 155 likes some of these people who are giving you likes could be hiring managers or they could be AI Engineers working in other company so this way you are building a relationship with those folks and tomorrow when you're looking for a job maybe they will give you a referal or maybe they will hire you in their own team building relationship ship on LinkedIn is super important and you posting comments valuable comments okay don't post comments

like this okay true Absolut right because that will not generate any engagement you're not adding any value but when you add some value to the post you are omitting your personality in this online world of LinkedIn and that will help you build relationship that will help you get attention to your profile remember that online presence is a new new form of resume along with online presence you need to also think about business fundamentals as an AI engineer you will be working in some industry Retail Finance any industry if you have good understanding of business Concepts

it will help you communicate better with the stakeholders which are involved in your project to learn the business Concepts I will suggest you follow this think school YouTube channel okay so I'll will show you one video where he talked about how amul beat the competition and here he's talking about numbers and strategies and dairy industry in general so when you go through these kind of business studies you are building your business understanding you're developing a business acument okay Additionally you need to learn the art of asking questions Discord is a platform which allows you to

ask questions while you are learning let's say python SQL whatever and if you have question where should you go one of the ways is asking questions in Discord server okay now there are many Discord servers for code basics for our Channel we have this Discord server which has around 33,000 members okay and if you have question let's say uh for Math and statistics or let's say for machine learning you can post a question and the community members will answer those questions now asking questions is an art do not just copy paste the error that you're

facing and ask for the help because then people will not help you because you're looking for spoon fitting the right approach is to look for direction not the spoon feeding I have highlighted that art in this particular LinkedIn post I have link linked it here you can go through it and your assignment for this time duration will be to write meaningful comments on at least 10 AI related LinkedIn post and KN down your key learnings from three case studies on things School and share them with your friend as in when you finishing those assignments you

can just keep on marking them that way you are tracking a progress as an AI engineer you will not be working alone on a project you will be working with a team now how do you collaborate with the team how do you share your code with the team how do you review that code well the way to do that is via Version Control therefore you need to have sound understanding of Version Control Systems such as git G Hub is a website which is using git as an underlying Version Control System there is another website called

gitlab too okay but GitHub is very popular develop an understanding of how git and GitHub works the topics you will learn are listed here and in terms of learning resources once again you can use YouTube on YouTube you can refer to Cory safer's playlist or I also have a playlist here and in this playlist I have explain things as if you are a high school student in a very simple language using a practical approach to keep the motivation High I have linked an interview of a mechanical engineer who became deep learning engineer using self- study

mahad is the name of the person and I love his confident and the way he approached his entire journey is really inspirational so I would highly recommend you watch this interview when it comes to soft skills presentation is the most underrated skill I would say for this I would suggest you watch uh this Death by PowerPoint video this video is a gold mine it is giving you very simple and very powerful tips of how do you build effective presentations as an AI Engineers you will be working with stakeholders you will be in a meeting rooms

you will be presenting all the time and if you don't know how to present well there is no use of your technical work because you're not able to sell your work or you're not able to convey your ideas in a language that the business stakeholders understand watching this video and preparing skills for presentation is going to boost your career week 10 and 11 we need to focus on SQL and relational databases as an AI engineer we will need data to train our models and to do variety of operations this data is often stored in a

relational database and SQL is called structured query language it's a language that you use to query data from those databases here you need to learn all these topics and in terms of free learning resources we have an excellent Khan Academy SQL course so you can go through it learn those skills you can also use W3 schools or a platform like SQL bolt which allows you to practice SQL while you're learning it so I really love this platform you should definitely try it out and then on YouTube also there are tons of video my channel have

this particular video which goes through SQL skills uh there are so many other high quality SQL tutorials available on YouTube in case you want to speed up your learning and you want to learn in a very practical approach and also work on an industry project then I have this SQL course okay this SQL course is very highly rated it's very affordable and uh we are not only going through all the SQL technical fundamentals but we are teaching how these SQL projects are executed in the industry so all the stakeholder management skills project management skills are

also covered for assignment uh you need to work on SQL resume project Challenge on our platform Cod basics. we run this free resume project challenges where we share problem statement and data with folks and people work on these projects and not only that they build presentation and they present it on LinkedIn so let me show you so here is the resume project challenge where you see the data said the mockups everything the problem statement so many people participate in this one and the winner for example here is Aran Sharma so if you click on this

LinkedIn post what he did is he built a solution in SQL and then he created a linken post where he explained the solution that he built not only that he attached a video presentation where he was talking as if he's presenting this to business stakeholders now when you are doing this kind of activity you are uh showcasing your verbal your written uh English communication skills to the world let's say if a potential hiring manager watches this video they will get lot of clues about aran's personality his technical as well as his softes the fact here

is that Aran literally got hired in a company as a data analyst just based on this particular resume project challenge so this is really effective it has worked for Aran and many other folks and it can work for you as well next comes numai and pandas and I have attached the playlist and learning resources for it numai and pandas are used for data cleaning data exploration those kind of things so you are spending just one week in learning this basic libraries and later on there will be a time period where you will actually practice the

Eda skills exploratory data analysis skills then comes the heavy module math and statistics for AI math and states is the foundation for AI any AI project so if you're working as an AI engineer you need to have sound fundamentals in math and statistics now math and states is a vast field I have listed down all the topics which are need needed by an AI engineer okay so just focus on all these topics I have also linked the learning resources which includes Khan Academy scores the YouTube channels you know channels such as St quest uh there

is a free YouTube playlist uh and a channel called three blue one brown this person teaches mathematics in a very Visual and very appealing way so just refer to his videos if you are interested in learning things like calculus linear algebra Etc I have also linked my math and statistics course here which covers all the fundamentals it also covers an industry project where we had a database of half a million records and we did hypothesis testing on the launch of a new credit card okay so you can refer to this course if you want to

uh learn using industry Style Project based learning next one is exploratory data analysis you might have heard this term Eda Eda is nothing but you get all the data that you need for your AI project you need to First do some exploration there might be lot of bad values you need to clean those bad values you also need to perform certain data transformation okay so this module covers that the technical skills that you need for this are numai pandas matplot lib Etc which you have learned previously correct but in this particular module what I want

you to do is go to kel.com Kel is a website which is hosting uh data sets and competitions related to Ai and here you will find a lot of useful data sets and also the problem statements so you have to go through some of these problem statements okay and practice you will see solutions from other folks as well but I want you to practice things on your own first and then look at the solution from other people so the exercise here Will be if initially during learning you do Eda using three data sets and then

you work on additional two data sets and perform exploration now comes probably the most important module machine learning here you will be spending week 18 to 21 entire month machine learning is a vast field and this particular segment covers only this statistical machine learning okay so you need to First cover pre-processing techniques and then model building techniques the great news here is that we have a YouTube playlist this is a playlist on my own channel it has received more than 2 million views I have explained the theory in a very intuitive way then there is

code and then there is exercise so go through this playlist first 21 videos only when you get a job as an AI engineer you will be using some kind of project management tool in the industry right now scrum and Canan are the two popular agile project management techniques it will be good to have some understanding of scrum and Canan I have linked excellent free resources for both of it it won't take you much time so please go through them and here is the assignment you need to complete all the exercises in the ml playlist work

on two Kel ml notebooks write two LinkedIn post on whatever you have learned in ml on LinkedIn let's say if you have learned about uh classification you know let's say logistic regression and if you have worked on a small problem statement you can write a nice summary of what you have learned and that will generate some engagement so being active on LinkedIn is going to be a constant requirement in week 22 we will be looking at mlops mlops is similar to devops if you are aware about software engineering in software development there is this role

called Dave Ops where a person will look into uh you know automating some parts of a software development so they will be working on cicd pipelines on Jenkins on automating workflows integrating linters and many other useful tools in GitHub Etc similar to that ml Ops is a field where you are trying to automate some of the things in machine learning project development here you need to learn what is API and then fast API fast API and flask are the two popular Frameworks that people use to write server around a train model once you have train

model you will write this server so that it can serve HTTP request coming from a client fast API is getting popular for which we have once again a free YouTube video which goes through all the fundamentals of fast API and you are creating this You Know sample website and calling fast API from that then comes Docker and kubernetes these two technical tools are used widely in the industry whenever we build any ml solution we usually put them in container and doer is something that helps you with conization and you can also use kubernetes for orchestration

okay uh also make yourself aware about at least one Cloud platform okay AWS or Azure and you don't need to go crazy just uh fundamental understanding of how Cloud Works create a free uh account on either Azure or AWS if you're talking about AWS there is something called Amazon Sage maker that's a platform that allows you to do machine learning on the cloud okay so on the sage maker create a platform try to run some Notebook on sagemaker mlops itself is a vast topic and many companies have a separate mlops engineer role but as an

AI engineer at least you need to have some understanding of mlop so don't go crazy here okay because for details there is mlops engineer it's a separate career role but as an AI engineer sometimes when you are working in a small company where there is no separate mlops role you will have to do some of the mlops all right so just having fundamentals clear is going to be super important now that you have learned essential skills in week 23 24 you will be building some machine learning projects so I have linked two projects one for

regression one for classification both of these are YouTube playlist end to endend projects incl including deployment please go through them in terms of soft skills you need to build an ATS resume don't build resum towards the end you can start building resume right now ATS stands for application tracking system which many companies are using and they will use this system to filter out your resume so make sure your resume is ATS compliant so that it doesn't get filtered automatically by ATS system we have created a video on this topic so please go through that video

and and there is also a checklist that will help you make your resume ATS compliant so just go through all this point check check check and once you have checked all the boxes your resume will indeed be ATS friendly other than resume you need to build a project portfolio website we have linked some resources here so for example I'm going to show you one sample a project portfolio website this website is like your own website where you are writing about your skill what kind of projects you have worked on and you will give a link

to a GitHub or whatever that online tool is where you are showcasing your work and here are some ideas for the assignment the projects that we have done on YouTube maybe you can start using different technology for example instead of flas use fast API okay in classification project uh instead of sport celebrity classification you can use classification of movie stars or maybe your family member pictures that will give your project a unique flavor and it doesn't look like you're just copying a project from YouTube now comes a very hot topic deep learning you'll spend 3

weeks learning about what is neural network the fundamentals of convolutional neural network sequence models such as RNN Etc deep learning is getting very popular it is the biz of J llm chat GPT all the hype that you seeing is using deep learning underneath for learning deep learning there are two playlist I will uh refer you to so the tensor flow is a framework from Google we have this very popular playlist on YouTube once again exercises code Theory everything is covered folks all the learning resources are available for free all you need is a willpower motivation

a computer and a stable internet and then comes end to end deep learning project for potato disease classification in this project we built a mobile app which any farmer can use to take a picture of a potato plant and it will tell you whether the plant has a disease or Not underneath it is using deep learning and convolutional neural network week 28 230 you can either learn NLP or computer vision you don't need to learn both there will be AI Engineers who will be specializing either in computer vision or NLP it's like you become a

general doctor and then you become lung doctor or heart doctor you don't need to become both in terms of NLP these are the topics that you can learn there is once again a YouTube playlist that you can use to learn theory practice coding and also work on exercises the last two weeks of this entire 8 month long journey will go in learning llm and Lang chain these are the buzzword and and Lang chain is a framework that is getting very popular and if you look at any machine learning engineer positions nowadays majority of them require

you to have some exposure to Lang chain framework so for this also I have a playlist where we have covered all the Lang chain fundamentals and we have built three projects three llm projects which you can use to learn as well as you can put those projects on your resume obviously with some customizations remember that in this 8 months you have learned all the fundamental skills but that doesn't mean you have become an expert AI engineer the learning for AI is continuous so many things are happening every day therefore from week 33 onwards you'll be

working on more and more projects you'll be working on building online credibility through Linkedin Kel uh and then you'll be applying into jobs and if you have prepared with sincerity you'll definitely get a job because there is a huge boom and there is lot of demand for people who know AI well now I want to share tips for Effective learning as well because there is lot of things that you have to learn and you want to make sure that you spend less time and learn effectively there are some rules for Effective learning for example you

spend less time in consuming tutorials you spend more time in digesting implementing and sharing nowadays people do reverse they spend more time in watching videos and for digestion they spend less time it should be other way around if you're spending 1 hour in studies maybe 20 minutes or 30 minutes you spend in uh watching the tutorials and remaining time you spend in digesting then you implement you write some code and you share it with your friends group learning is very important when it comes to sharing in our Discord uh server you will see partner and

group finder Channel where people say Okay I want to learn data science uh who wants to partner with me and this way people make groups and then they have weekly Zoom calls where they check progress of each other you know it's like a going to gym with bunch of friends if you go alone you will get bored but if you go in group you will stay motivated that's it folks I wish you all the best once again check video description for the PDF the entire PDF is included here all the learning resources are free I

wish you all the best if you have any question Post in the comment box below if you like this video please share it with your friends we are putting a lot of hard work in making this video videos so if you can share it with your friends or if you like it is going to help us a lot thanks for [Music] watching