Roadmap to Learn Data Science & Industry Ready Projects In 2024 With Free Videos And Materials

hello all my name is krishak and welcome to my YouTube channel so guys in this video we going to see the perfect road map to learn data science in 2024 at the end of every year probably I upload this kind of video so that your learning are always updated with respect to data science and similar kind of videos also I upload with respect to data analyst big data and many more so in the next year uh for in January I will also be coming up with a road map to become a data analyst in 2024 okay but again going forward uh understand this specific road map is quite amazing the reason is that I've been uploading videos from past 5 years I've been teaching from past 7 to 8 years I've seen amazing career transition I've seen so many different different tools that are probably coming up in the market I've seen what kind of uh skill sets are specifically required in interviews what they asking I've done lot of podcast with respect to transition stor and many more things so considering all those things I've created this amazing road map and this road map has all the handwritten notes it has all the projects it has all the videos in videos format everything you'll be able to access it and trust me the videos that I am probably going to provide you and that is uploaded in the form of playlist has helped people to successfully crack jobs with respect to data science so uh definitely this is my overall effort of the past 4 to 5 years and this year in 2023 I was quite interested in creating a lot of end to end projects with mlops and generative AI is one of the thing now if you go ahead and see my playlist I've created around 10 to 15 projects on generative AI using Lang chain using open AI using U Google gmany and many more and that in 2024 I'm going to continue that I'm going to focus on two different things one is generative Ai and one is mlops right so let's go ahead and without waste of any time let's go ahead and see this I will keep the like Target of this particular video to 2,000 please make sure that you quickly do that hit like put some kind of comments and share with all your friends because all this entire road map has all the free content that you specifically require everything is available over here okay so let's go ahead and let's see the road map so first thing work of a data scientist as you all know the life cycle of a data science project has been almost same from past 4 to 5 years but as we go ahead with respect to step by step there are some amazing tools that have actually come you know I'll be talking about all those tools it's a very big road map Al together see the reason it has become big because I've given multiple links multiple videos types multiple documentation type if you're not able to understand from documentation I've given you videos so if you probably scroll there are around so many different different projects like this projects will be sufficient I've created more than 50 plus project but I've selected somewhere around 10 projects which you can probably use it and do any kind of projects right and there in that specific project I've added mlops tools I've added multiple things trust me guys in no other YouTube channel you will be able to find it I'll give you that guarantee that at least this many number of projects NN projects with deployments will not be available okay so uh to go ahead with uh you know we'll first of all understand initially when we have a data science project we go to the next step which is called as requirement gathering in requirement Gathering domain experts and product owner along with business analyst they discuss a lot of thing and they create a specific uh you know they they create a lot of stories and at each iteration or at each Sprint how many stories needs to be uh completed based on that they'll be deciding the program manager will be deciding the team size then all this requirement will be sent to the data analyst or data science team then again the data science or data analyst team will be discussing with the product owner because we need to understand what does the data scientist do as usual along with this product owner and expertise they have a lot of discussion and then they try to find out for this specific use case where they have to probably take the data from so they will be dependent on internal databases they'll be dependent on thirdparty cloud apis they may be dependent on some third party paid apis itself right for the data itself and once they identified then by creating Pipeline with the help of Big Data engineering team all this data is efficiently stored in a specific databases it can be mongod DB it can be different different databases it can be Hado database it can be it it depends on the use case and scenarios that you're specifically using now once these big data Engineers they have created that pipeline at the end of the day all those data will be now sent to the data science team and that is where the life cycle of a data science project begins right the first step is feature engineering second step is feature selection third step is model creation hyper parameter tuning the fourth step is model deployment and here a lot of ml is used right and that is the reason why I'm telling you mlops mlops this year next year probably see because of open AI right because of this llm models now the most important thing is that how you can create an project efficiently with the help of mlops tools right so here dockerization cicd pipeline all those Concepts and then we finally do the deployment and finally at the end of the day we also do model monitoring right and we also look for retraining opportunities now in feature engineering if you want to more know more about it we specifically do explor data analysis handling missing values handling outliers categorical encoding normalization standardization correlation forward elimination backward elimination uni variate selection random Forest importance and all and all are there right see guys if you go probably go ahead right this road map looks quite big but understand I've created multiple playlist both in English and Hindi language right so if you interested in learning in Hindi you can go ahead with you can if you're interested in learning in English you can go ahead there still many videos that I really need to upload in Hindi also so that will be my Target also in 2024 okay so first thing first what is the prerequisite that is probably required or what is the first skill set that is actually required to learn data science one is programming language and again I would always suggest from past three years I'm suggesting go ahead with Python programming language because Python programming language is improving extensively extensively means there are so many libraries there's so many things that are coming up any companies that are even coming up with the llm models or any feature first of all they make sure that it is compatible to python because the community is huge many companies are using it many companies are supporting for this specific development and python is very easy to use okay so uh again in this time when Char GP is there when videos formats are there so many things are there I've already created a detailed playlist both in English and Hindi you can probably see over here right so this is basically in English and this is in Hindi right I've created a detail playlist you can definitely follow this and you can learn python within 1 month why I'm saying one month if you are devoting 2 to 3 months every day sorry 2 to three hours every day then trust me it will be very much easy and again to see more and more examples you have to use Chad GPT okay try to use chat GPT or Google B try to ask more different examples over there many people say that Krish we don't know like what kind of examples will be coming up how to practice though go and ask CH GPD they'll give you hundreds of examples now your learning process has become very simple right all you need to be is becoming smart and practicing more and more with the right kind of questions over there right so with respect to this python I've actually created three playlist uh one is python playlist in English Hindi and to support this I've also created a flask framework playlist okay what is the final goal of outcome with respect to python here you can see basic to intermediate python with various knowledge of various data structures like numai pandas mat plot Lim and many more knowledge of Performing EDF feature engineering and creating visualization charts using python at least make some python Pro projects using Frameworks such as flas deployment when I say end to end python project I'm talking about deployments I'm talking about this so that this becomes very much easy when you go to the next step again at the end of the day you want to become a data scientist right so that is the reason why I'm telling you this okay then the next thing is statistics statistics as usual is quite amazing okay statistics is the most important thing in data science whether you're working in machine learning whether probably you're working in LP anything where you work in right statistics can play a very important role and for this also I've created some amazing sessions there are three amazing playlist even in English Hindi everything is there right there are around 43 videos in English there are 20 to 22 videos in Hindi and still I need to complete more this more videos I'll try to upload as we go ahead but this is the fundamental thing that is basically requ required statistic because of Statistics you'll be able to understand how you can use this amazing tool see maths machine learning is what machine learning actually provides you stats tools to analyze the data to visualize the data to do future prediction to probably create model and many more things so statistics can be very much amazing see and all these are created with amazing links all the materials will be available and just imagine you just need to learn right and I'll give you a technique like what you should definitely do with respect to learning so here you can probably see English video live session of Statistics I've created 7 Days live session which completes the entire statistics you can learn in this way and Hindi also I've created around 20 videos that also you can probably find out and everything is present over here you can follow any one of them according to your comfortability right first we started with python then probably complete statistics then once you do that learn about feature engineering right feature engineering and this is for all the people who wants to learn from basic Okay who wants to learn from basic it's not like uh I'm telling you that you always need to start it from here if you know all these things and I think people who are following me in my YouTube channel they should be knowing at least this much because this is what I've been uploading from past 3 to 4 years right this year I focus more on end to- endend project right so here is your feature engineering both in uh live playlist and complete detailed Eda so you can also watch this the final outcome will be that techniques to perform statistical analysis more I'll be talking about internship many more things jobs everything I'll be talking about as we go ahead then uh coming to the next one is about databases in databases I usually say focus on one SQL and one no SQL databases for no SQL I've selected mongodb you can also use cassendra you can also use other mongod DBS all these no SQL databases will now play a very important role because now in generative AI there is something called as Vector embedding and most of the time no SQL databases is used and all those vectors vectors basically means what whenever text is basically converted into when the word is converted into some numerical format right so that the machine learning algorithms will be able to understand it right so that is the reason my again one Focus will be on no SQL databases and again I've created a playlist on this my SQL databases and plan is that that in the future I will try to create the cassendra database which is an apas candra the documentation link is also given over here so everything I will try to upload this so please make sure that guys you for this report repository start this particular repository so that it'll be handy for you okay then coming to the next one machine learning as usual guys there is a there is a thing right there's a some questions now generative AI is coming up can we learn generative AI without machine learning or deep learning the answer is yes you can you can directly go and job okay no worries but it is always good if you have your fundamental strong and that fundamentals why I love about data science from 2014 I'm working on it you can just imagine the kind of fundamental base that I have actually built if you go ahead and see my every video where I've used mathematical intuition where I've taught multiple things my fundamental base is very much important over there right the concept is very good so that even though if I even now also if I probably go ahead and give any interview without any preparation I will be definitely able to answer things because my fundamentals are strong so if you also want to make your fundamentals strong right right I would always suggest start with machine learning the best way again telling you guys you can start with this live ml playlist right so here in live ml playlist in 6 to 7 days I've completed almost all the algorithms you can go ahead and see it and this is with practical implementation okay this is with practical implementation so that will be quite amazing then coming to the next one deep learning playlist see any of this you can probably select it is upon your thing if you want to go slow go ahead with this longer playlist if you don't to go fast want to prepare quickly then if you have lot of time then probably uh use this second one if you have less time go ahead with live ml playlist you can see two two hours videos go ahead with that not a problem if you want to learn in Hindi Hindi is also there all the algorithms are specifically uploaded after you complete machine learning then we come to a subset of machine learning which is called as deep learning now guys uh many people talk about deep learning right deep learning the ma thing Isn CNN RNN the variation of RNN the variation of CNN object detection and many more things right so for this also we have created this specific playlist okay so there is a five days live playlist there's Complete deep learning playlist and also there is a deep learning playlist in Hindi so as I said my main aim is to provide you content in a way that you don't have any language barrier problem you don't have any content problem itself right that is what is my aim my main aim is to democratize this entire AI education right so that you'll be able to learn in an amazing way that is what I specifically want so here you can probably see this three playlist you can start with and I have probably completed almost almost everything NLP I've completed deep learning I've completed everything along with materials along with free guides along with tutorials along with videos everything trust me everything is over here and I want this repository to go into multi multiple places so that people also watch this because at the end of the day they get to know about things and all the playlist is structured in a vet manner right now once you complete deep learning again in deep learning also you need to focus a lot guys you need to uh understand how tens flow Works how py torch works you need to probably understand how things uh with respect to learning I'm telling you right and nowadays since generative AI llms right so focus more on the NLP part if you're focusing more on large image models then focus on computer vision part so that is how you can probably categorize things okay then coming to the NLP playlist so here you have English live NLP playlist and in complete NLP playlist okay so this is again there and you can also go ahead and walk and this all I did it in last year so that it is very much handy and available to it and right now also it has a lot of views people are using it and many more things okay now once you complete all these things guys at the end of the day you really need to create a lot of projects when I say projects it's just not like Capstone project project that Capstone project that jupyter notebook project uh not that project the project is something that you should develop completely end to end you should use one repository where you are committing the code you should talk about uh um mlops techniques you should talk about GitHub actions you should talk about multiple things you should talk about modular coding you should talk about logging you should talk about databases many more things as such so for this also it is good that you know some of the important Frameworks one is the flask detailed playlist that I already created and then one is flask onot video gradio Bento ml ml flow and dhub I will talk more about this particular Frameworks but this is specifically required for production deployment if I talk about DVC all these things right so it is good that you know or you have some idea about this kind of Frameworks okay so this Frameworks is pretty much important still we have lot many things now this is the most important thing guys this is the most important still say this is the most most most important thing that is mlops machine learning operations that is with respect to design model development and operation as I said guys what is going to happen in the future now if you probably see a lot of llm models arei models these models are having huge accuracy because those bigger companies which have bigger bigger gpus bigger bigger data sets they are able to train models with so much accuracy even in hugging face if you go ahead and see with respect to every machine machine learning deep learning object detection any model they already have some amazing pre-trained model and over there you can just go ahead and find tune and you can use their API but understand accuracy part of the model is already solved right it is been solved and it is being solved by these bigger companies already and again for a startup to probably do that rework it'll take time because at the end of the day this was the problem that was happening a startup AI startup if you see previously that were coming they used to take a lot of time to develop their product but but this year as soon as generative AI became very much popular you could see that there was so many products so many startups that had actually started AI startups itself right yeah mid Journey so many different things at the end of the day they using some of the other models from these amazing Giants right so what is the most important thing after that integrating with their platform right and that is where mlops or devops will come into picture so for this I have created a lot of videos guys for some of the things I have not created it but again in first of all I would suggest always focus on GitHub cicd pipelines GitHub actions then you have Circle CI you have Cube flow you have ml flow ml flow I've already developed a video deployment techniques in AWS a Dockers and kubernetes I've done this in my Project Playlist which I will show you just down then there is something called as evidently AI so if you probably go and see evidently AI this is another amazing open source ml Observatory platform where you'll be able to see how your model is performing and and how you can basically do so I've also created a YouTube video then you have grafana monitoring you have airflow you have bentto ml you have Sage maker I've created a detailed playlist and projects on sagemaker you have DVC you have Dockers many more things so the reason why I put this many things it is not necessary that you have to learn each and everything but at least learn some of the handy machine learning Frameworks you know the complete machine learning life cycle of the project which can be handled by ml flow or um if you have B to ml something like that right so you have to learn all these things whichever you find it easy whichever is required in the industry you can go ahead with this but the best thing is that most of the Frameworks have actually covered videos is also developed and you'll be able to see where I have not given video no that kind of tutorials has also been uploaded in the YouTube channel right in the in some of the projects so here you can probably see end to endend mldl projects with ML offs deployment and open source tool so here is the two playlist that I really wanted to show it to you if you have never developed a project how you have to probably do the modular code how you have to probably do the logging how you have to go ahead with doing each and every steps what is the process of creating a project this we have created and many people have shared it many people have put it in their resume and trust me when you have this kind of projects explaining the interview becomes very very much easy right as I said that I've uploaded more than 50 plus end to end project videos but out of them I have selected this 10 okay so here you can see first end to end ml project for starter student Prof prediction end to end NLP project end to end machine learning project using awsa computer vision and to end cell segmentation deep learning project with deployment mlops DVC end to end ml flow projects projects with ML flow end to end ml project implementation Dockers GitHub action Lang chain open AI project kidney classification project Lang chain open so over here you'll be able to see I've uploaded every kind of project Let It Be NLP let it be deep learning Let It Be machine learning trust me guys I don't know you will never be able to get this much along with video explanation along with materials everything the reason is that everyone I I I my aim is again to democratize AI education I want everyone to learn AI not to just get job right my main name is not to get job understand the importance of AI try to use it in your day-to-day activities right so all those things you can specifically do right then uh once you probably complete this specific project one by one project you can do yes if you know all all those things that you have learned earlier this projects becomes very very much easy then coming to the detailed generative Ai and llm playlist so here you can see openi playlist English langin playlist Google gmany Playlist I've also uploaded this and if you want to specifically do any open source contribution I've already created a dedicated video and created one repository which has 4.7k star so here you can probably see in ml projects there are lot of projects that are probably coming over here you can also go ahead and contribute it so that many people will be able to see it right or use it because and as I've told you can also do your branding over here you can put your profile link and all whatever things you specific you want to do okay that you can actually do now this is the most important thing use of chat GPT or Google B extensively now guys whenever I you may be thinking that how Chris you are able to upload daily videos see the main thing is like let's say with respect to generative AI recently I was checking with respect to gini I was able to see Gemini Pro right API I was able to see do it in jupyter Notebook very much quickly okay because those documentation link was already provided but again at the end of the day to convert that as an end to end project it becomes very much difficult because you need to create a front end you need to make sure you can have to use some Frameworks like stream late flask anything else that what I did I simply go went ahead and asked chat GPT hey provide me a template where I am going to use the stream late probably I want a front end with one button one submit button one upload Button as soon as I click the submit it should hit my G API so that entire template was specifically created by chat GPT and it was available to me right so that is the most amazing thing right so at the end of the day this is the future right here you are saving time you're becoming much more productive when you are probably using a coding this right it becomes very much easy because initially which was taking 5 years now it is just I mean initially let's say a work is taking 5 hours now it is probably taking 1 hour why because of chart GPD you don't have to probably go and do much Google give the right context get the right answer try to use it try to debug it and try to solve it right so this is the most important thing and this will be the most important thing that will stand out with the current data scientist and with the previous data scientist if they're using this right it is quite amazing you will definitely be productive and I don't have to create a tutorial how you can use chat gity that is by your side itself right you can actually do it see now at the end of the day you may be thinking chish you have given such a big road map for the people who are starting right now how we should go ahead see for the people who are starting right now you can go ahead with this thing only not a problem see it may take six to 7even months right but the most important will be practice like there if there is a full stack developer he wants he or she wants to work with generative AI he can directly jump with generative AI that is there okay but my major aim is to learn in such a way that your Basics is also strong your fundamentals is also strong and it is always good to build knowledge slowly when you start in the right manner I would not suggest that always learn after Ed directly down jump to deep learning I don't want that right by that specifically you want to be able to understand right because if your fundamental is strong guys tomorrow you work anywhere any new technology any new things come you will be able to grasp it very much quickly right take my example right anything when new comes I just take a couple of hours I read about it I practice something and I'm able to create a video about it I'm able to teach you right the same thing will happen to you when your basics andun fundamental are very very much strong at the end of the day after learning this much guys for a freshers I would always suggest for the people who are having career gaps I would always suggest two internships right while learning try to find out internships because for a fresher many people would say that hey fresher do not have jobs in data science right see data science jobs are something that companies look with respect to experience right the kind of work that you specifically do in a data science project is very much crucial it can create a lot of loss in the companies if it is not done in a proper way right so internships can actually help you to gain that specific experience even though you have a career Gap I had so many students who were doing government exam they were they they they spent four to 5 years you know they have four to five years of career Gap because they were preparing for government exam but just because of internships they again able to come back to the jobs and internships trust me guys is easy to get when compared to a full-time job for freshers if you have at least 6 months experience then it is easy for you to get into the industry but without experience it becomes very much difficult right so that is the reason why I would always suggest go ahead and apply with internships if you keep on applying in internships you are going to get the opportunity I've seen with respect to full-time jobs for a fresher and if I compare it with internships they able to get internship very much quickly and there are a lot of messages that I've already put up in my LinkedIn for experienced PE person who who are working in different technology they can actually make a transition over here right for them whatever work they have done over there just see how they can apply data science over there and create a proof of concept project and by that way they will be able to put those things in the in their resume I'm not telling you to write anything as a lie over there whatever things you have learned and how you have actually implemented your previous project have you applied any data science concept over there if you're not able to apply somewh the other problem will be there at least somewhere right try to see if there is able if you're able to find it out and then probably try to convert into a PC project and then try to put that in your resume and explain the same thing in front of the interviewer right you have a genuine work right so once you probably do the internship internship is important again Inon provides you internship right so there is an internship platform many many people there are more than 500 projects over here you can sign in it it provides you the entire dashboard it provides you everything as such what you have to do is that just go go ahead and probably enroll for the internship complete the project submit the projects because as soon as you do the internship also you get an offer letter and as soon as you complete it submit it you'll get that many number of months uh experience let's say if you're taking six months to complete a project whatever project is mentioned over here then that 6 months experience you will be able to get as an internship certificate okay so internship is super important and here I have also created a data s tracker sheet which you can use all the other things you will be able to see in all this channels so guys this was it from my side I hope you like this particular video but at the end of the day guys continuous learning is a very important in the field of data science the more you learn the more you become better so I'd always suggest have a always a mindset of learning more and more seeing new things because that will actually help you to grow in the industry so yes this was it for my side I'll see you in the next video have a great de thank you and all take care bye-bye

Channel: Krish Naik

Views: 178,579

Keywords: yt:cc=on, data science roadmap 2024, generative ai roadmap 2024, machine learning roadmap, deep learning roadmap, how to become, how to get data science jobs

Id: N7RU6W4hAMI

Length: 27min 54sec (1674 seconds)

Published: Fri Dec 29 2023