Don't be misleaded by such people, machine learning is still a thing that is worth learning in 2025. If you are making ML models for specific tasks or even doing DL, you would need to know ML. Or even if you are training ready made models to make something, or if you want to fine tune it, you would need to have knowledge of ML. There definitely are many options in AI. But ML is still worth learning.
@DarshTayal-p9b "I am planning to get a job at NLP".. aise sirf job mindset rakhoge to inn fields me nahi milega job.. ML and related fields are more passion/knowledge and research oriented compared to other fields. You have to be truely passionate about algorithms, about the techniques and especially about the subject. You need to read lots of research papers, read about what is being used in NLP fields right now and how engineers are solving the present challenges etc then after learningthe basics you'll have to build projects and contribute to open source projects (Currently since 6 months I am not into NLP so I cannot directly tell you what to do for sure but do your own research and you'll be good).. But whatever, the bottom line stays same, you have to be truely passionate about the subject and patient enough till you get an offer. NLP or ML/DL fields are not like your average IT job. Do learn, do contribute, be passionate and you'll do good. All the best!
Thanks for your insight. ML is still a thing, and will remain so for foreseeable future. And I do state it in this video as well. The target audience for this video are not seasoned players in ML. But those who have spent money, time and effort, taking up courses on Data Science, hoping to find a well paying entry level job, only to know later otherwise. This video is only to ease out their struggle in landing their first job.
@TowardsAGI I appreciate you responding back to my comment! But what I understand from your video that you have targetted for audience that are trying to get a job in AI field easily (relatively). I do agree Gen AI job is more easier to get than a traditional ML/DS job due to complexity of ML/DS, and for Gen AI you don't really need much knowledge about complex topics unlike ML/DS. But I believe you may have made the video title and thumbnail a little extreme and a little oversimplified your argument. ML/DS is indeed a long journey, but arguably even for Gen AI you would need to know programming, and math level for a job level is not that complex, mostly high school maths. But yes, you would need to spend time and effort in learning algorithms and libraries, that's the main part. But even for making Gen AI tools you would have to know prompt engineering, programming, API development and stuff. It is relatively easier and your argument here is correct, and I think for entry level jobs, basic knowledge will be good, but I think as you advance or if you are making more complex tools, even tho you directly arent using ML algorithms but it's still a good thing to know, sometimes you may have to fine tune or train on more data. I may be a little wrong here, but still, I don't think most Gen AI tools in the real world work without fine tuning and a good system prompt. And arguably unlike ML where you have to have a good foundation of maths, I think to make a good prompt you would have to have a good foundation of linguistic skills. And I think a lot of people are still making efforts to learn ML and still getting a job. I think, even tho Gen AI may be relatively easier but still efforts and time is needed.
It's true, you'll be a better Gen AI expert if you understand ML. But it's not mandatory skill. This video doesn't talk about skipping ML, but only talk about how freshers can get into AI faster. Learn GenAI first, and then add ML skills later.
machine learning is the stepping stone, more like the foundation to everything else. learning machine learning first, and then other subsets of AI, clears your basics and makes you stronger in this field. stop misleading people by giving curious titles to videos. i didn't watch the video and i won't either. v v wrong title. if you are just another sheep wanting to land a job, go ahead w this person's advice. all the passionate AI enthusiasts who genuinely are trying to contribute to the community will not at all agree with the title of this video. disappointed!
First of all, I am happy that we have passionate AI enthusiasts like you. But you got riled up for nothing. This video is not about dishing it out Machine Learning. Instead this is for those who have taken courses, spent money and time, hoping to find a well paying entry level job as a data scientist easily, only to find the grass is not as green as it was made out to be. However, I do disagree calling those who just want to land a job as another sheep. Being able to follow own passion is also often a luxury not many can afford, and the only option they have is 'land a job'. This video is for them.
Your suggestion will work, especially for entry level. In my experience, surviving on gen AI alone for mid to senior role is not possible, for example, people making carrer transition mid-career. This is because for senior level roles, they are looking for "full stack data scientist", as you mentioned in the beginning.
Having been a full stack data scientist and having experience of 8 years in data science (I am also Master of data science from top tier university), I agree partially with this lecture. There is indeed saturation at entry level. However the very second reason he offers ["The subject is very complex and requires learning programming language, statistics, Cloud knowledge, deep learning, AI, MLOPs, deployment"], itself is the reason why the initial tough competition and the crowd of curious folks will disappear. So, those who persevere will succeed for sure. I FULLY AGREE WITH HIS STATEMENTS ABOUT FUTILITY OF 1 MONTH /3 MONTH/6 MONTH COURSE. MINIMUM 1 YEAR (180 TO 220 HOURS) FOR A GRADUATE PERSON WITH NICE MATH AND ENGLISH BACKGROUND. I however do not agree with advice of jumping directly to generative AI. GENERATIVE AI IS A MUST HAVE SKILL, BUT TO MAKE FULL USE OF IT (IN MACHINE LEARNING DOMAIN) YOU MUST HAVE FUNDAMENTALS OF MACHINE LEARNING CLEAR)
When I say genai expert, I mean API implementation rather than model development. Just so that the freshers can be at least start competing for those roles. I did advice them to learn code ML and DL once they have done a decent number of geani project.
I appreciate your content sir as it's definitely very helpful, can you suggest the prerequisites for learning GenAI for an absolute beginner who doens't want to invest 2 years on data science but interested in AI..
I'm in field of IT under operations and my focus and commitment towards learning data science is nowhere due to large amounts of resources and a lot of bootcamps provided by Ed tech companies and RUclips educators. As mentioned kick starting a career in Gen AI is a good choice of career transition?
If you intend to transition to a career in AI, following the GenAI path will be easier. When I say easy, I mean relatively easier than DS option. But I think it's obvious that it will sill require hard work, focus and intertest. Bes of luck!
Generative AI is an exciting and rapidly developing field, transitioning directly into it without solid foundational knowledge in Data Science or ML may not be the most effective approach. It's essential to have a well-rounded understanding of the core AI concepts before diving into Gen AI. With the right approach, freshers or professionals in IT can start building a career in AI, whether through Data Science or a combination of Gen AI and operations, but it requires patience, focus, and structured learning.
While prompt engineering is a valuable skill, it's not a replacement for deep AI knowledge. Many real-world scenarios demand custom solutions beyond simple prompts to OpenAI. Factors like data privacy, accuracy requirements, and client preferences often necessitate building your own small language models (SLMs). This requires a solid understanding of machine learning, deep learning, and transformer models, which can take years to acquire. In our own work, we've encountered situations where relying solely on OpenAI wasn't feasible due to client constraints and accuracy concerns. Therefore, we chose to develop our own SLMs. The idea that you can bypass core machine learning concepts is simply wrong.
All this youtuber are like - don't learn machine learning in 2025 , don't learn web dev , don't learn app dev , don't learn digital marketing don't respect your parent All you should do just make content and tell others what not to do
Making content, giving out an advice that you believe in, is better than just seeing thousands regret their career choice. At the end, it is still their choice. My advice is not binding on anyone.
He is right about the Full Stack Machine Learning role. There seem to be no entry roles in ML and companies globally want someone with 5-8 years of experience. I used to think the ML engineers will work with Data Scientists and Data Analysts with cleaning data and processing the data to develop models and that they only need to focus on learning Machine Learning. But where I work they are asking us to first start with Data Analysis, then learn Data Science, Gen AI and finally move to Machine Learning. So they are training us for 1 year on this and I have completed the Data Analysis so far, it helped me with Python, SQL, R and the Python libraries like Numpy and Matplotlib. It is helping us understand how everything works in Machine learning at the end. On the other hand Gen AI seems to be easy role where a non-tech can easliy grasp the concepts and implement projects since it is interesting. Thank you for the insightful video.
Yes, I have learn Data Science and trying for the entry-level jobs from 2 years but not able to find, Later the insights from the HR's from the company and software engineers who are working, is the roles related to machine learning and data science required min of 3-4 years of experience. If you are beginner it is very difficult to find a job related to data science
sir nowdays everyone says no job in ai engineer for fresher who has limited skills in ml stats dl only difficult n interview also they ask core questions focusing on genai is not good having knowledge is plus fresher what is ur opinion
@@HDSV10 Companies want everything from one person. They ask 100 things during interview and not use even 10 out of them during job. As a fresher, you can't just rely on answering questions in an interview. Build a compelling portfolio of genai projects. If you can showcase your work, interview takes a back seat.
Hello Satish ! Adarsh here.....I am working in Gen AI Model Validation right now in Banking industry. Although Im new to Data science but have good grasp of ML, DL and GenAI concepts, I want to understand, what are the potential jobs I should be targeting later on to grow fast in terms of compensation and exposure especially focussing on GenAI ?? Thanks in advance 😊
@@TowardsAGIhello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for lucrative package or if someone is interested in it?? As I watched some RUclips videos in which they are saying that web3 and blockchain are dead and it was all hype??
Shall we take this recommendation as learn to drive the surf board but skip swimming classes, wind direction prediction, waves formation? This is almost like saying skip any course that says it will teach you something in 3 months. Instead of 3 months, he says 6 months. Now will that not keep you interested? GenAI may be useful. But focusing on that predominantly isn't enough in my opinion. That may be like learning to drive the water surf board. Would someone allow you to go to sea with that knowledge alone? I doubt it. They would expect you to know swimming definitely. understanding wind directions, wave formations, what type of board to be used when and so on.
I appreciate the effort in putting down your thought. However, it seems my definition of GenAI expert is different than what you have assumed. I am only taking about somebody who can build geani solutions using API implementation, not model development. I don't think core ML, DL skills are must for it. I know startup founders who have build complete suite of genai product without even a single data scientist in their team. With only software developers. I said skip any 'data science' course that says 3 months, not just any course. There are in fact a lot of things you can learn in 3 months. A course on how to make jalebis will definitely take less than 3 months. Not data science. Also, I am not saying 6 months instead of 3 months, because 6 months is not for data science, but an alternate relatively easier skill of genai.
@@TowardsAGI Got it. I was wrong and sorry about that. Still, I'm concerned about one thing. Any skill that's easy to learn can easily be replaced by AIs in very near future. So not sure if this is this right to choose.
I completely agree with your point my friend you have really made a point here with ease looking forward for more of these cutting edge technology videos!
i sort of agree how you put up this issue like this and i would love to see another video of you where do describe more on how to land on my first gen ai job and what projects to do and how to sell myself gen ai Expert.
I'm coming a full circle from a critic to someone who's seeking help. (No shame in admitting mistake). Please ignore my previous comments and help me further 😊 Help me understand more about GenAI. It sounds as if the work of a GenAI expert is just to use an existing AI model's API and build a tool needed for the respective company around it. It feels like same as user of chatgtp. Except, a user is using the front end interface of the API and a GenAI expert is directly using the API programmatically. Is that all the difference? If that's the case, I don't see there's anything to learn about GenAI for someone who understand backend development. Is there anything more to that? I mean like, does a GenAI expert train / fine-tune the models using his own dataset? If so.. does this involve skills like curating and annotating datasets or understanding AI models?
Data Science is not an entry level position. Usually you gain some experience from other data roles like data analyst or business analyst or have Masters degree and transition into Data Science. Data Science requires a good practical knowledge of statistics and not just ML algorithms. Now-a-days you will also be doing a bit of data engineering sort of task like bringing a specific type of data for analysis or Model building through a pipeline
Thanks you!. A roadmap of the skills required for GenAI expert is already there on my channel. A video on 6 month roadmap to learn those skills is in the works.
This is a truly practical video reflecting the current global scenario. As mentioned in the video, could you share insights on how to land a job in Generative AI?
Hey, I need a suggestion. Gen-ai is used for 'Product making" by most companies or startups. But what if I want to get into fraud detection, biotech or fintech using ML and DL. Basically away from gen-ai. Is this a good idea for fresher? I mean do companies hire fresher for such roles? Or Gen-ai is the only path to get into industry?
See, since genai itself is new, companies at times will look over experience if you can showcase some good personal projects in your portfolio. Traditional ML is great, but you will be competing against a lot more aspirants for limited job opportunities. Companies also tend to prefer experience, often even asking for Masters or PHD in the field.
Getting any job is tough. What this video talks about is that it's 'relatively' easier to get into GenAI than ML, considering the time, effort and the available opportunities.
I am sorry that this video makes you feel this way. Instead, take it an insight for the future. Learn the Data Science, but also keep focus on the genai. At the end you will have both skills which will make you even more valuable.
Thanks sir for your forward thinking strategy on how to get into AI field. Please make that video on how to go about becoming an generative ai expert and how one can market as such
Randomly bumped into your video. Thanks, man, for the great advice. I am a senior engineer with solid dev experience around Microsoft from dotnet to dotnetcore ,azure, API's dev , devOps architecting and integrating stuff from Microsoft eco system to other worlds . It's absurd when I see the hype of GenAI . I remember a recruiter lady told me over the phone don't go for master's in data sciences, as she receives 150+ resumes of people having specialized master's degrees and there are handful jobs available. When I see the learning graphs being shared, I seriously want to vomit, this is not reality, the paths shown in graphs in Data Scientist makes me laugh. you probably gave the best advice. Will stick to it.
Hey, thanks! I was so confused about data science vs. Gen AI - three weeks of agonizing! I finally picked AI, but I'm still wondering if it's right. Your video was a huge relief; I feel much better about my choice now.
I am data analyst with 6 months intern + 6 months of full time and i always wanted to be ai ml guy i have baisc knowledge of ml algorithms now wanted to move to ai space so should I target more data scientist roles but whenever I see the role for ML/AI roles they wanted experience of 3+ year so should I try in gen ai space or should I continue to try in Data Science Jobs
It's a tough call, but I would recommend focusing on genai and ML equally (since you have an interest in ML). The entry barrier for geani ai is lower than data science. But it will still be tough as expected.
If you are really passionate about core ML, try harder. I can understand it can get overwhelming at time, specially with a full time job. Else, you can try going the GenAI path. Build a good portfolio.
I'll take back all my comments and conclude that his intentions are that if you're passionate about the AI / ML overall, take the long path of 2+ tireless years which is still going to be much more valuable in the long run. But if you believe that path would be a struggle for you, take an easier path of becoming GenAI expert and then go on to learn other skills slowly. I believe the intentions are honest but not understood in the first go itself.
Thank you so much! This helps me to put my efforts into something that gives back results or appreciation sooner in this market and also accepting the trend. 🙌🙌
@@TowardsAGIhello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for lucrative package or if someone is interested in it?? As I watched some RUclips videos in which they are saying that web3 and blockchain are dead and it was all hype??
Im working as VB NET and Sql developer for 7 years, i need a transition, so i plan to learn in demand skill and land a job(remote). which will be smoother for me? Gen AI expert or Data Engineer With Aws/Azure.
Both are good options, it depends on your interests and learning preferences. Data Engineering is a good option if your prefer less coding and more interaction with data. GenAI expert otherwise.
correct sir, very big and vast subject for data science and very interesting concepts when i learn . i invested 2 years from 2022- 24, after i leave my job i done some many projects on deep learning and machine learning , but still i am not getting interview call also and sure i will get data scientist job in this year
This video is a test to our learning. He says don't trust someone who says learn something in 3 months instead of a tiring 2 years. He ends up saying learn something in 6 months. Connect the dots which is what he wants us to do. If you aren't able to spend a tiring 2+ years into learning in 2025, and instead focus on learning something in 6 months, you are not job ready or you should be extremely lucky.
Every skill has it's own requirements. So, I am not sure why you think it's okay when I say data science in 3 months is scam, but it's not okay when I say genai expert in 6 month is feasible. I think of it on the lines of MVP, minimum viable product. You ship out your MVP first and then iterate on it for full functionality. Same way, genai expert is the MVS, minimum viable skill to be able to start competing in the job market as a fresher. And then you iterate on it and add ML/DL skills down the line.
@@TowardsAGI That's because I immediately explored various JD for GenAI experts and many have the other skills that you suggest to be skipped as a fresher to be important skills to have. I understand you the JD would always say but you can still be selected without it. But when I compete with someone who isn't at an MVP state and are knowledgeable in other stuff, then I'm gonna miss. I am agreeing with you in 1 point though. If we aren't willing to invest even 2+ years of tireless knowledge seeking, then we will get carried away in this era where machines can do most of the low level jobs. It's going to be survival of the fittest as always. But even tougher in the AI era.
hello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for lucrative package or if someone is interested in it?? As I watched some RUclips videos in which they are saying that web3 and blockchain are dead and it was all hype??
If the video you watched said this because of quantum computing, I disagree. Quantum Computing is still far far from being anything useful in real life.
One guy says machine learning has high scope in the future, another guy says to not learn it. One guy says learn this high scope, then another says its a waste of time. At this point id rather sell onions.
Reply on your own interest bro, it definitely takes a lot to time to learn all the concepts of Data Science and yea entry level jobs aren't that easy over here, but yea GenAI has a good scope and u need to know at least basic ML to get into GenAI, so reply on your personal interest and choice
Don't just take my advice, or the other guys advice. Do your own research as well, and also take into account your interest, your capacity for time, and effort you can put in. At the end, take an informed decision. That is the whole purpose of this video. So, that people just fall for the hype and promises given out by ed tech companies.
Nice video sir. But I have one doubt. I have already done data science course from renowned institute but still I am struggling to get a job... I am thinking to learn computer vision, but I am unsure the market about computer vision... is it beneficial to learn computer vision to get job in 2025?
While prompt engineering is a valuable skill, it's not a replacement for deep AI knowledge. Many real-world scenarios demand custom solutions beyond simple prompts to OpenAI. Factors like data privacy, accuracy requirements, and client preferences often necessitate building your own small language models (SLMs). This requires a solid understanding of machine learning, deep learning, and transformer models, which can take years to acquire. In our own work, we've encountered situations where relying solely on OpenAI wasn't feasible due to client constraints and accuracy concerns. Therefore, we chose to develop our own SLMs. The idea that you can bypass core machine learning concepts is simply wrong.
Computer Vision was a thing a few years back. CV is already a well researched field now. While you will still need to have a Computer Vision project in your resume, not much is happening right now in it.
I agree. This video is to guide fresher to at least be able to compete for jobs. Which is relatively easier and quicker as a genai expert than core data science. But still learn core ML, DL on the side.
OMG every thing u said is spot on. i wish i knew this long time ago as a fresher who fell into this data science trap freshers listen only come to data and ml field if only u already doing masters in this feild or really passionated and skilled or else its going to be extremly difficult to landa job as fresher in this field. wish this video goes viral u just earned sub Tq
@@TowardsAGIhello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for lucrative package or if someone is interested in it?? As I watched some RUclips videos in which they are saying that web3 and blockchain are dead and it was all hype??
While prompt engineering is a valuable skill, it's not a replacement for deep AI knowledge. Many real-world scenarios demand custom solutions beyond simple prompts to OpenAI. Factors like data privacy, accuracy requirements, and client preferences often necessitate building your own small language models (SLMs). This requires a solid understanding of machine learning, deep learning, and transformer models, which can take years to acquire. In our own work, we've encountered situations where relying solely on OpenAI wasn't feasible due to client constraints and accuracy concerns. Therefore, we chose to develop our own SLMs. The idea that you can bypass core machine learning concepts is simply wrong.
The idea is not to bypass core ML. The idea is to be able to compete in the job market in 6 months, rather than 2 years. The idea is similar to shipping out a MVP (minimum viable product) and then iterate over it, rather than waiting for the full final product before your first ship. I call it MVS (minimum viable skill). I did say in the video that learn genai first, start looking for a job and then also add ML skills on the side. Not completely skip the core ML.
Not sure if you meant so, but I will take it as huge compliment. As in my opinion, motivational speakers are the worst kind of people, biggest scammers.
Searching for Genai isn't any different than any other tech job. Build a good portfolio of genai projects and look for opportunities. I prefer linkedin, both for job search and for building right connections.
superb first point you are the one say this correctly nowadays ed companies portrait wrongly AI career using high salary image but reality for freshers it takes too much time and skills finally they asking experience for freshers and also low pay ,even colleges also provide AI ,data science degrees lol
I don't think I have mentioned ML Engineer even once in the video. If you are confused between Machine Learning Engineer (role) and Machine Learning (Skill) then I will suggest you some basic googling.
@@culturedaadmi4683 While exploring alternative career paths in AI is valid, the claim that ML and Data Science are no longer the best path for freshers in 2025 is misleading. AI continues to grow, and knowledge of Machine Learning remains a fundamental and valuable asset. The best approach for freshers is to acquire a strong foundational understanding of ML and Data Science and then specialize in areas that align with their interests or the evolving AI landscape
sir.. You're giving really great information about DS ML..but you need to change the way to explain it. person will take yawn after some time..add some graphics, some animation
Since I come from AI background, my knowledge of RPA field is superficial, hence I think it's not right for me to comment on it. But I do think some of the RPA work will be taken over by AI Agents in the near future.
To be honest, I have mixed feeling for the data analyst role. Simply because I see LLMs getting better and better at doing what much of data analysts does. While AI is going to impact every tech job, but some more than other. I feel in the case of data analyst, it will on the 'more' side.
In order to be a good Gen AI guy , you must understand DS and ML. You cannot keep relying on Gen AI And tokens for even smaller requirements... You must have your own Algo or model ... Don't fall for this
Lol😂 AI can only provide you certain solutions but to understand those solutions you need to know the DL and ML even to improve your AI results you still need ml and dl
Not really. From what I know, GenAI experts are either Prompt Engineers, or Full Stack Engineers/SDEs who know how to communicate with GenAI LLM APIs, to prompt the API for some response. It's essentially an "AI engineer" without the "AI" part, which might sound confusing, but it's someone who doesn't develop the AI models using TF, PyTorch, etc. like the average AI engineer, but instead uses existed LLMs to get the job done. A Full Stack Engineer can then become a GenAI engineer by learning LLM APIs, and then the GenAI Engineer can become an AI Engineer down the line by learning how to build/train their own models using TF, PyTorch, etc., and create API endpoints using Flash/Django, etc.
@@TowardsAGI See i am not saying you have to master all ,But yet ,At core concept Algebra,Probability,3types of Algorithm category , then Metrices ,Deeplearning, NLP ,these are all will be still core concepts to consider ,Gen Ai is like a Hype ,if a fault is Found in large scale ,The actual people who can fix it are the people who know the core concept ,Like if there is a error in GPT , No pro user can fix it ,only developers can , So na matter how high you fly ...you still need to come to gorund ...thats all
@@TowardsAGIbut sit we need to know ANN to understand genAI.. Whenever comes to ANN there is a backpropagation concept there which is impossible to understand without calculus.. Other thing is ANN loss functions are hectic to understand.. But ML model loss fucntiin are comparatively easy. So genAI without ML seems to be hard.. But these things is not necessary for people who are going to use Third part API to build Gen AI application. But doing so we can't able to understand underlting concepts .. Correct me If I am wrong sir
I think it's an honest and bold approach to bring out the truth as it prevails in the practical world. I appreciate the effort and thak you for the vedeo. It would be useful to many young aspirants.
hello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for lucrative package or if someone is interested in it?? As I watched some RUclips videos in which they are saying that web3 and blockchain are dead and it was all hype??
@@TowardsAGIhello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for a high paying job or because someone have interest in it?? As some videos I have seen in which they are saying that web3 and blockchain was all hype and it is dead...
@@TowardsAGIhello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for lucrative package or if someone is interested in it?? As I watched some RUclips videos in which they are saying that web3 and blockchain are dead and it was all hype??
Amazing Git Hub Repos for GenAI Projects.
1. github.com/NirDiamant/GenAI_Agents/tree/main
2. github.com/huggingface/smol-course
3. github.com/opea-project/GenAIExamples
4. github.com/Yash-Kavaiya/GenAI-Projects
Full Road Map for GenAI Expert:
ruclips.net/video/JDFb4Y9PJnI/видео.html
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@@do_personal9334 Thanks for letting me know. Check the links now.
@@TowardsAGI thanks man
Don't be misleaded by such people, machine learning is still a thing that is worth learning in 2025. If you are making ML models for specific tasks or even doing DL, you would need to know ML. Or even if you are training ready made models to make something, or if you want to fine tune it, you would need to have knowledge of ML. There definitely are many options in AI. But ML is still worth learning.
I am planning to get a job in NLP. What should I do?
@DarshTayal-p9b fresher level he is correct, even top MNC need experienced people for DS, ML roles.
@DarshTayal-p9b "I am planning to get a job at NLP".. aise sirf job mindset rakhoge to inn fields me nahi milega job.. ML and related fields are more passion/knowledge and research oriented compared to other fields. You have to be truely passionate about algorithms, about the techniques and especially about the subject. You need to read lots of research papers, read about what is being used in NLP fields right now and how engineers are solving the present challenges etc then after learningthe basics you'll have to build projects and contribute to open source projects (Currently since 6 months I am not into NLP so I cannot directly tell you what to do for sure but do your own research and you'll be good).. But whatever, the bottom line stays same, you have to be truely passionate about the subject and patient enough till you get an offer. NLP or ML/DL fields are not like your average IT job. Do learn, do contribute, be passionate and you'll do good. All the best!
Thanks for your insight. ML is still a thing, and will remain so for foreseeable future. And I do state it in this video as well. The target audience for this video are not seasoned players in ML. But those who have spent money, time and effort, taking up courses on Data Science, hoping to find a well paying entry level job, only to know later otherwise. This video is only to ease out their struggle in landing their first job.
@TowardsAGI I appreciate you responding back to my comment! But what I understand from your video that you have targetted for audience that are trying to get a job in AI field easily (relatively). I do agree Gen AI job is more easier to get than a traditional ML/DS job due to complexity of ML/DS, and for Gen AI you don't really need much knowledge about complex topics unlike ML/DS. But I believe you may have made the video title and thumbnail a little extreme and a little oversimplified your argument. ML/DS is indeed a long journey, but arguably even for Gen AI you would need to know programming, and math level for a job level is not that complex, mostly high school maths. But yes, you would need to spend time and effort in learning algorithms and libraries, that's the main part. But even for making Gen AI tools you would have to know prompt engineering, programming, API development and stuff. It is relatively easier and your argument here is correct, and I think for entry level jobs, basic knowledge will be good, but I think as you advance or if you are making more complex tools, even tho you directly arent using ML algorithms but it's still a good thing to know, sometimes you may have to fine tune or train on more data. I may be a little wrong here, but still, I don't think most Gen AI tools in the real world work without fine tuning and a good system prompt. And arguably unlike ML where you have to have a good foundation of maths, I think to make a good prompt you would have to have a good foundation of linguistic skills. And I think a lot of people are still making efforts to learn ML and still getting a job. I think, even tho Gen AI may be relatively easier but still efforts and time is needed.
To be great as a Gen AI expert , you need to have an understanding of how machine learning works, so don't skip it !
It's true, you'll be a better Gen AI expert if you understand ML. But it's not mandatory skill. This video doesn't talk about skipping ML, but only talk about how freshers can get into AI faster. Learn GenAI first, and then add ML skills later.
machine learning is the stepping stone, more like the foundation to everything else. learning machine learning first, and then other subsets of AI, clears your basics and makes you stronger in this field. stop misleading people by giving curious titles to videos. i didn't watch the video and i won't either. v v wrong title. if you are just another sheep wanting to land a job, go ahead w this person's advice. all the passionate AI enthusiasts who genuinely are trying to contribute to the community will not at all agree with the title of this video. disappointed!
indeed
First of all, I am happy that we have passionate AI enthusiasts like you. But you got riled up for nothing. This video is not about dishing it out Machine Learning. Instead this is for those who have taken courses, spent money and time, hoping to find a well paying entry level job as a data scientist easily, only to find the grass is not as green as it was made out to be.
However, I do disagree calling those who just want to land a job as another sheep. Being able to follow own passion is also often a luxury not many can afford, and the only option they have is 'land a job'.
This video is for them.
You are extremely right, really appreciated your comment.
Your suggestion will work, especially for entry level. In my experience, surviving on gen AI alone for mid to senior role is not possible, for example, people making carrer transition mid-career. This is because for senior level roles, they are looking for "full stack data scientist", as you mentioned in the beginning.
Yes, this advice is purely for entry level. And they need to add the ML, DL skills later on.
Having been a full stack data scientist and having experience of 8 years in data science (I am also Master of data science from top tier university), I agree partially with this lecture. There is indeed saturation at entry level. However the very second reason he offers ["The subject is very complex and requires learning programming language, statistics, Cloud knowledge, deep learning, AI, MLOPs, deployment"], itself is the reason why the initial tough competition and the crowd of curious folks will disappear. So, those who persevere will succeed for sure. I FULLY AGREE WITH HIS STATEMENTS ABOUT FUTILITY OF 1 MONTH /3 MONTH/6 MONTH COURSE. MINIMUM 1 YEAR (180 TO 220 HOURS) FOR A GRADUATE PERSON WITH NICE MATH AND ENGLISH BACKGROUND. I however do not agree with advice of jumping directly to generative AI. GENERATIVE AI IS A MUST HAVE SKILL, BUT TO MAKE FULL USE OF IT (IN MACHINE LEARNING DOMAIN) YOU MUST HAVE FUNDAMENTALS OF MACHINE LEARNING CLEAR)
When I say genai expert, I mean API implementation rather than model development. Just so that the freshers can be at least start competing for those roles. I did advice them to learn code ML and DL once they have done a decent number of geani project.
I appreciate your content sir as it's definitely very helpful, can you suggest the prerequisites for learning GenAI for an absolute beginner who doens't want to invest 2 years on data science but interested in AI..
I'm in field of IT under operations and my focus and commitment towards learning data science is nowhere due to large amounts of resources and a lot of bootcamps provided by Ed tech companies and RUclips educators.
As mentioned kick starting a career in Gen AI is a good choice of career transition?
I am also doing the Same thing like u and trying to move towards ds.
If you intend to transition to a career in AI, following the GenAI path will be easier. When I say easy, I mean relatively easier than DS option. But I think it's obvious that it will sill require hard work, focus and intertest. Bes of luck!
Generative AI is an exciting and rapidly developing field, transitioning directly into it without solid foundational knowledge in Data Science or ML may not be the most effective approach. It's essential to have a well-rounded understanding of the core AI concepts before diving into Gen AI. With the right approach, freshers or professionals in IT can start building a career in AI, whether through Data Science or a combination of Gen AI and operations, but it requires patience, focus, and structured learning.
While prompt engineering is a valuable skill, it's not a replacement for deep AI knowledge. Many real-world scenarios demand custom solutions beyond simple prompts to OpenAI. Factors like data privacy, accuracy requirements, and client preferences often necessitate building your own small language models (SLMs). This requires a solid understanding of machine learning, deep learning, and transformer models, which can take years to acquire. In our own work, we've encountered situations where relying solely on OpenAI wasn't feasible due to client constraints and accuracy concerns. Therefore, we chose to develop our own SLMs. The idea that you can bypass core machine learning concepts is simply wrong.
But I don't have laptop for doing and practicing python 😢
All this youtuber are like - don't learn machine learning in 2025 , don't learn web dev , don't learn app dev , don't learn digital marketing don't respect your parent
All you should do just make content and tell others what not to do
Making content, giving out an advice that you believe in, is better than just seeing thousands regret their career choice.
At the end, it is still their choice. My advice is not binding on anyone.
He is right about the Full Stack Machine Learning role. There seem to be no entry roles in ML and companies globally want someone with 5-8 years of experience. I used to think the ML engineers will work with Data Scientists and Data Analysts with cleaning data and processing the data to develop models and that they only need to focus on learning Machine Learning. But where I work they are asking us to first start with Data Analysis, then learn Data Science, Gen AI and finally move to Machine Learning. So they are training us for 1 year on this and I have completed the Data Analysis so far, it helped me with Python, SQL, R and the Python libraries like Numpy and Matplotlib. It is helping us understand how everything works in Machine learning at the end. On the other hand Gen AI seems to be easy role where a non-tech can easliy grasp the concepts and implement projects since it is interesting. Thank you for the insightful video.
Thanks You have given me a good solution for my confusion. Please suggest some book
Yes, I have learn Data Science and trying for the entry-level jobs from 2 years but not able to find, Later the insights from the HR's from the company and software engineers who are working, is the roles related to machine learning and data science required min of 3-4 years of experience.
If you are beginner it is very difficult to find a job related to data science
Yes, it's the unfortunate realty at the entry level which people don't to talk about.
sir,
please elaborate it.
Presently I am doing PGDiploma in AI from CDAC.
I wanna learn this skill.
Guide.
sir nowdays everyone says no job in ai engineer for fresher who has limited skills in ml stats dl only difficult n interview also they ask core questions focusing on genai is not good having knowledge is plus fresher what is ur opinion
I couldn't understand your question properly.
@@TowardsAGI sir interview perspective only core question ml dl asked right and u say learn gen ai directly somewhere doesn't fit well for freshers
@@HDSV10 Companies want everything from one person. They ask 100 things during interview and not use even 10 out of them during job.
As a fresher, you can't just rely on answering questions in an interview. Build a compelling portfolio of genai projects. If you can showcase your work, interview takes a back seat.
Sir eagerly awaiting the GenAI masterclass you mentioned in your last video! It would be a great way to kick things off.
I hear you! The GenAI masterclass is in the works, and I'm really excited to share it with you all. 🙏
Hello Satish ! Adarsh here.....I am working in Gen AI Model Validation right now in Banking industry. Although Im new to Data science but have good grasp of ML, DL and GenAI concepts, I want to understand, what are the potential jobs I should be targeting later on to grow fast in terms of compensation and exposure especially focussing on GenAI ?? Thanks in advance 😊
Hi Adarsh,
Keep getting stronger in ML and DL. And focus on Agentic AI projects. Agentic AI systems is the flavor of 2025.
@@TowardsAGI Thanks a lot Satish !! I totally agree as per the buzz I am currently witnessing across the web
Please make a video on how to apply and get the job as a genAl dev
In the works, coming out soon!
@@TowardsAGIhello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for lucrative package or if someone is interested in it?? As I watched some RUclips videos in which they are saying that web3 and blockchain are dead and it was all hype??
Shall we take this recommendation as learn to drive the surf board but skip swimming classes, wind direction prediction, waves formation?
This is almost like saying skip any course that says it will teach you something in 3 months. Instead of 3 months, he says 6 months. Now will that not keep you interested?
GenAI may be useful. But focusing on that predominantly isn't enough in my opinion. That may be like learning to drive the water surf board. Would someone allow you to go to sea with that knowledge alone? I doubt it. They would expect you to know swimming definitely. understanding wind directions, wave formations, what type of board to be used when and so on.
I appreciate the effort in putting down your thought. However, it seems my definition of GenAI expert is different than what you have assumed.
I am only taking about somebody who can build geani solutions using API implementation, not model development.
I don't think core ML, DL skills are must for it.
I know startup founders who have build complete suite of genai product without even a single data scientist in their team. With only software developers.
I said skip any 'data science' course that says 3 months, not just any course. There are in fact a lot of things you can learn in 3 months. A course on how to make jalebis will definitely take less than 3 months. Not data science.
Also, I am not saying 6 months instead of 3 months, because 6 months is not for data science, but an alternate relatively easier skill of genai.
@@TowardsAGI Got it. I was wrong and sorry about that. Still, I'm concerned about one thing. Any skill that's easy to learn can easily be replaced by AIs in very near future. So not sure if this is this right to choose.
Great video, what about the GenAI masterclass series you talked about in your previous videos?
In the works, Should be out in the next 2-3 weeks.
I completely agree with your point my friend you have really made a point here with ease looking forward for more of these cutting edge technology videos!
Thanks for the appreciation!
Appreciate your thoughts, intrested in getting a in AI. Please post the video what your are saying, waiting for that..
Will do so. Thanks
i sort of agree how you put up this issue like this and i would love to see another video of you where do describe more on how to land on my first gen ai job and what projects to do and how to sell myself gen ai Expert.
Thanks, the next video is in the works and will be out soon.
I'm coming a full circle from a critic to someone who's seeking help. (No shame in admitting mistake). Please ignore my previous comments and help me further 😊
Help me understand more about GenAI. It sounds as if the work of a GenAI expert is just to use an existing AI model's API and build a tool needed for the respective company around it. It feels like same as user of chatgtp. Except, a user is using the front end interface of the API and a GenAI expert is directly using the API programmatically. Is that all the difference?
If that's the case, I don't see there's anything to learn about GenAI for someone who understand backend development. Is there anything more to that? I mean like, does a GenAI expert train / fine-tune the models using his own dataset? If so.. does this involve skills like curating and annotating datasets or understanding AI models?
Data Science is not an entry level position. Usually you gain some experience from other data roles like data analyst or business analyst or have Masters degree and transition into Data Science. Data Science requires a good practical knowledge of statistics and not just ML algorithms. Now-a-days you will also be doing a bit of data engineering sort of task like bringing a specific type of data for analysis or Model building through a pipeline
I agree. Data Science is not a beginner-friendly field.
Loved your content. Please make a video on roadmap for Gen AI expert!
Thanks you!. A roadmap of the skills required for GenAI expert is already there on my channel.
A video on 6 month roadmap to learn those skills is in the works.
This is a truly practical video reflecting the current global scenario. As mentioned in the video, could you share insights on how to land a job in Generative AI?
Thanks. A video on that is in the works. Should be out in the next 2-3 weeks.
Hey, I need a suggestion. Gen-ai is used for 'Product making" by most companies or startups. But what if I want to get into fraud detection, biotech or fintech using ML and DL. Basically away from gen-ai. Is this a good idea for fresher? I mean do companies hire fresher for such roles? Or Gen-ai is the only path to get into industry?
See, since genai itself is new, companies at times will look over experience if you can showcase some good personal projects in your portfolio. Traditional ML is great, but you will be competing against a lot more aspirants for limited job opportunities. Companies also tend to prefer experience, often even asking for Masters or PHD in the field.
Thanks Sir for the great advice. I can understand the depth of your advice.
Glad you found it insightful.
DSA required?
No, not a mandatory skill for AI.
as a fersher no one gives job as generative ai engineer that easily it is as tough as getting job in core ML
Getting any job is tough. What this video talks about is that it's 'relatively' easier to get into GenAI than ML, considering the time, effort and the available opportunities.
True there is so so much oversupply for data science and Al jobs.
Just joined a data science course and ended up here! Good start i guess
I am sorry that this video makes you feel this way. Instead, take it an insight for the future. Learn the Data Science, but also keep focus on the genai. At the end you will have both skills which will make you even more valuable.
Just keep an idea and go ahead with gen Ai. That's it. AI is now a service. It's very rare that we need to build a model.
Thanks sir for your forward thinking strategy on how to get into AI field. Please make that video on how to go about becoming an generative ai expert and how one can market as such
Will do so. Thanks
Randomly bumped into your video. Thanks, man, for the great advice. I am a senior engineer with solid dev experience around Microsoft from dotnet to dotnetcore ,azure, API's dev , devOps architecting and integrating stuff from Microsoft eco system to other worlds . It's absurd when I see the hype of GenAI . I remember a recruiter lady told me over the phone don't go for master's in data sciences, as she receives 150+ resumes of people having specialized master's degrees and there are handful jobs available. When I see the learning graphs being shared, I seriously want to vomit, this is not reality, the paths shown in graphs in Data Scientist makes me laugh. you probably gave the best advice. Will stick to it.
Glad to be of help!
Hey, thanks! I was so confused about data science vs. Gen AI - three weeks of agonizing! I finally picked AI, but I'm still wondering if it's right. Your video was a huge relief; I feel much better about my choice now.
I'm glad the video helped you feel more confident about your decision!
@TowardsAGI Really heartfelted thank you for your video.God bless you for your work and all your efforts.
I am data analyst with 6 months intern + 6 months of full time and i always wanted to be ai ml guy i have baisc knowledge of ml algorithms now wanted to move to ai space so should I target more data scientist roles but whenever I see the role for ML/AI roles they wanted experience of 3+ year so should I try in gen ai space or should I continue to try in Data Science Jobs
It's a tough call, but I would recommend focusing on genai and ML equally (since you have an interest in ML). The entry barrier for geani ai is lower than data science. But it will still be tough as expected.
Have 2 yrs experience in software development, studying datascience for 4 months , continuously on loop , couldn't able to keep up .
If you are really passionate about core ML, try harder. I can understand it can get overwhelming at time, specially with a full time job. Else, you can try going the GenAI path. Build a good portfolio.
Such a gold advice on the entire internet. Thanks a lot.
Thanks Shankar!
I'll take back all my comments and conclude that his intentions are that if you're passionate about the AI / ML overall, take the long path of 2+ tireless years which is still going to be much more valuable in the long run. But if you believe that path would be a struggle for you, take an easier path of becoming GenAI expert and then go on to learn other skills slowly.
I believe the intentions are honest but not understood in the first go itself.
Thank you so much! This helps me to put my efforts into something that gives back results or appreciation sooner in this market and also accepting the trend. 🙌🙌
Glad it helped you make a good decision!
@@TowardsAGIhello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for lucrative package or if someone is interested in it?? As I watched some RUclips videos in which they are saying that web3 and blockchain are dead and it was all hype??
Im working as VB NET and Sql developer for 7 years, i need a transition, so i plan to learn in demand skill and land a job(remote).
which will be smoother for me? Gen AI expert or Data Engineer With Aws/Azure.
Both are good options, it depends on your interests and learning preferences.
Data Engineering is a good option if your prefer less coding and more interaction with data. GenAI expert otherwise.
Very Very Helpful Sir, Thank U Very Much ❤
Btw are u a Software Engineer?
Thank you, glad you liked it. Between 9-5 I work as a Lead Data Scientist.
correct sir, very big and vast subject for data science and very interesting concepts when i learn . i invested 2 years from 2022- 24, after i leave my job i done some many projects on deep learning and machine learning , but still i am not getting interview call also and sure i will get data scientist job in this year
Thanks. Hard work eventually pays. All the best.
@@TowardsAGI thank u sir
I am having 5 years in ML, want to transition to Gen AI (Not having software development skills) - How should I plan it ? (Not sure where to focus)
I will recommend my previous video, 'Full Roadmap to GenAI Expert'. I think it will help you.
This video is a test to our learning. He says don't trust someone who says learn something in 3 months instead of a tiring 2 years. He ends up saying learn something in 6 months. Connect the dots which is what he wants us to do.
If you aren't able to spend a tiring 2+ years into learning in 2025, and instead focus on learning something in 6 months, you are not job ready or you should be extremely lucky.
Every skill has it's own requirements. So, I am not sure why you think it's okay when I say data science in 3 months is scam, but it's not okay when I say genai expert in 6 month is feasible.
I think of it on the lines of MVP, minimum viable product. You ship out your MVP first and then iterate on it for full functionality.
Same way, genai expert is the MVS, minimum viable skill to be able to start competing in the job market as a fresher. And then you iterate on it and add ML/DL skills down the line.
@@TowardsAGI That's because I immediately explored various JD for GenAI experts and many have the other skills that you suggest to be skipped as a fresher to be important skills to have. I understand you the JD would always say but you can still be selected without it. But when I compete with someone who isn't at an MVP state and are knowledgeable in other stuff, then I'm gonna miss.
I am agreeing with you in 1 point though. If we aren't willing to invest even 2+ years of tireless knowledge seeking, then we will get carried away in this era where machines can do most of the low level jobs. It's going to be survival of the fittest as always. But even tougher in the AI era.
hello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for lucrative package or if someone is interested in it?? As I watched some RUclips videos in which they are saying that web3 and blockchain are dead and it was all hype??
If the video you watched said this because of quantum computing, I disagree. Quantum Computing is still far far from being anything useful in real life.
@TowardsAGI no it doesn't say because of quantum computing.
One guy says machine learning has high scope in the future, another guy says to not learn it. One guy says learn this high scope, then another says its a waste of time. At this point id rather sell onions.
Reply on your own interest bro, it definitely takes a lot to time to learn all the concepts of Data Science and yea entry level jobs aren't that easy over here, but yea GenAI has a good scope and u need to know at least basic ML to get into GenAI, so reply on your personal interest and choice
Don't just take my advice, or the other guys advice. Do your own research as well, and also take into account your interest, your capacity for time, and effort you can put in. At the end, take an informed decision. That is the whole purpose of this video.
So, that people just fall for the hype and promises given out by ed tech companies.
Eye opening❤❤❤.. Very informative❤❤❤
Finally I got someone with Truth and unbiased thinking!
God Bless you man!!!!!!
Thanks!
Nice video sir.
But I have one doubt. I have already done data science course from renowned institute but still I am struggling to get a job... I am thinking to learn computer vision, but I am unsure the market about computer vision... is it beneficial to learn computer vision to get job in 2025?
While prompt engineering is a valuable skill, it's not a replacement for deep AI knowledge. Many real-world scenarios demand custom solutions beyond simple prompts to OpenAI. Factors like data privacy, accuracy requirements, and client preferences often necessitate building your own small language models (SLMs). This requires a solid understanding of machine learning, deep learning, and transformer models, which can take years to acquire. In our own work, we've encountered situations where relying solely on OpenAI wasn't feasible due to client constraints and accuracy concerns. Therefore, we chose to develop our own SLMs. The idea that you can bypass core machine learning concepts is simply wrong.
Computer Vision was a thing a few years back. CV is already a well researched field now. While you will still need to have a Computer Vision project in your resume, not much is happening right now in it.
I agree. This video is to guide fresher to at least be able to compete for jobs. Which is relatively easier and quicker as a genai expert than core data science. But still learn core ML, DL on the side.
OMG every thing u said is spot on. i wish i knew this long time ago as a fresher who fell into this data science trap
freshers listen only come to data and ml field if only u already doing masters in this feild or really passionated and skilled
or else its going to be extremly difficult to landa job as fresher in this field. wish this video goes viral
u just earned sub Tq
I am glad you found my perspective right. I have seen a lot of people falling into this trap over the last few years
@@TowardsAGIhello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for lucrative package or if someone is interested in it?? As I watched some RUclips videos in which they are saying that web3 and blockchain are dead and it was all hype??
Explained well what really works and needed to the IT market
Thanks
While prompt engineering is a valuable skill, it's not a replacement for deep AI knowledge. Many real-world scenarios demand custom solutions beyond simple prompts to OpenAI. Factors like data privacy, accuracy requirements, and client preferences often necessitate building your own small language models (SLMs). This requires a solid understanding of machine learning, deep learning, and transformer models, which can take years to acquire. In our own work, we've encountered situations where relying solely on OpenAI wasn't feasible due to client constraints and accuracy concerns. Therefore, we chose to develop our own SLMs. The idea that you can bypass core machine learning concepts is simply wrong.
The idea is not to bypass core ML. The idea is to be able to compete in the job market in 6 months, rather than 2 years.
The idea is similar to shipping out a MVP (minimum viable product) and then iterate over it, rather than waiting for the full final product before your first ship.
I call it MVS (minimum viable skill).
I did say in the video that learn genai first, start looking for a job and then also add ML skills on the side.
Not completely skip the core ML.
This guy is a reverse Motivational speaker 🤣
Not sure if you meant so, but I will take it as huge compliment. As in my opinion, motivational speakers are the worst kind of people, biggest scammers.
@@TowardsAGI absolutely 💯 confirm as a Sri Lankan
Passed out from 10th grade
But I want to be a data scientist
If I will be
Please do that video on Gen Ai job thing 😊
In the works. Thanks
Thank you sir for these insights
Glad you found the video helpful.
How do we search for the real Gen AI Jobs Sir? The video was great!!!
Searching for Genai isn't any different than any other tech job. Build a good portfolio of genai projects and look for opportunities. I prefer linkedin, both for job search and for building right connections.
sir please make a video on genai
In the works, will be out soon.
Please make the road map for GenAi
In the works, Should be out soon. Thanks
Thanks for the clarity
I'm glad you found it helpful! 😊
Very nice video, you deserve more views and subs
Glad you found the video helpful! 😊
For a change someone speaks so much logic and sense
Please Sir, Go ahead and do the video on how to land a Job in Gen AI. It will be surely worth it. Kind Regards and Thanks s mill!!!
In the works, Should be out soon. Thanks
@@TowardsAGI We are looking forward to it. Meanwhile, we shall continue to work on Agentic Projects.
superb first point you are the one say this correctly nowadays ed companies portrait wrongly AI career using high salary image but reality for freshers it takes too much time and skills finally they asking experience for freshers and also low pay ,even colleges also provide AI ,data science degrees lol
Yeah, it's the unfortunate reality that no one want to talk about. Ed companies are simply over selling these options to maximize their profit.
SIR I want to master in NLP in Ai Is it rewarding plz?
NLP is quite rewarding and there is still a lot work going on in this field. Better choice than CV for sure.
dont confuse machine learning engineer and AI developer.....those two diffrent paths. Dont just create content if you dont know what your saying.
I don't think I have mentioned ML Engineer even once in the video. If you are confused between Machine Learning Engineer (role) and Machine Learning (Skill) then I will suggest you some basic googling.
@@TowardsAGI Then your title is WRONG, YOUR CONFUSING BEGINNERS WHO ARE WATCHING YOU. MAKE YOUR TITLE RELEVANT !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
@@TowardsAGII teach Machine learning at MIT dont confuse them let them learn
@@DeepDiveAI-j4r really dude
@@culturedaadmi4683
While exploring alternative career paths in AI is valid, the claim that ML and Data Science are no longer the best path for freshers in 2025 is misleading. AI continues to grow, and knowledge of Machine Learning remains a fundamental and valuable asset. The best approach for freshers is to acquire a strong foundational understanding of ML and Data Science and then specialize in areas that align with their interests or the evolving AI landscape
You don't know what you are telling.
Just want to reduce competition.
I have one word for you. LOL!
Super informative 👍
Glad you found it helpful! 🙏
Yes sir waiting for genAI first job getting vdo and resources to learn
That video will be out roughly in 2-3 weeks time. Working on it. Thanks
sir.. You're giving really great information about DS ML..but you need to change the way to explain it. person will take yawn after some time..add some graphics, some animation
Thanks for the suggestion. Yes, I get you. There's still a lot of scope for improvement.
Very practical advice for beginners
I'm glad you found it helpful!
Don't learn Machine Learning instead start selling Vadapav, get rich in 2025 🎉
There is competition in selling vadapav as well!
Sir what about Robotic Process Automation
Since I come from AI background, my knowledge of RPA field is superficial, hence I think it's not right for me to comment on it. But I do think some of the RPA work will be taken over by AI Agents in the near future.
What about data analyst a d genAI
To be honest, I have mixed feeling for the data analyst role. Simply because I see LLMs getting better and better at doing what much of data analysts does. While AI is going to impact every tech job, but some more than other. I feel in the case of data analyst, it will on the 'more' side.
Sir please Make Video About GenAi expert
In the making. Will be out soon
waiting for next video
Thanks, will be out soon
very informative sir..
Thanks, I'm glad you found it insightful!
In order to be a good Gen AI guy , you must understand DS and ML.
You cannot keep relying on Gen AI And tokens for even smaller requirements... You must have your own Algo or model ...
Don't fall for this
Lol😂 AI can only provide you certain solutions but to understand those solutions you need to know the DL and ML even to improve your AI results you still need ml and dl
I agree.
Fundamental of ML is still important for Gen AI
While no knowledge is bad knowledge, I am curious to know which ML skill you think is must for building genai based application
Not really. From what I know, GenAI experts are either Prompt Engineers, or Full Stack Engineers/SDEs who know how to communicate with GenAI LLM APIs, to prompt the API for some response. It's essentially an "AI engineer" without the "AI" part, which might sound confusing, but it's someone who doesn't develop the AI models using TF, PyTorch, etc. like the average AI engineer, but instead uses existed LLMs to get the job done.
A Full Stack Engineer can then become a GenAI engineer by learning LLM APIs, and then the GenAI Engineer can become an AI Engineer down the line by learning how to build/train their own models using TF, PyTorch, etc., and create API endpoints using Flash/Django, etc.
@@TowardsAGI See i am not saying you have to master all ,But yet ,At core concept Algebra,Probability,3types of Algorithm category , then Metrices ,Deeplearning, NLP ,these are all will be still core concepts to consider ,Gen Ai is like a Hype ,if a fault is Found in large scale ,The actual people who can fix it are the people who know the core concept ,Like if there is a error in GPT , No pro user can fix it ,only developers can , So na matter how high you fly ...you still need to come to gorund ...thats all
@@Codershub-h5f you're absolutely correct bro.
@@TowardsAGIbut sit we need to know ANN to understand genAI.. Whenever comes to ANN there is a backpropagation concept there which is impossible to understand without calculus.. Other thing is ANN loss functions are hectic to understand.. But ML model loss fucntiin are comparatively easy.
So genAI without ML seems to be hard..
But these things is not necessary for people who are going to use Third part API to build Gen AI application. But doing so we can't able to understand underlting concepts ..
Correct me If I am wrong sir
I think it's an honest and bold approach to bring out the truth as it prevails in the practical world. I appreciate the effort and thak you for the vedeo. It would be useful to many young aspirants.
Thanks. I'm hoping it will save some people from making the same mistakes.
hello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for lucrative package or if someone is interested in it?? As I watched some RUclips videos in which they are saying that web3 and blockchain are dead and it was all hype??
Please don't misguide peoples
Why do you think I am ?
@@TowardsAGIhello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for a high paying job or because someone have interest in it?? As some videos I have seen in which they are saying that web3 and blockchain was all hype and it is dead...
@@TowardsAGIhello sir can you please tell me that learning blockchain and web3 is worth it in 2025 for lucrative package or if someone is interested in it?? As I watched some RUclips videos in which they are saying that web3 and blockchain are dead and it was all hype??
og
Thanks