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.
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.
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 TH-cam 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
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
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 TH-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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.
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
@@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 TH-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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
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 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.
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 TH-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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.
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?
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.
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.
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.
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 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.
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
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.
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.
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.
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 TH-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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.
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
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
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.
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 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 TH-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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
@@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 TH-cam 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:
th-cam.com/video/JDFb4Y9PJnI/w-d-xo.html
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@@do_personal9334 Thanks for letting me know. Check the links now.
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.
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.
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 TH-cam 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.
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
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
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 TH-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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.
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
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 TH-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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
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.
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.
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 TH-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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. 🙏
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.
DSA required?
No, not a mandatory skill for AI.
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.
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.
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.
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.
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.
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.
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 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.
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
Explained well what really works and needed to the IT market
Thanks
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.
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.
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.
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.
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 TH-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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 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.
Very nice video, you deserve more views and subs
Glad you found the video helpful! 😊
True there is so so much oversupply for data science and Al jobs.
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.
Thank you sir for these insights
Glad you found the video helpful.
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.
Thanks for the clarity
I'm glad you found it helpful! 😊
You don't know what you are telling.
Just want to reduce competition.
Very practical advice for beginners
I'm glad you found it helpful!
Super informative 👍
Glad you found it helpful! 🙏
Please make the road map for GenAi
In the works, Should be out soon. Thanks
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
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.
For a change someone speaks so much logic and sense
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.
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.
sir please make a video on genai
In the works, will be out soon.
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.
very informative sir..
Thanks, I'm glad you found it insightful!
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 please Make Video About GenAi expert
In the making. Will be out soon
waiting for next video
Thanks, will be out soon
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.
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 TH-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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
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 TH-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
og
Thanks