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.
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.
So you are advising the freshers to be a GenAI expert withing 6 months without knowing ML and DL? To be able to grasp the ideas behind Gen AI, you must know the concepts of RNN, GRU, LSTM, Attention and Transformers. In order to know these things you must know what is optimization and loss function. In order to know optimization an loss function you must know how ANN works. In order to know ANN, you must have solid foundation in classical ML theory. So in one sentence, You must know classical ML and DL in order to crack any interview in GenAI field.
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.
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.
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.
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 UA-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.
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.
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.
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.
Hi , I just wanted to know if a person like me who is system admin/application support for more than 6 years who want to transition into data science will I be considered as a fresher / or entry level .?
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.
I need suggestions everyone... I am ios developer and having 2 year solid exp in ios swift and flutter apps as well... But now i think i want to move ios to Ai paths But i am confused which is the best path no idea about ML vs Ai Focus on Ai or ml Which is the best pathsss... Please any one help me how to avoid any conflict...just i need clear road map
If a person does not understand what is standardization or normalisation then how they will be able to understand the quantasised models, if they don't know what is transfer learning then how come they understand the concept of fine tuning... If the person does not know feed forward network or attention mechanism the person will not be understanding the concept of transformer. Don't you think the person should understand the basics first and then they can start the genAI. Other wise the people will loving solve the determinstic problems with generative model and eventually that will create a mess.
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!
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
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 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 UA-cam 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.
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.
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.
I am a mechanical engineer at Tata Motors with 18 years of experience. My current salary is 15 LPA. Additionally, I have 15 years of deep experience in the stock market. However, I feel frustrated in my current field and want to switch or improve my skills in the AI domain-not for salary reasons, but for self-improvement. Over the past two months, I have been learning Python, SQL, and most machine learning concepts. I feel confident that I can make a switch or gain some experience in this field. Please guide me with good suggestions.
afaik for freshers it is really tough to get into ML roles in India. There are many pay after placement bootcamps in Data Science. You may try them. In it you will get placement assistance.
So, your's is different case than the target audience this video was made for. If you are employed, and can remain employed, then there is no pressure on you to get a job in AI asap. In that case you can use the next 1-2 years building your AI profile. You did not mention if you have joined some course or learning on your own. People often tend to loose focus, or get lost in the ocean of learning material available online when they prepare on their own. So if not already, I will suggest a long term course, just for the structured learning it provides. Since you are from mechanical background, see if you can merge these two disciplines. As in, if you can find use cases for ML in the mechanical engineering work that you have been doing. This could show continuity in your profile. You can even apply ML in stock market. It's a long and tough journey, but worth it, if you have the appetite for it. All the best.
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.
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..
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.
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?
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
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.
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 😊
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.
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
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.
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.
@@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 UA-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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.
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.
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?
There is nothing to admit bro. It was just that our definition of a genai expert was differed. To answer your questions: " 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? " Not really. It's not same as just using chatgpt via an api. Buling genai apps over say openai's API require multiple other skills like effective prompt engineering, basic or advanced RAG techniques, third party frameworks like langchain, lammaindex, langraph, autogpt, crewai, agents and agentic system. Partial or full fine tuning is not that common, but sometimes becomes necessary depending the use-case. And of course some frontend-backend skills as well. Understanding of AI model helps in certain scenario but is not must in most case. On the other end of spectrum, people are building genai apps using no-code tools as well.
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.
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 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.
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 UA-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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 UA-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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.
Don't be mislead the peoples. There are lot of peoples are giving shortcut path for mastering in AI. I have done M.Tech in Artificial Intelligence and Machine Learning, As of my experience, Freshers could start learning AI from ML. Because everything will come and go, but fundamentals always remain as it is. Linear Regression is the best example of this. Make fundamentals strong and then jump to other things in AI. This video is totally misleading for peoples.
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
Is there any job in India for which there is no oversupply ??❤ ML jobs have oversupply but it is less compared to the oversupply compared other jobs and more compared to oversupply in other software roles.❤ Software is a dynamic fieldand even the most in demand field will get saturated very soon, one has to begin somewhere ,get your foot in the door and keep learning.❤ Business Analytics is taking over almost all managerial roles slowly ,even HR, Mktg, Sales and Finance with Fintech ❤ ❤❤❤❤❤❤❤❤❤❤❤
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.
Am learning machine Learning, Deep Learning with Pytorch and Doing my computer Science Degree at the same time. Am also a Backend Engineer. Am a G man real Sigma🤣😂🤣😂🤣😂🤣😂
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.
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:
ua-cam.com/video/JDFb4Y9PJnI/v-deo.html
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@@do_personal9334 Thanks for letting me know. Check the links now.
@@TowardsAGI thanks man
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.
@@TowardsAGI To me this is the ideal route.
Not necessary bro.
i am not a ML expert, but got into Gen Ai , i have learned and implemented many things but I do agree that understanding of ML would have been better
@ at least you got in; no you can transition into ML engineering.
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.
So you are advising the freshers to be a GenAI expert withing 6 months without knowing ML and DL? To be able to grasp the ideas behind Gen AI, you must know the concepts of RNN, GRU, LSTM, Attention and Transformers. In order to know these things you must know what is optimization and loss function. In order to know optimization an loss function you must know how ANN works. In order to know ANN, you must have solid foundation in classical ML theory. So in one sentence, You must know classical ML and DL in order to crack any interview in GenAI field.
sensible comment.
I respect this mindset. Wonderful comment
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.
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.
Bro your video does not make sense u wasted my data machine learning is the foundation of Generative AI
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.
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 UA-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.
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.
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.
what about data analyst is it right to learn in 2025 ?
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.
Should I learn Gen AI or AGentic AI to get started my career in AI in 6 months. which is shortest path. Thanks
Hey I want to be an AI engineer. So I just start the journey by learning python. what should be my next step?
Hi , I just wanted to know if a person like me who is system admin/application support for more than 6 years who want to transition into data science will I be considered as a fresher / or entry level .?
Since Data Science is completely different than system admin, should you be able to make a transition, you will most probably considered fresher.
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.
I need suggestions everyone...
I am ios developer and having 2 year solid exp in ios swift and flutter apps as well...
But now i think i want to move ios to Ai paths
But i am confused which is the best path no idea about ML vs Ai
Focus on Ai or ml
Which is the best pathsss...
Please any one help me how to avoid any conflict...just i need clear road map
If a person does not understand what is standardization or normalisation then how they will be able to understand the quantasised models, if they don't know what is transfer learning then how come they understand the concept of fine tuning...
If the person does not know feed forward network or attention mechanism the person will not be understanding the concept of transformer.
Don't you think the person should understand the basics first and then they can start the genAI.
Other wise the people will loving solve the determinstic problems with generative model and eventually that will create a mess.
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!
Perfect Analysis.
Can you please share your thoughts on DevOps?
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.
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. 🙏
Finally I got someone with Truth and unbiased thinking!
God Bless you man!!!!!!
Thanks!
Don't learn Machine Learning instead start selling Vadapav, get rich in 2025 🎉
There is competition in selling vadapav as well!
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.
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.
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 UA-cam 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.
You were spot on @14:15 when you said that - to transition into a AI career (entry-level)!
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.
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.
I am a mechanical engineer at Tata Motors with 18 years of experience. My current salary is 15 LPA. Additionally, I have 15 years of deep experience in the stock market. However, I feel frustrated in my current field and want to switch or improve my skills in the AI domain-not for salary reasons, but for self-improvement.
Over the past two months, I have been learning Python, SQL, and most machine learning concepts. I feel confident that I can make a switch or gain some experience in this field. Please guide me with good suggestions.
afaik for freshers it is really tough to get into ML roles in India. There are many pay after placement bootcamps in Data Science. You may try them. In it you will get placement assistance.
So, your's is different case than the target audience this video was made for. If you are employed, and can remain employed, then there is no pressure on you to get a job in AI asap.
In that case you can use the next 1-2 years building your AI profile. You did not mention if you have joined some course or learning on your own. People often tend to loose focus, or get lost in the ocean of learning material available online when they prepare on their own. So if not already, I will suggest a long term course, just for the structured learning it provides.
Since you are from mechanical background, see if you can merge these two disciplines. As in, if you can find use cases for ML in the mechanical engineering work that you have been doing.
This could show continuity in your profile.
You can even apply ML in stock market. It's a long and tough journey, but worth it, if you have the appetite for it. All the best.
Superb analysis... accept my gratitude regards fraz
Can anyone summarize the video ?
I would love to learn more about the steps I should take to get a job in GenAI!
DSA required?
No, not a mandatory skill for 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.
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..
Thanks.
The first step should be learning basic python. And of course you should have interest in this field.
But I don't have laptop for doing and practicing python 😢
You will need a laptop. It does have to be high spec, as services like google colab, kaggle allow you to practice online for free
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!
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.
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.
I am a gen ai engineer having 2 years of experience but its worth to learn ML, DL so youll know the fundamentals and then its so easy to learn
are you on X?
@021biomedical yes
@@hydrochloricgrip4464 username?
@@PrasanakumarK-c1e yeah best choice.
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.
sir,
please elaborate it.
Presently I am doing PGDiploma in AI from CDAC.
I wanna learn this skill.
Guide.
More details are coming in future videos.
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
@@TowardsAGICan you make a video on agentic ai and how can we start learning 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'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.
Very intelligent and precise. Thanks Satish for you wonderful advice
Thanks! Glad you found it helpful.
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
Such a gold advice on the entire internet. Thanks a lot.
Thanks Shankar!
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.
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.
ML is very important it's a pillar in AI domain, even for gen ai position interviewer ask ML model workflow and evaluation Matrices.
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.
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 UA-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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.
Explained well what really works and needed to the IT market
Thanks
Eye opening❤❤❤.. Very informative❤❤❤
Thanks for watching! 🙏
Thanks Sir for the great advice. I can understand the depth of your advice.
Glad you found it insightful.
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.
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?
There is nothing to admit bro. It was just that our definition of a genai expert was differed.
To answer your questions:
" 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? "
Not really. It's not same as just using chatgpt via an api. Buling genai apps over say openai's API require multiple other skills like effective prompt engineering, basic or advanced RAG techniques, third party frameworks like langchain, lammaindex, langraph, autogpt, crewai, agents and agentic system.
Partial or full fine tuning is not that common, but sometimes becomes necessary depending the use-case.
And of course some frontend-backend skills as well.
Understanding of AI model helps in certain scenario but is not must in most case. On the other end of spectrum, people are building genai apps using no-code tools as well.
@@TowardsAGI Got it. Thanks
Yes, I need the video of how to get into Generative AI and what are the projects I can do and showcase as Gen AI engineer on LinkedIn guidance video
The GenAI playlist is coming soon!
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.
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.
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.
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 UA-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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
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 UA-cam videos in which they are saying that web3 and blockchain are dead and it was all hype??
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.
Appreciate your thoughts, intrested in getting a in AI. Please post the video what your are saying, waiting for that..
Will do so. Thanks
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
Thanks You have given me a good solution for my confusion. Please suggest some book
Thanks. I will have to look at books
Very nice video, you deserve more views and subs
Glad you found the video helpful! 😊
Thanks for the clarity
I'm glad you found it helpful! 😊
Don't be mislead the peoples. There are lot of peoples are giving shortcut path for mastering in AI. I have done M.Tech in Artificial Intelligence and Machine Learning, As of my experience, Freshers could start learning AI from ML. Because everything will come and go, but fundamentals always remain as it is. Linear Regression is the best example of this. Make fundamentals strong and then jump to other things in AI. This video is totally misleading for peoples.
True there is so so much oversupply for data science and Al jobs.
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.
Thank you sir for these insights
Glad you found the video helpful.
Ironically, my friend got job in Paytm as Machine Learning Engineer.
Super informative 👍
Glad you found it helpful! 🙏
For a change someone speaks so much logic and sense
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.
Is there any job in India for which there is no oversupply ??❤
ML jobs have oversupply but it is less compared to the oversupply compared other jobs and more compared to oversupply in other software roles.❤
Software is a dynamic fieldand even the most in demand field will get saturated very soon, one has to begin somewhere ,get your foot in the door and keep learning.❤
Business Analytics is taking over almost all managerial roles slowly ,even HR, Mktg, Sales and Finance with Fintech ❤
❤❤❤❤❤❤❤❤❤❤❤
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.
Passed out from 10th grade
But I want to be a data scientist
If I will be
As a data scientist i m convinced that learning machine learning is à must !
Sorry but i dont agree with you😮😊
Very practical advice for beginners
I'm glad you found it helpful!
I am doing iitm data science and machine learning
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.
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.
very informative sir..
Thanks, I'm glad you found it insightful!
Am learning machine Learning, Deep Learning with Pytorch and Doing my computer Science Degree at the same time. Am also a Backend Engineer. Am a G man real Sigma🤣😂🤣😂🤣😂🤣😂
Please do that video on Gen Ai job thing 😊
In the works. 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
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.
You don't know what you are telling.
Just want to reduce competition.
I have one word for you. LOL!
waiting for next video
Thanks, will be out soon
sir please make a video on genai
In the works, will be out soon.
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 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.