I think depends on your background. If you’ve background in software engineering and have been doing data engineering and understand stats and parameter tuning and approach model like an oops function and do ml ops and evaluation and retraining like ci/cd, I think you can proceed to this role. Very comparable to being a data architect but some understanding of science and engineering is needed. Good discussion.
this is true. Getting into AI is not easy. it needs at least 2 yrs of dedicated effort. it's not like learning a tool or a programming language which you can do in 2-3 months. the aspirant needs to know everything including, cloud, DevOps, ML, DE along with AI, to be successful at his job. companies don't need coders anymore, Gen AI tools can do that efficiently and quickly. so they need people with strong data background.
Coding will start to get more easier but most of that would be generic phrases, the advance level of coding such as time complexity, problem specific approach is something LLM aren't trained. So companies might not require entry level coders, whereas demand for senior coders will stay same where one branch will eventually become AI engineers to prompt, deploy and monitor the LLMs and stay updated with new papers, whereas demand for Data Scientist and ML engineers too will remain consistence to build and deploy customized problem based models.
@@challengemania4447 @views-re2om if you have point, make it. if you differ from my opinion, challenge it. if you don't like my opinion, dislike it. or just scroll on. "are you a fresher?", "are you serious?", "are you a human being?", "are you from a different planet?" what kind of questions are these? you have a valid point in it? you just want to humiliate or insult someone just because you didn't like his opinion? that's shows your level of maturity...
Day by day population is increasing. Educated also increasing. If some is doing AI engineering,may be useful to them to settle in their life at high ends. But my opinion is that they are enhancing unemployment. AI can be used whare the work beyond the capacity of human being. So Al swallow the hope and opportunities of man kind
Hi I am a mother of 4 year old daughter with around 10 years of experience into support and maintenance i.e. consulting job in IT industries...I have completed data science course and trying to get job in the same...but due to my current job and as I am a mom I could not get enough time to brush up and I would have to start again before going for an interview...can you help me with how to brush up things quickly so that I can go for it...any help would be appreciated
This does not sound like a junior role, feels like one has to start from data scientist side or data engineer side, and grow towards AI engineering after working for some years. If one tries to tackle all aspects at the same time from the beginning, the knowledge base would be shallow, and this would not lead to a healthy work life.
what the fuck yaar ! someone says study data science whcih i ave been doing for last two years. but now someone says do this do that , fuck all the influencers . i will study data science no matter what . wether this field exists or not but still . i have given my 1 years now can't stop in between
relax and do what you are doing. He is giving overall expectation to settle in a big company. there are many startups who look for good knowledge and reasonable pay. thats how any new fresher gets into job. but many of those startups does not survive long. if you are skilled person, you will quickly jump to better with the experience gained. if you are mediocre, will continue to sweat alot. you can't be with same energy as the years passing. Hence some poeple prefer all that stress for money may not even worth it, when you are not enjyoing your daily life. Take the video as what it would be over a period of time. Even mainframe guys there and surviving in market, though mainframe market was dead 20 years ago, but you won't expect any comparable salaries in that compared to today market. Its always comes down to Who you are overall? you want to be best earner or just survivor in IT? alternatively stress with high salary (latest stack) vs relaxed life with low salary (old stack)
I have seen good baseline models being built by software engineers who know reasonable data science & machine learning. Many pure data scientists are a liability in many start-ups. MLOps engineers who know enough math & stats with python do a good job with baseline models. Concept & Data drifts are common.
well said. those pure Data Scientist jobs which just makes reports to management may not be there any more. Those roles are actually redundant as you correcctly said, also a representation of unskilled management layer in the company.
I think depends on your background. If you’ve background in software engineering and have been doing data engineering and understand stats and parameter tuning and approach model like an oops function and do ml ops and evaluation and retraining like ci/cd, I think you can proceed to this role. Very comparable to being a data architect but some understanding of science and engineering is needed. Good discussion.
this is true. Getting into AI is not easy. it needs at least 2 yrs of dedicated effort. it's not like learning a tool or a programming language which you can do in 2-3 months. the aspirant needs to know everything including, cloud, DevOps, ML, DE along with AI, to be successful at his job. companies don't need coders anymore, Gen AI tools can do that efficiently and quickly. so they need people with strong data background.
Are you a fresher bro ?
companies don't need coders anymore, - lol are you serious?
@@views-re2om yes its serious . Your comment is a joke
Coding will start to get more easier but most of that would be generic phrases, the advance level of coding such as time complexity, problem specific approach is something LLM aren't trained. So companies might not require entry level coders, whereas demand for senior coders will stay same where one branch will eventually become AI engineers to prompt, deploy and monitor the LLMs and stay updated with new papers, whereas demand for Data Scientist and ML engineers too will remain consistence to build and deploy customized problem based models.
@@challengemania4447 @views-re2om if you have point, make it. if you differ from my opinion, challenge it. if you don't like my opinion, dislike it. or just scroll on. "are you a fresher?", "are you serious?", "are you a human being?", "are you from a different planet?" what kind of questions are these? you have a valid point in it? you just want to humiliate or insult someone just because you didn't like his opinion? that's shows your level of maturity...
Hi I had a general question what’s the difference between AI engineer vs data scientist?
Interesting point of view. All the best insh'Allah
How a fresher can be a AI engineer? Please share the roadmap along with how to apply and get the job?
Day by day population is increasing. Educated also increasing. If some is doing AI engineering,may be useful to them to settle in their life at high ends. But my opinion is that they are enhancing unemployment.
AI can be used whare the work beyond the capacity of human being. So Al swallow the hope and opportunities of man kind
Pls don't get me wrong .... I fear very soon the internal clash may happen..
Do Java and microservies developer with more than 15 years needs to shift AI anx ML
Hi I am a mother of 4 year old daughter with around 10 years of experience into support and maintenance i.e. consulting job in IT industries...I have completed data science course and trying to get job in the same...but due to my current job and as I am a mom I could not get enough time to brush up and I would have to start again before going for an interview...can you help me with how to brush up things quickly so that I can go for it...any help would be appreciated
Very Interesting video, that prepares anyone who wants to be an AI Engineer.
This does not sound like a junior role, feels like one has to start from data scientist side or data engineer side, and grow towards AI engineering after working for some years. If one tries to tackle all aspects at the same time from the beginning, the knowledge base would be shallow, and this would not lead to a healthy work life.
It's not a junior role. You need to spin multiple plates.
Hi sir,
Can u pls tell me about MLOps job role. And do we have MLOps job market better in future??
MLops has intersection with Data engineer and Data Science roles. It has good demand
is MLOPS engineer next role is AI engineer..?
I think both are kind of mixed, just new terms.
what the fuck yaar ! someone says study data science whcih i ave been doing for last two years. but now someone says do this do that , fuck all the influencers . i will study data science no matter what . wether this field exists or not but still . i have given my 1 years now can't stop in between
:D
relax and do what you are doing. He is giving overall expectation to settle in a big company. there are many startups who look for good knowledge and reasonable pay. thats how any new fresher gets into job. but many of those startups does not survive long. if you are skilled person, you will quickly jump to better with the experience gained. if you are mediocre, will continue to sweat alot. you can't be with same energy as the years passing. Hence some poeple prefer all that stress for money may not even worth it, when you are not enjyoing your daily life. Take the video as what it would be over a period of time. Even mainframe guys there and surviving in market, though mainframe market was dead 20 years ago, but you won't expect any comparable salaries in that compared to today market. Its always comes down to Who you are overall? you want to be best earner or just survivor in IT? alternatively stress with high salary (latest stack) vs relaxed life with low salary (old stack)
I have seen good baseline models being built by software engineers who know reasonable data science & machine learning.
Many pure data scientists are a liability in many start-ups.
MLOps engineers who know enough math & stats with python do a good job with baseline models.
Concept & Data drifts are common.
I can correlate..
well said. those pure Data Scientist jobs which just makes reports to management may not be there any more. Those roles are actually redundant as you correcctly said, also a representation of unskilled management layer in the company.
well said!!
Good awareness