Help regarding managing interests

I am a data scientist with 4.5 years of experience and want to transition to software engineering. In DS, we do not code the ways its done in SW roles. Moreover, I am not from CS background. How do I get started on preparing to get into tier 1 companies as SWE / SDE if I want to achieve this in the next 1/1.5 years?

Hey guys, so I have been interning at a company for the past 9 months. They have offered me a ppo and I will most likely accept it. But my interest lies in the ML field or some data fields such as data engineering. Can anyone advice me how do I go about it? Like should go for masters(my undergrad degree is not CS or some pheonix branch). Should I learn on my own and keep giving interview. Or should I take some experience in sde and then switch? Thanks in advanced

Current CTC is 25lpa. 6yrs of experience started as data analyst then as business Analyst. Have been working as machine learning engg for past 2 years in series c funded product based company. My work is mostly related to model scaling, maintainability and reproducibility. Do you think, is lower, on par or more than market rate. (Also if anyone is hiring, I can share more details)

Currently I am in college 3rd year(EEE). Since there aren't really many jobs in EEE. I decided to pursue my carrier in software. So far I have learned full stack development and built some small websites to. Since the internship season is coming I have applied for a lot of postions on various websites but not really getting any replies. So my question is should i continue grinding the full stack devlopment even though competition is at all time high(saw 2000+ applications for 1 intern postion 🤡) and fear of AI(DEVIN) Study AI/Ml since it's the trending topic. But there aren't many postions jn india Learn web3(solana +rust). Many people are telling there is no future in it. But I saw some of my frnds printing money in this tech So senior software enginnering please 🙏 help your fellow junior

I am a python Developer having experience of 7.3 years. In this span I have worked as a Data Engineer with Geospatial data, RestFul API Developer, Away API gateway Integration and development Engineer. Right now since last 1.6 years working as ML engineer (80% software development+ 20% Data science exposure to me, There is Data scientist team for model development). Now I want to switch but confused that should I learn Deep learning in deep and practice in my current project before switch or I should master DSA and UI (React JS) and switch as SDE or Lead position. Adding to my tech stack, I have good knowledge to work with AWS, and Azure and using python SDKs for both. Beginner/Good experience with Docker kubernetes as well. Please suggest me so that I can make a choice to switch my company and get place in a Good org with good payment and work culture. Thanks in advance.

Hi, I am a software engineer with 12 years of experience. I need some suggestions. 1: Is it too late now to learn Data Science and pursue a career in it? 2: If I want to learn the necessary concepts of ML what path I should follow? 3: I find the maths behind the ML models a bit confusing can anyone please suggest any good resource for that?

I'm a mobile app developer with 6+ years of experience. I don't have much interest in data analysis/engineering/management related fields, neither do creating ML models excite me. But with everything being integrated with AI/ML these days... I feel a FOMO - should I switch fields in order to remain relevant?

I have been working on Backend development with NodeJs & ExpressJs with databases like Mysql, pg, redis and rabbitmq and some parts of devops like k8s, gcp etc. for the last 3 years. Before that I was working as a C# developer for 2 years. Now I want to learn something challenging. I am done with creating websites and normal stuff. People are recommending different things like Golang, Rust, Ruby on Rails, Elixir or anything else. I want to get a global remote job next year. So what should I work on so that I can work accordingly. The competition shouldn't be that much and side projects should be enough to get a good job. Or give a good roadmap.