Wish to build your career in Data Science and Artificial Intelligence space? Here is a video with the best advice from subject matter experts. Listen to these data scientists share tips on how to crack a data science interview or an artificial intelligence interview along with advice on how to make a career transition into AI, Machine Learning and Data Science. You will also find tips on how to build an effective resume. 0:33 AI Career Advice from Swiggy Data Scientist 2:12 Data Science Career Advice from Youplus Data Scientist 3:35 Data Science Career Advice from Flipkart Data Scientist 4:38 DS and AI Career Advice from K-Mart Data Scientist 6:09 Data Science Career Advice from Walmart Labs Data Scientist Subscribe to our channel to get updates on the latest videos. Hit the subscribe button now! http://bit.ly/36DfiCy Who is data science for? http://bit.ly/33M0a2T What are the required skills for data science? http://bit.ly/2qnTFFY What does Machine Learning Engineer do? http://bit.ly/2Yeewry Who are we? Springboard is an online learning platform that helps you master in-demand skills through a personal 1:1 mentor-led model and a project-driven curriculum. Over the last 6+ years, we have served 10K+ learners in 100+ countries. We are now in India and are offering Career Track programs in Data Science, Data Analytics and AI/ML along with job guarantee. Apply here: http://bit.ly/34JJt9D For more information, please write to us at india@springboard.com or call us at +91 8098866488 or +91 7483024694 Follow Springboard: Facebook: https://www.facebook.com/springboardind/ LinkedIn: https://www.linkedin.com/company/spri Twitter: https://twitter.com/springboard_ind Medium: https://medium.com/@springboard_ind #DataScience #ArtificialIntelligence #MachineLearning #DataScienceCareer#DataScienceJobs #ArtificialIntelligenceCareer #MachineLearningCareer #CareerAdvice If you want to start AI tomorrow there are three things I would say that you should have. One is figuring out what kind of learning do you like? Do you like to learn from a book or do you like watching videos? I like watching videos. When you’re watching videos are you taking notes? Those kinda things, figure out your learning curve, how are you going to do that. Second thing is, find more friends. You can find people in the forums, you can talk to them and see and have this kind of a community wherein you can go to; you can go to data science meetups and meet people who are also the same, following the same paths, struggling to learn, etc. Then the third thing is, you’re having people who have already gone through this. Have some mentors. I think that really helps a lot. Talking to them will make a lot more sense to you; you would also know where you’re going wrong and you can also say that this is the path I want to learn. There is going to be a lot of clarity which you’re going to get. And the fourth thing that I am going to say is this – Do not get stuck in theory. It has to be hands-on. Unless and until you run your first model, understand and run your first model, it’s ok even if it’s a blackbox, just run it. Even if you don’t understand python, just run it. Download a notebook and just run it on a Google Collab or whatever it is, but just run it. It’s OK. Be more hands-on. Only then you’ll learn a lot more. So, 3 things: Figure out the course, whatever you want to do; have a support structure of friends, forums, etc have couple of mentors or a mentor who is going to help you out and the fourth thing, Be HandsOn, do more projects. I would say that breaking into data science is just equivalent to breaking into software engineering for someone who does not have that kind of background. To split it down into atomic parts, I would say that you need to be passionate about that field, you need to get a strong hold of the basics, basic technical skills that you require for that field. Apart from that you should probably choose an industry in which you have an inherent interest. For example if you’re interested in Finance, you should look for roles in the financial industry as a data scientist. And apart from that you should have a knack of augmenting your knowledge regularly because it is an ever evolving field so everyday you have new research papers being published, the amazing research that is happening in the AI and the community. And there a new tools that you get to use for implementing your solutions. You should have that sort of curiosity and that sort of drive in you to learn something new each day and keep augmenting your knowledge. If you feel you identify with this kind of a skill set you’re on the right path of transitioning into data science. The thing people still have confusion that anyone can be a data scientist or not. So I will say anyone can be a data scientist. Even I'm mentoring one student, he has absolutely no background of maths and coding and he is doing fine, very good in the data science track.