Global AI and Data Science

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  • 1.  Career Guidance

    Posted Tue February 18, 2020 03:22 PM
    Hi Guys!!
    I am an aspiring Data Scientist from India.
    I am a B.Tech Graduate in Electronics and Communication.
    I wanted to discussion with all of the respected people here that how should I progress in my career if I want to be a Data Scientist.
    I am unemployed currently. I have completed my certifications on Data Science with Python,Data Analysis and Visualisation using Python.
    So,how should proceed further now so that I can ensure myself a respectable job?
    Kindly send me your thoughts.

    Rahul Dubey


  • 2.  RE: Career Guidance

    Posted Wed February 19, 2020 10:56 AM

    Hi Rahul!

    I would suggest you to start working on real world data science projects. The best possible match for a real world data science problems can be found on or UCI. Try to pick different types of project in order to cover the broader dimensions of the data science. For example, start with a predictive analysis and then move on to a classification problem once you are done with the first one. After completing both types of supervised learning, you should work on an unsupervised learning based project. Once you are done with at least these 3 projects, you are prepared enough to appear for the Data Science interview. The more you work on the projects, the more you will be prepared for a job. Good luck with your job hunt :)

    Shivam Solanki

  • 3.  RE: Career Guidance

    Posted Sun February 23, 2020 05:47 PM
    Edited by System Fri January 20, 2023 04:19 PM

  • 4.  RE: Career Guidance

    Posted Sun March 01, 2020 03:20 PM

    Well said by @Shivam Solanki Given my experience on how I became a Data Scientist, he's got some point you should consider following. 

    In addition to his suggestions, I recommend you take part in Kaggle competitions and showcase them on your git repository so employers can see them.

    Additionally, I will like to point out that most companies nowadays from their models on the cloud. So a bit of cloud computing is highly recommended. What do i mean, i meant being able to deploy your models to productions. Few examples are Wastson Machine learning, WS SageMaker, Google ML

    As you keep building your portfolio do not forget to keep yourself updated with research papers, blog posts...
    I hope this helps. Feel fee to write me if something is not clear. I do not believe in luck so I will say go out there and make it happen. You have got this. 

    Cheers :) 
    Damilola Omifare 

    Damilola Omifare
    Data Scientist

  • 5.  RE: Career Guidance

    Posted Tue March 03, 2020 04:27 PM
    I have to say this is amazing.

    Thanks for your sharing !

    nice topic !

    Caroline Yang