Career Guidelines

Namaskar I am Kushal from learnvern.

Today we will talk about careers. Just now you have finished this course and after completing the course I believe there will be a lot of expectations in your mind and you must be hoping that this course will help me further in my professional journey and in my career. 

So I will just tell you, that if you are a fresh graduate and you have just completed your education and if you are searching for a job then you should look out for ML engineer or data scientist or junior data scientist, so these type of job roles you should search for and apply for.

Now when you watch for job roles then I will recommend that as soon as you see the email or on any portal you see an opening for a job , then you should always read the job description because in the job description you will be able to see what their actual job expectations are.

So here you will understand that in machine learning there are lot of topics and lot of domains which we have covered in our course also and out of that some areas they would have highlighted, either they would have given some libraries of python along with python or they would have given different approaches to machine learning and along with that they would have written EDA or data wrangling meaning that this complete area is of machine learning but along with this you will be able to see some more things like if they want linux platform so they must have written something like ubuntu(ub-antu) , fedora( fe- dora) red hat, something like this and if they want data visualization also then they would have listed some data visualization tools like tableau (table -u) or power BI and apart from this if they want ETL then they would have mentioned ETL also where we get help from data migration tools to migrate data and that would also have been mentioned or they would have mentioned databases and data warehouses also so, what I mean to say here is that when you see job role then that is not a only based upon a programming language or just one concept because that is a job role and there you have a demand for multiple technologies and multiple skill sets so because of this you need not bother and whatever you know among that you have to just brush up those topics more and apply for that job and give a nice interview.

Now we will talk about people who are experienced, those who have three to five years of experience , for you people also senior software developer in machine learning or machine learning engineer , data scientist and apart from this computer vision engineer or one thing more can qualify for you like computer engineer and so these type of job titles that you see, then you should again go to its job description and see if it matches your skill set or not and now those who are far more experienced meaning those who have five years of experience, seven years of experience , ten years of experience, fifteen years of experience so for you my recommendation is that you already have an enriching experience like for different products, services, like different software services that you would have worked upon , for that you must be having experience and along with this experience of yours this machine learning course is cherry on the top and along with this I will surely recommend you to develop some POCs to even broader your understanding and based upon your past experiences and best practices you must try and amalgamate this knowledge and try to develop it and I will recommend that you should apply for senior data scientist, solution architect and data engineering or for machine learning and if you have experience of fifteen years or ten years then you can apply for Director of analytics, director of data science and there are vice president positions also in companies and you can apply for that also.

So this I have told you level wise, that this course will help you in each level ,so now I will tell you some combinations , see when there is some work in a company and the complete project architecture if you understand , so in project architecture, data engineering, big data, data analytics visualization and business reporting , so all these things are associated with machine learning and in the complete pipeline and complete architecture all these things they come and so along with this to enhance your learning and enrich your learning more you can also opt for data visualization and business reporting courses also with machine learning and in this you can learn power BI and tableau or you can do strongly visualizations with python if you have a software development or programming background.

Now another aspect I will tell you that today the machine learning that we are applying works automatically with data that is very huge and from vivid sources and in various formats , so here you must have understood that I am talking about big data and big data analytics ,so to enhance your learning experience in depth and to know how you apply machine learning distribution models and how data analytics can be done, for this you can learn tools that come with big data like apache hadoop, apache spark , you can learn data migrations, ETL and also learn NOSQL database, so this skill set will help you to learn to handle big data along with machine learning and how to process it and how it will be amalgamated. So this will be a very enriching experience for you.

So these were some courses and these were some tools that I told you and you can learn which will help you a lot in your complete journey and so once again I congratulate you for this wonderful journey and I hope that all this knowledge you will be able to apply in your professional career.Thank you very much.