I have actually often been shortlisted as the operator science faculty in India and similarly DR. Base is again a leading credit academician in stats and data science comes with several decades of experience the reason why our curriculum really stays industry-relevant and why we're able to attract such high-quality industry is also because of industry advisers and some of our key industry advisers include very well-known names such as doctors a janitor who is one of the machine learning leaders in the IBM Watson project globally we also have my Yucat√°n who is the chief data scientist at Flipkart as one of our industry devices for the program.

Of course, we're also Ola Zambia who is who was formerly heading machine learning and AI, so we invite a lot of industry professionals to come and deliver in our classroom sessions specific courses and again we invite industry professionals or industry experts across a force or variety of companies or financial services technology companies data science companies such as mu sigma and so on and the common unique feedback that we get always is that this adds to the learning experience because now you know part spins are better able to understand persons actually lead on to failure opportunities with all of these folks when they come and lecture in the classroom you know one of the ideal motives to them this is basically the spot talent.

So having known all of this you know how can you decide whether this is the right program for you well we have created certain rubrics on this so you know we know this is our first data and looking at data from alumni who are the ones who are likely to do well in this program so in terms of who should pursue this course first and foremost if you are a technology professional then you are a good fit for the program if you want to progress to machine learning goals alternatively if you're just star tinging in big data or data fence role but have no understanding of machine learning because all you know all of data science is actually moving towards machine learning plus a lot of applications on Big Data is happening via machine.

It's only a matter of time in fact already the industry is moving in this direction so if you are working on the Big Data engineering side or the data side then machine learning is a natural logical progression for you in terms of skills that you need to add lastly you should pursue this course only and only if you are looking for the rigorous meaningful program that is going to teach you by making you do a lot of stuff right so it is not a passive learning experience at all one way you can just look at videos and hope that you learned but this is an extremely immersive learning experience wherein you will learn through some of the best faculty in the country and the industry plus you will also be required to apply your learnings through different projects and different hands-on assignments a corollary - this is who should not pursue this course well.

If you are not from a background in technology and you don't intend to be and then I don't think this is the right program for you because machine learning you know careers will need you to to take a deep dive in technology to essentially to do programming right you will have to like code it Python and if those are not failures if you have any background on or and either you want to have that background then then this will be a tough course for you to navigate if you're looking only for something that is at at 10,000 feet level and you basically just want to speak the language without really completely committing to knowing or understanding it completely then again this programs going to be an open fields and third part is that you're just looking to learn a tool such as Python or someone or - you know one or two techniques in this together and get a quick way to get a certification you will be disappointed because the program actually has very rigid evaluation criteria and that is one of the reasons why it is so respected and then lastly because you know there is a strong quality metric that is maintained with every batch that graduates so essentially no easy way out here you should enroll in the program only and only when you know that you are ready to make that kind of effort and time commitment is their placement assistance in the programs the problem question.

So yes we do have a career services module in the program, and we do a bunch of activities first we do conduct career development workshops wherein we get industry experts to advise and guide and it's on how to build careers in machine learning you know what kind of rows what kind of companies to target how should they be pitching their profiles and so on we also maintain a very active job put in the program because of a large network and recognition in you know analytics and data science machine learning space there's a lot of companies that reach out to us with opportunities the positions they are looking to fill and these are all opportunities that are shared with Andy with alumni, and we see a lot of candidates you know converting these options.

So that that is something that is of immense value peer-to-peer networking finally you are learning in a high quality is good a program where you learn in with a bunch another forty fifty you know top-notch professionals working in some of the best companies the very same companies where you want to work or you know which are looking to hire big numbers in terms of machine learning skills, so we see a lot of you know intro batch referrals happening and and it's you know switching companies like that we also see you know some of these industry professionals who come in and deliberate parts of the program or spend their time in mentoring students actually ending up recruiting shoes now that again is because they get to experience talent firsthand and when they see that here on this island is capable and is well-trained you know they there's other lap it up for their own organizations first over the years these are you know some companies where our alumni work in data science in machine learning roles.

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