Why should you opt for the NMIMS Global Access M.Sc. (AI & ML Ops)?



27 May, 2021

Why should you opt for the NMIMS Global Access M.Sc. (AI & ML Ops)?

We are a privileged generation to live in this era full of technological advancements. Gone are the days when almost everything was done manually, and now we live in the time where a lot of work is taken over by machines, software, and various automatic processes. 

Before having an insight into what are the benefits of pursuing an M.Sc. in AI and ML from NMIMS, it is very important for you to have an understanding of what exactly AI and ML is and why you should go for it, or what are the future benefits of AI and ML which can help you foster your career growth. So let’s start with getting a very basic understanding of what AI and ML is.

What is Artificial Intelligence (AI)?

Intelligence: “Ability to learn, understand and think”

Artificial intelligence or AI is nothing but the science of computers and machines developing intelligence like humans. In this technology, the machines are able to do some of the simple to complex stuff that humans need to do on a regular basis. John McCarthy coined the term ‘Artificial Intelligence’ in the 1950s. He said, ‘Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language, form abstractions, and concepts, solve kinds of problems now reserved for humans, and improve themselves.’

What is Machine Learning (ML)?

Machine learning is a subset of artificial intelligence (AI). Machine learning algorithms allow AI to not only process that data, but to use it to learn and get smarter, without needing any additional programming. With increased data and experience, the results of machine learning are more accurate—much like how humans improve with more practice.

The adaptability of machine learning makes it a great choice in scenarios where the data is always changing, the nature of the request or task is always shifting, or coding a solution would be effectively impossible.

Growing demand of AI and ML

There is no denying the fact that Artificial Intelligence and Machine Learning are influencing every part of the tech industry. AI and ML are everywhere, from the corporate world to gaming stations, and perhaps, more than our regular lives, AI is impacting the business world more.

Tech giants like Facebook and Google have placed huge bets on machine learning, and they are already using this technology in their products.

But this is only the beginning. Businesses have seen a massive unraveling of the AI and ML phenomena as they find the possibilities of their application in various fields. For example, researchers started using Machine Learning to gain insights into the recent global pandemic that brought the world to a standstill. Businesses are already on the patch to create more robust virtual work environments leading to heightened demand for AI and ML professionals.



Data is no longer the new oil, it is now the world’s most essential resource for business profitability and innovation. The immeasurable applications of data have created an insatiable demand for skilled professionals who are proficient in tools that drive automation, maximize insights, create lucidity & more from data; over 1 million Artificial Intelligence professionals will be needed by 2021 globally. NMIMS Global along with INSOFE recently announced the launch of a 24-month Master of Science program in Artificial Intelligence and Machine Learning Operations (MS in AI and ML Ops). MS in AI & ML Ops Program will have a strong focus on comprehensive technical training. This will mold students into becoming more competitive professionals. MS in AI & ML Ops introduced by NMIMS Global emphasizes equipping students with the skills to use data to increase insights, generate lucidity and increase efficiency in the tools that operate automation. The program has been designed to provide working executives with the skills necessary to compete in the rapidly growing market for Data Science professionals. Enterprise in the private and public sectors need executives, analysts, and specialists with advanced training in analytics technology as well as business management. 

  1. Career Assistance: Career assistance is an integral part of the MS in AI & ML Ops program. Students will get access to 500-plus top hiring partners of NMIMS Global & INSOFE along with access to NMIMS Global’s job portal, resume and interview assistance.
  2. Learn In-Demand Skills: You will be able to acquire skills most frequently posted by employers and gain confidence and mastery in the entire AI algorithm development and deployment cycle (understanding business problems to analytical and mathematical problems, data understanding, data preparation, modeling, evaluation, and deployment).
  3. Rigorous and holistic curriculum: It adopts a holistic approach that allows students to apply knowledge via multiple routes such as internal assessment, examination while gaining hands-on experience at a Bootcamp and acquiring in-depth knowledge through a Scholar-guided Masters’ Dissertation. 
  4. Extensive classes: The program offers 750+ learning hours including 220+ teaching hours & 212+ lab hours in a flexible online-blended interactive format specifically designed for working professionals.
  5. Real industry experience: The Dissertation project will cover 200 hours working with complex research-driven data to solve business problems. It allows the student to gain deep technical professional experience by applying the concepts, tools and techniques learned during the program, in developing and implementing machine learning & artificial intelligence solutions.
  6. Gain academic and industry insights from expert faculty: The faculties are best in class, no doubt about that. Some of them work in renowned MNC’s like SAS, Crisil, Capgemini, Microsoft, General Mills and put in many efforts in teaching us the concepts in great detail. The faculty pool consists of over 50+ world-class Products Builders, Researchers, and Consultants Scholars. These are practicing academicians together bring depth in the approach to data science education.
  7. Updated curriculum: The curriculum is up-to-date and gets updated every year from the feedback of industry people and the advisory board. So that is a big plus point that the syllabus and subjects keep getting updated from time to time, and we study the latest technologies and developments in the market. Also, NMIMS has tied up with Virginia Tech University (USA). Every semester a teacher from VT comes and teaches a subject like Statistics, Big Data, and Machine Learning for a week every semester.
  8. Additional certifications and tools used: The course also includes two certifications from SAS, which are an add-on to our Resume. Students will be able to get an understanding of tools like Apache Spark, Hadoop, Python, R, Tableau.
  9. Networking advantage: The batch is a mix of both freshers and experienced people so it’s great collaborating together in various academic projects and presentations.
  10. On-Campus Bootcamp: The five-day residential on-campus Bootcamp will be held in Mumbai and provide a hands-on opportunity to solve real industry problems, and also build and scale prototypes and applications. 

What will you achieve by the end of this program?

By the end of this program, students will be able to:

  • Understand & solve complex machine learning problems with competencies in data mining, regression analysis, text mining, and predictive analysis.
  • Gain confidence and mastery in the entire AI algorithm development and deployment cycle (understanding business problem to analytical and mathematical problem, data understanding, data preparation, modelling, evaluation and deployment).
  • Analyse & solve big data problems using engines like Apache Spark & Hadoop Ecosystem.
  • Get competencies in algorithm development and visualization tools including R, Python & Tableau and specialised advanced machine learning areas such as NLP, Big Data, Robotics & Reinforcement learning.
  • Draw strong computational and application architecture knowledge to deploy and scale AI and ML applications.
  • Obtain hands on experience with industry prototype building and working to apply business and data thinking to complex research problems.

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