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Why Do You Need to Learn Machine Learning in Cloud? And Why IIT Madras?

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24th Oct, 2019
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Why Do You Need to Learn Machine Learning in Cloud? And Why IIT Madras?

If you think training computers and machines to think and reason like humans was the limit, think again. Scientists and researchers continue to push the edges of what is possible. This constant experimentation and ingenuity have resulted in the birth of machine learning, a subset of artificial intelligence.

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Machine learning is the process of designing algorithms that have self-learning capabilities. This means once the algorithm is trained on a particular set of data, it will be able to make accurate predictions and deductions on the basis of previously presented data- much like humans make decisions.

As one can deduce this is a highly complex, innovative, and challenging field. Scientists have just begun to scrape its surface and implement its usefulness. The latest step in that direction is taking machine learning to the cloud. This field is still in its nascent stage but promises huge potential. upGrad recognizes it and thus, in collaboration with IIT-Madras, has launched the ML in Cloud program.

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Why ML in Cloud Program

As we ran and connected with students in our previous ML courses, we came to realize a big gap. 

Students worldwide were learning and gearing up to be ML professionals. They were learning about supervised and unsupervised learning, introducing themselves to statistics, sharpening their programming, and understanding maths at a deeper level than before. In the end, they were emerging as knowledge, skilled, and eager ML professionals who truly understood this field. They then took their skills to the workplace, where their challenges started. And the fundamental challenge, we realized, was common amongst all students.

This challenge was of scaling. Companies started ML and AI projects, but once they took off and needed more expensive hardware and software, the companies put on their brakes. They started looking for ways to cut down and compromise with how much ML was needed – reaching complete disuse in some cases. These limited the professionals’ ability to implement the full scope of their knowledge and bring true value to the company.

And yet, companies needed ML. They still do and will do so in the foreseeable future as well. Where was a middle ground to be found? It was to be found high up where no one had initially thought to look: on the cloud.

What this program offers

The ML in Cloud program allows individuals the opportunity to become any company’s end-to-end packaged ML solution. With this program, not only will you become well-versed in ML, but then also solve any organization’s critical need for scaling up the ML capabilities. When the time arrives for this, an ML in Cloud student will know the how and what of making this transition. Even if they aren’t involved with the nuts and bolts of everyday operations, they’ll be able to guide their teams well because they are adequately equipped with the right knowledge.

Here are the skills you will be becoming fluent in:


The core and necessary languages that you’ll be working in are Python and SQL since the former is required for ML and the latter for the Cloud.

Machine learning concepts

From basic to advanced, you’ll be learning it all. This includes applying the appropriate ML algorithm to categorize unknown data or make predictions about it. Also included is the ability to modify and craft algorithms of your own should and when the need arises.

Foundations of Cloud and Hadoop

Knowledge about Hadoop, Hive, and HDFS is essential and will be covered. As will be the implementation of ML algorithms in the cloud on Spark/ PySpark (AWS/ Azure/ GCP).

Overall, the curriculum is designed so that students learn the local Python implementation as well as the cloud PySpark implementation of classical machine learning algorithms. What you won’t become is a Cloud expert or a Hadoop expert since in this course we are only exploring the Cloud relative to ML. If you would like to gain proficiency in Cloud as well, you can check out more upGrad programs here.

Who this program is for

We carried out extensive research when crafting this online program. We spoke to industry experts, upGrad alumni, and carried out competitor research to understand the overall market landscape.

As a result, we’ve realized that the ML in Cloud is the ideal program for the following people:

  • Data analysts/business analysts/cloud engineers with at least 1-2 years of experience and an undergraduate engineering degree.
  • Software engineers/application developers/product managers with 4-12 years of experience and an undergraduate computer science degree.

Either of the following skillsets is needed:

  • Proficiency in data visualization. Mid proficiency in R/SQL/Python. Deep knowledge of an industry or business function.
  • Proficient in C, C++, Java, Python. Knowledge of OOP, Agile methodology, and databases.

The following groups will not benefit from this program at all:

  • Graduates in fields outside of engineering, statistics, and engineering
  • Recent graduates from any field with less than 1 year of experience
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Wrapping up

Thus, for the right ones, the ML in Cloud program is a one-of-a-kind program. It will help professionals working in large enterprises to adequately and satisfactorily meet the ML needs of their organization. upGrad will bring its experience in teaching whereas IIT-Madras will bring its long history of academic excellence delivered in a practical and hands-on way. After putting your best foot forward in this program, you can rightfully expect to soar in your career as an ML Cloud engineer. What are you waiting for now? Doors are open!

If you are interested to learn about cloud computing and Machine learning, upGrad in collaboration with IIIT- Bangalore, has launched the Master of Science in Machine Learning & AI. The course will equip you with the necessary skills for this role: maths, data wrangling, statistics, programming, cloud-related skills, as well as ready you for getting the job of your dreams.



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