Mission Python -tete-a-tete with Ivy’s successful Alumni



  • Python is used by the Fortune Global 500 companies for a multitude of tasks in computer science.
  • “Python is also easy for beginners to use and learn”- Pyorg
  • Three out of four data professionals recommend that aspiring data scientists learn Python first.
  • A LinkedIn report lists Machine learning engineer and Data Scientist among the emerging job roles in the ‘Emerging Jobs’ list.
  • TIOBE ranked Python as programming language of the year 2018!


Experts frequently credit the easy learning curve of Python to its flexibility, readability and its robust set of libraries which makes it a go to coding language for so many tasks

A snippet from the Python Developers Survey 2018 conducted by the Python Software Foundation which reveals the varied tasks developers use Python for.


Assertions are great but may not tell the entire story. So, we decided to ask our alumni for their day-to-day story.


We receive a lot of query from students from different backgrounds who are enthusiastic about learning various new languages like Python but are in dilemma to take the first step.


Are you planning for a career change too?


You are not alone. Meet our alumni Akash Sacheti, an Assistant Manager at Genpact, he switched to Data Analytics after 8years as a Jewellery Marketer! An extremely dedicated student, he learnt Python to be a “complete Data Scientist”. In his words … “Python is not too tough, I find it similar to R.” He credits Ivy for landing a job “Being from a non-engineering background, I got this job because I learned so much from IVY”


Our take: Its increasingly becoming important to keep learning and upskilling yourself. By 2020 the number of Data Science and Analytics job listings is projected to grow by nearly 364,000 listings to approximately 2 mln in the US alone. If you are willing to take the plunge our mentors at Ivy are with you to guide you to help you traverse through this path.


As a Data science professional should you learn R or Python?


Python & R are the two most popular programming tools for data science right now.

Arkit Sen, a Jr Analyst in Cognizant, Mumbai tells us his story. “In 2016 I initially started learning R and other concepts. Meanwhile I realized Statistics was a very important part of it. I had started from scratch. Things started getting too difficult or rather I lost my way into it gradually. This was the time when I attended some seminars from different institutes, Ivy being one of them. I somehow found the content and instructors at Ivy to be of my type. Transparent, adequate and to the point. Also, I had the need to train myself to industry standards, to land an appropriate job. Python was an important alternative to R that many companies demanded and I felt the need to know it. At Ivy, Python was taught from the very basic, along with Neural Network basics and other necessary packages.”


Our take: Python is a powerful and versatile language. Even on someone from a non-programming background, Python is kind.

Just like Python, R is also an open source programming environment specifically designed for statistical computing & data analysis and is entrusted by academicians and industries alike. To gain a better understanding of “Data Science with R” check out this webinar.

The Python vs R debate confines you to one programming language. The reality is that learning both tools and using them for their respective strengths can only improve you as a data scientist. Look beyond the debate and embrace both tools for their respective strengths.



Our alumni take on if a prior programming knowledge is essential or not so much? 


Arkit helps us in understanding if a prior programming background helps in picking up Python faster.

“As I was from Computer Science, prior programming knowledge surely helped a bit. But that being said the instructor took into account that none of us had any prior programming exposure and tried to break down each and every step. It was easy as far as each one of us devoted adequate time and effort to what was taught.”


Our take: Even if you are completely new to coding you can always learn Python. At Ivy we believe in making every student industry ready and have designed the modules with utmost care and structured it according to industry standards even for someone who is new to programming. Read this blog to get an understanding of how to get started!


Is Upskilling myth or truth?


To that Riturai Bhattacharyya, an associate at Cognizant, a passionate coder says that Upskilling has really helped her. “I have assisted my project people in some of the cases.”


Arkit credits his SAS certificate to the knowledge he gathered at Ivy. “My SAS Certification got a tad easier to crack as I had prior knowledge.”

They say a Data professional is known by the knowledge of his tools. “Also having R knowledge helped me resolve many cases. VBA, Excel that I learned at Ivy always keeps me ahead in the race. Slicing and dicing the data to have a prior look before putting it to use becomes quite important. Also an automated tracker report for the project is something my manager loves to have.”…..Arkit tells us.


And all said and done… in the end it is all about passion.


For Riturai , it was her passion for coding that drew her to the Data Science and Machine Learning Certification course. “I am an IT professional and have knowledge and experience of programming languages. From industry perspective, machine learning is slowly taking over all the existing technologies. Not knowing it will surely push a person backwards by some years. That is what motivated me(to learn Python).”


And that is why at Ivy we believe in each and every student is capable of scaling new heights if they are ready to sweat it out (not literally offcourse! )


The courses at Ivy were adequate and to the point. Easy to grasp and understand. Case Studies assigned were industry standard and adding them to the resume gave weightage.Extra assignments and case studies were provided in cases students needed some more practice.”-Arkit


“A very good place to kick start the journey into the analytics world. I have already started recommending it.”… Riturai signs off.


When we asked them about any experience, tips or tricks to share with our readers/novice coders who are just starting out.


Arkit: “The secret is to never give up. Data Science/Analytics is like an ocean and there is no overnight success. There are numerous algorithms/techniques used in various domains and newer ones finding place with each passing day. It’s a continuous learning process. However to start out, knowledge of a Regression, a Classification and a Clustering algorithm; Time series and implementation of these in R/Python would be good. Excel being an important skillset and one is good to go. Good Luck!”


Akash :Pay complete attention in class, Do assignments and case studies timely , even after completion of course be in touch with all tools and techniques you learned.”


“Success is going to require talented experts, a beginner’s mind, and a long-term orientation.”-Jeff Bezos.


As a Data professional you need to continuously up your game, be in trend with the cutting-edge technologies, latest industry trends because of how quickly the field is evolving. The courses at Ivy Professional School are designed keeping that in mind.

Watch a free tutorial conducted by Ivy Professional School to get an idea of how Python is used in Data Science and Why it is important to make a career in Data Science.

Compiled by Shromona Kahali – Content Strategist, Ivy Pro School


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