A Journey From Fresher to Data Scientist- Sai Dinesh

Is transitioning from having no technical background to becoming a successful data scientist at a renowned company a highly challenging journey that demands exceptional determination and continuous guidance? Or does it underscore the power of ambition, particularly when coupled with the right mentorship and support?

Is it possible for Freshers to establish a foothold in the Data Science field?

Freshers aiming to enter the ever-evolving realm of data science should commence their journey by strategically balancing fundamental learning and hands-on experience. Creating a collection of personal projects or engaging in internships can offer valuable practical exposure. By merging theoretical understanding with real-world application and adopting a proactive approach to skill development, newcomers can open the pathways to a bright future in data science.

Introducing Sai Dinesh, a 2020 mechanical engineering graduate who was first introduced to the world of machine learning during his final year of studies. Given the rapid advancements in technology, he decided to enrol in a DataMites Data Science Course to explore and master the evolving landscape of cutting-edge technologies and later he successfully joined as a Junior Data Scientist in the ExamRoom.AI. His journey towards becoming a data scientist is remarkable and offers a beacon of hope that can serve as a guiding light for others.

We had the opportunity to sit down with Santhosh and explore his transition into a data science career, guided by DataMites. Let’s get a glimpse into his captivating journey!

Q- Dinesh could you explain your Profile, where you started, what inspired you to think about a career in Data science, and how you pursue your learning?

A- I am a batch of 2020 mechanical graduates and during my final year of engineering I was introduced to machine learning because the curriculum was changed and we were getting introduced to new technologies additionally we have a crash course in machine learning through our college and that was the initiation of machine learning in my life because until then I didn’t know what is machine learning or anything about data science. So, post-completion of my course, I joined DataMites for training in data science course and completed my certification from DataMites as a Data Scientist, I am also doing my certification and written the exam for AI Expert as well. The curriculum which was provided by DataMites helped me through my journey from being a mechanical engineer to entering the field of data science.

Q- Why do you think the majority of data scientists are coming from Mechanical background? What is your Motive?

A- I love to play with technology and therefore my love towards machines became the reason for choosing mechanical engineering. Machines are tangible and scalable which helps in solving the problems of the real world. When I joined the course of DataMites Data Science Course, I completely shifted from tangible to intangible solutions and additionally, the mechanical domain in AI is quite high and valuable. 

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Q- Did you have any programming skills before you started your journey towards data science?

A- As such I do not have any experience but I have done my crash course during my final mechanical year which introduced me to programming which felt a bit difficult because usually in mechanical we use software but there was a little bit of difference between Python and hands which I used to do like Matlab. It was the initiation of Python during my bachelor’s and Post when I joined DataMites, I was been taught from scratch. 

Q- How do you feel, Is it difficult to learn Python being a non-programmer?

A- Yeah, when we got introduced during my bachelor’s day it was high-level language and later I came to know it can be learnt very quickly it doesn’t take that much time and yeah it surely needs frequent practice to be consistent in that. So It was not difficult but easy.

Q- How many hours did you spend per day and how long it took you to hand on Python for Data Science?

A- Initially, I used to go around coding for 2 to 3 hours per day but then the challenges I faced, first of all, I started from scratch from Python concept to concept and I got caught into a project and then whichever problems I faced I tried to debug them wherever it occurred that created more curiosity in me to learn the significance of Python.

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Q- How many months it take you to be comfortable with Python?

A- A month and a half.

Q- Do you think thermodynamics helps mechanical engineers to get the hang of maths better, is it something that helped you?

A- To be honest, it helped me understand the concepts where to need more maths. If you consider, deep learning, the algorithms which happen and the calculation within the algorithm, we need strong math to understand. So yeah, I got a little help from my technical side. 

Q- How long does it take to get a hang of machine learning while learning with DatMites?

A- It was easy for me to grasp the concept of machine learning, so I took only one month to fully understand it.

Q- What kind of projects you have done while learning data science learning projects?

• The projects I have taken were NBA  
• NBR which belongs to the spoke sector 
• time-series projects 
• handwritten digits which was a deep-learning project 
• Heart disease prediction from a medical background 

Q- When did you start applying for Jobs?

A- I finished my certification in data science then I became more interested in diving deep into the concepts of deep learning because I was eager to know what is happening with the data and why the algorithms perform at such skills to simply the task. Post my certification I was assisted by the placement assistance team from DataMites. As soon as my certification was over I was bombarded with lots of Job opportunities. My first job was through pad services and later I started applying for jobs through LinkedIn.

Q- What was the first job you got after completing your data science course?

A- I got my first job as a Junior Data Scientist in ExamRoom.AI.

Q- What is your experience and how many interviews did you attend before you got into your first and second Jobs?

A- I have attended 4 to 5 interviews before landing on ExamRoom.AI company.

Q- What type of questions you faced during the interview after learning data science and AI?

A- I was asked basics of Python and its data structures then I was asked about machine learning and depending on the job description they might ask you concepts of deep learning and algorithms. They also ask regularization, underfitting and overfitting kinds of questions. Moreover, they also ask about the projects we have mentioned in the resume.

Q- How deep do they go into machine learning concepts, what kind of questions do you get in machine learning? 

A- They ask situational-based questions, suppose you are given some kind of data so being a machine learning engineer how would you think what is your thought process or what is your approach to the problem?

Regarding the machine learning part, they ask about the difference between linear regression and logistic regression because both have regression but the task they are doing is the right opposite -One is going for numerical data and the other is for classification.

Q- What is your average interview time?

A- Typically it lasts up to 1 hour and 15 minutes.

Q- What are your learning from your failed interviews?

A- Every failure is a step towards success because once you fail what kind of questions you couldn’t face in the interview in real-time because there is no documented way to questions which interviewer may ask. At some point in time, after a few failures, you get to know which concepts to focus more on and tackle the questions in a better way.

Q- What are the areas you would review after your first interviews?

A-Basics of Python 

Q- What is your general message for non-IT background who comes from metallurgy, civil and mostly mechanical?

A- My message is simple, if you have an interest you can do it there is no difficulty in it.

Watch the complete interview here

End Note

Sai Dinesh’s story highlights a significant reality: entering the field of data science as a novice is more attainable than one might think. His journey serves as a prime example of how determination, when complemented by proper guidance, can yield remarkable results.

With its all-encompassing training, steadfast mentorship, and robust resources for addressing queries, DataMites stands as the foremost global institution for empowering individuals in the domains of data science, machine learning, Python, artificial intelligence, and data analytics, enabling them to surpass constraints and achieve their goals. DataMites online data science courses and in-person data science training conducted in Bangalore, Chennai, Pune, Hyderabad, Mumbai, and Ahmedabad. His acquisition of the IABAC Certification via DataMites not only enhanced his credibility but also unlocked thrilling prospects for him.