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System Engineer to Data Science: Growth Journey

System Engineer to Data Science: Growth Journey

by | Oct 18, 2019 | Career Transitions, Data Science

Career Transition from
System Engineer to Data Science Success Story

You are judged based on practical knowledge, regardless of past experience.

– Ruchi Saboo

Background

Education: B. Engineering in Computer Science

Previous Profile  >>> Current Profile
Company: Amdocs
Profile: SQL, UNIX Developer
(Ordering and Billing)
Designation: System Engineer
Domain: Telecom
Experience: 2 years		 Company: TSystems
Designation: Consultant
Profile: Data Science
Designation: Data Scientist
Domain: Telecom

My journey into Data Science

Why Data Science?

Day by day, the technology is evolving. I didn’t see myself getting the career growth I wanted with the technology I was working on before (SQL/UNIX). As anyone in IT would know, having a job as a System Engineer in SQL/UNIX these days is very mundane. I thought I wouldn’t survive for long. That was the main motivation to keep myself updated with the latest tech.

When it came to choosing the new tech, I found myself being more keen towards Data Science. It’s very interesting and insightful. It called to my intellectual side. It’s like you’re creatively playing with data and getting business results.

Why Dimensionless?

It’s a funny story. When I decided to go with Data Science, I enrolled in a classroom course mainly because I was never comfortable with Online Classes. It was mostly theory and my experience was neutral.
Since I was already working as a System Engineer using SQL, I had the database part covered at my end.

It was only when I started giving interviews, that I realized that their course curriculum and faculty was sub-par. A lot of the interview questions asked were not even covered in the lectures. When I went back to them with these doubts, they said it was out of syllabus.
Then I tried to learn by myself. I checked out some free courses.

In one of my interviews, I met this guy. He was a fellow candidate and he seemed pretty confident. We got to talking and he told me that he did a Data Science specialization course from Dimensionless. He was so satisfied with the course that I could feel his genuineness. Obviously, I got very excited to know more about Dimensionless.

Next thing I did was I spoke to their counsellors and joined in the next batch itself.

Experience with Dimensionless?

TBH, before taking up this course with Dimensionless, I was convinced that I can only learn properly in a physical classroom. I thought physical classrooms provide more support and are more accessible. Now I am much more comfortable in online training. Online or offline, if the teachers are good and doubts are handled, it doesn’t matter. It was so comfortable to attend classes from anywhere.

I knew why that guy in the interview was so happy with Dimensionless. The doubt-solving was quick. Teachers were available on call too. The sessions had a lot of communication and they were interactive overall. The course content was practical and easy to follow too.

Career Transition to Data Science

After completing the course in 5 months, I did some more self-study because I thought why someone would select me over an experienced Data Science professional.  I delayed applying for jobs. Finally, after some moral support from their mentors and mock interviews with Dimensionless HR, I built up the courage to apply for jobs and give interviews. Among other companies, I applied at TSystems, Wipro and Capegemini, and I got selected in all three!!! Imagine my excitement.

When I started giving interviews I realized that interviewers judge you based on knowledge and not past experience.

In Data Science, as well as every other advanced technology, the main thing that matters is practical knowledge.

Do you also want career transition like Ruchi?
Follow this link, and make it possible with Dimensionless Techademy!

Furthermore, if you want to read more about data science, you can read our blogs here.

 

Network Engineer to Machine Learning Engineer

Network Engineer to Machine Learning Engineer

by | Oct 14, 2019 | Career Transitions, Data Science

Career Transition to Data Science Success Story

Hands-on practice is the key to a good start in Data Science!


-Ashish Anand

Background

Education: BE Electronics & Communications

Previous Profile >>> Transition Profile >>> Current Profile
Company: Ericsson
Profile: Network Engineer
Domain: Telecom		 Company: Ericsson
Profile: Data Science Analyst
Domain: Telecom		 Company: Affine Analytics
Designation: Data Science Associate
Profile: Sr. Business Analyst
Domain: Retail

My journey into Data Science

Why Data Science?

In my previous profile, the work was very manual and monotonous, doing the same thing time and again. I was not satisfied with my work. I knew I had to change something. At that time, I was considering Data Science as well as Big Data since these two have the maximum scope and good pay as well. Maths and Stats were always my strong points and I am technically strong too. Considering this, Data Science looked like an exciting journey.

Why Dimensionless?

I tried to learn by myself through other online learning classes. I also took a course through Udemy. The pre-recorded videos were a drag. It was not interactive and I had a lot of doubts. That is when I came across Dimensionless.

Compared to other courses, this one had a detailed syllabus with 200 hours Live and Interactive training. I was sure about joining this course as soon as I attended the Demo. I took a lot of other courses but there was something or the other missing in them. With Dimensionless, I found all of it in one place.

Experience with Dimensionless?

It was exactly as I wanted it, a good mix of theory and practical. The classes were very interactive and teachers were always available for doubt-solving. They also helped me with my additional self-studies. I went to them with topics that were not in the syllabus and still got support. There was ample pre-recorded content as well, that we could refer to after the live classes.

Career Transition to Data Science

I’ll be honest, I didn’t get through any interviews at first. With mentors at Dimensionless, I got feedback on my performance at the interviews. The career mentoring facility helped me understand what I was interested in and which jobs I should be applying to accordingly. The HR guided me about which companies and jobs I need to apply to, weigh the advantages and disadvantages of the profiles.

This started giving me confidence. Finally, I got shortlisted for multiple companies, one of them was through Dimensionless. I joined Affine Analytics with almost 70% hike from my previous job. I am thankful to Dimensionless for all of this.

I like my work, I can work for 10 hours straight and not feel stressed.

 

Electronics Engineer to Machine Learning Engineer

Electronics Engineer to Machine Learning Engineer

by | Sep 24, 2019 | Career Transitions, Data Science

Career Transition to Data Science Success Story

Data Science and AI are career choices for everyone who want to be excited about their jobs and learn new things!


– Jagrati Valecha

Background

Education: B. Tech Electronics & Communications

Previous Profile

Company: Honeywell Aerospace
Profile: Electronics Engineer
Domain: Aerospace
Experience: 3.4 years

Current Profile

Company: Honeywell Aerospace
Profile: Machine Learning Engineer
Domain: Aerospace

My journey into Data Science

Why Data Science?

I was an Electronics Engineer in Aerospace and I couldn’t see any growth in my domain. The opportunities to learn new things were limited, which lead to no growth and it became less and less exciting to me every day.

I realized I had to switch to software and upgrade my skills as per the demand to stay relevant throughout my career. I spoke with many of my peers, did some research, and found a few career choices viable as per the market right now. Data Science looked like an interesting career choice but I still remember having so many doubts!

Why Dimensionless?

As I was researching, I came across Dimensionless on Google and enrolled for a Demo session. I asked them all the questions and doubts I had about taking up Data Science. I literally bombarded them with questions like…
How difficult is it going to be without having much of programming knowledge?
Is having no previous work-experience okay? And does it count?
How does Data Science fit in my domain (Aerospace)?

They answered all of it with patience and logic. I also had a one-on-one career counselling session with their counsellor.

Then there were other things to consider, like if I can attend the classes regularly, if the fee is viable, if I can get back to studies after such a long break, etc.

So, I went for the Experience and Pay option. Attended the classes for 2 weeks, I liked their methodology, and since I could understand what I was learning, I found myself attending lectures regularly along with my work and without being too stressed. And then, I continued and completed the entire course.

Experience with Dimensionless?

The course structure and methodology is not too stressing. The teaching pace wasn’t too stressing. Doubt-solving was immediate. I could get my doubts solved during the class, in the doubt-solving sessions or even one-on-one with the respective teacher. And trust me, coming from a non-programming background, I had a lot of doubts. Mentors and teachers were always available answering doubts.

Career Transition to Data Science

Resume-building sessions made me understand how to steer my career towards Data Science in Aerospace. When mentors started giving us projects, I got to choose projects from my domain so I could build upon my experience. This helped me get ready for interviews more than anything. Knowing theory is one thing, but the interviewers ask very technical and practical questions.

About only 70% of the course was done when I applied for an internal-switch at my company and got accepted. In fact, I even got a promotion and didn’t have to apply anywhere else.

I went from an Electronics Engineer to Machine Learning Engineer, within just 4 months into the course. With sincere efforts, you too can become a Data Scientist.

Go beyond doubts, ask questions and keep learning.


Big Data to Data Science: Career Transition

Big Data to Data Science: Career Transition

by | Sep 23, 2019 | Big Data, Career Transitions, Data Science

Career Transition to Data Science Success Story

Knowing ML algorithms is not enough. In-depth understanding to build ML models is more important.

– Darshan Jayanna

Background

Education: B.E. Electronics

Previous Profile

Company: Accenture 
Profile: Big Data Engineer 
Domain: Healthcare & Public Sector 
Location: Hyderabad
Experience: 1.5 Years

Current Profile

Company: The Math Co.
Profile: Data Scientist
Domain: IT 
Location: Bangalore

My journey into Data Science

Why Data Science?

Everyone in the IT industry knows Machine Learning is the future. Everything will be automated soon and if you can’t catch up, your job will be outdated soon. I realized and accepted that I will have to buck up. Coming from Big Data background, Data Science was a simple choice.

Why Dimensionless?

Honestly, I thought I could learn through free courses, so for almost a year, I tried to learn by myself online. I know I wasted a year, but I guess every IT person must’ve tried learning that way while getting to know new technology. Though there was a lot of knowledge around, it’s not in-depth. Like they give you the algorithms to study, but no one tells you the maths and logic behind those algos. That’s why I wanted a proper coaching class where someone can go in a step deeper and teach me the logic.

Also, since I was working, I wanted something online and something that did not cost a lot.

After checking plenty of courses, I came across Dimensionless. The reviews were all-star, the fee was reasonable, and the course curriculum and duration looked justified. I attended the Demo, it was quite impressive. For me, the decision-making point was that they started the course with the basics of Stats and Programming, so I could start learning from scratch.

Experience with Dimensionless?

The program was very flexible and highly interactive. Every day I had the option to join the class in the morning or the evening. Later a recording of the class was also available even if I missed my class. And 3 hours of self-study on the weekend was more than enough to cover up the weekly syllabus.

Frankly, implementation of ML on data does not involve much coding, rather it is about the logic behind the algorithm. Dimensionless helped me understand what’s going on in the backend.

Career Transition to Data Science

Once I was comfortable in the course, the transition felt natural. And after solving case studies under the guidance of Dimensionless I was able to smoothly switch to a Data Science profile within the company itself.

To start my career transition, first I got a project with Dimensionless and got some hands-on experience along with my job.

Initially, I was trying to transition within my company to gain some experience and feel more confident but I was not getting a release from the project due to company policies. But I did not want to get stuck and decided to move out. So I started giving interviews outside and actually ended with almost 100% hike in my salary.

The interviewers mostly asked questions on understanding of these algorithms. There were 2-3 hours of theory at Dimensionless before covering the algorithms, this made it simpler to understand and implement the algorithms. It helped me a lot during the interviews.

Through Dimensionless, I got selected in Motilal Oswal as a Data Scientist in Mumbai. Later I got 2 more offers, one from ePay and other from The Math Co., and as you already know…
I took the one at The Math Co. with a One Hundred Percent salary hike!

I strongly believe that as success comes to those who reach for it, similarly career-growth comes by constantly upgrading oneself.

 

Making a Career Transition: Business Intelligence to Data Science

Making a Career Transition: Business Intelligence to Data Science

by | Sep 13, 2019 | Career Transitions, Data Science

Career Transition to Data Science Success Story

I realized the only thing stopping my career-growth was my own hesitancy


– Kantesh Biswas

Background

Education: BE in IT

Previous Profile

Company: Syntel
Profile: Associate Consultant
Project: Reporting and BI
Location: India

Current Profile

Company: TCS
Profile: Business Analyst
Project: Data Science
Location: India

My journey into Data Science

Why Data Science?

I like to keep myself updated with the latest trends in the IT industry. Back in 2015, when I started my career, my choices were Data Science or Cloud Computing. After a bit of research about these domains, it was clear that with my analytical and logical skills I could do really well in Data Science.

Why Dimensionless?

One of my project-colleagues enrolled in the Data Science program at Dimensionless and he really liked the course. At first, I was a little sceptical about an online course since I am used to learning in a physical classroom. As my colleague was completing the course, he got transferred to a Data Science project internally!

That was an eye-opening moment for me. I attended a class along with him, all the students were asking doubts and getting it resolved. That helped me make the decision.

Experience with Dimensionless?

Even more comfortable than physical classes. The best part was that I could get my doubts resolved at any time. The teachers were helping and kept the classes very interactive.
This always kept me motivated to self-study and practice, study Data Science projects on my own.
I also got a lot of help from their alumni groups. Even to this day, I am in touch with my mentors at Dimensionless.

Career Transition to Data Science

Once I was comfortable in the course, the transition felt natural. And after solving case studies under the guidance of Dimensionless I was able to smoothly switch to a Data Science profile within the company itself.


I think if you follow the curriculum and course path along with gaining as much project-related knowledge as possible, you cannot go wrong with Data Science. Keep learning, keep upgrading.