Hello fellow human beings! This blog is mainly intended for professionals from non-CS Engineering (Mechanical, Electrical, Chemical etc) background professionals who want to develop an expertise in Data Science or pursue career path as Data Scientist. There is tons of information out there in the open almighty internet. However, there might not be very niche information like what would be the best option for certain type of people (e.g Chemical Engineering graduates). Thus, i want to share my analysis on what what is likely to work for me to build my expertise in data science. In the process, I hope to help professionals with similar background as myself to break into Data Science.
A few words about myself and why I chose to learn data science. I am a Chemical Engineering graduate and have been working in a major petrochemical complex in singapore for about 6+ years. Apart from the usual complaints, I do find my job interesting. There is a lot to learn and things do get very technical. However, with the slump of oil prices in 2015, came a rude awakening. With all the talks about oil demand peak and oil&gas to be a sunset industry from the next decade onwards. Thus, I felt the need to prepare myself for any possible unfavourable scenario. I was looking at various options - web development, computer-networking, instrumentation etc. The end result was just bits of work in different areas and stagnation. Finally, one day I was enlightened by my intellectual wife :). She pointed out that its not within our capacity to predict all possible future scenarios. So, just pick up one where interest lies and it seems to have a positive future. The key is to pick one, stick to it and deeply focus on it. Thus, I have decided to zoom in on data science to build my expertise. Few reasons for my choice:
1. The maths involved is something I am very familiar with and its interesting
2. Programming is interesting to me
3. A lot of organizations predict huge growth for need of data scientists
4. The skills can be applied in various industries and it is also very relevant to refining/petrochemcials industry.
Now, after choosing to build my expertise in data science, where do I start? Which books or online courses should I follow? Should I consider masters program or bootcamp? There are a lot of questions. The answers are going to depend on what is your current skill level in founding pillars of data science (math/ progrmamming/ Domain) and also finally what is your anticipated end goal. The focus on my blog articles is mainly for non-CS Engineering graduates who want to make a living from data science. There are many paths to achieve this goal. I intend to write one article on each the 3 different path I see:
1. Self study (Books, Videos & Practice)
2. Bootcamps
3. Maters program and certification.
Once the relevant basic skills are acquired, its a very different ball game on getting the job. Thus, I also intend to write an article covering the following:
1. Jobs as Data Scientist. Differences in requirements across various organizations.
2. How to clear HR screening ( Resume, Cover Letter etc)
3. Typical job exams and interview questions. How to prepare and crack them.
I do hope this information is useful for professionals similar to my background trying to break into Data Science. Pease do send me your feedback. Both positive and negative will be deeply appreciated. :)
Reference:
1. Ibm projection of 28% DS by 2020
2. McKinzey report on big data in oil&gas
A few words about myself and why I chose to learn data science. I am a Chemical Engineering graduate and have been working in a major petrochemical complex in singapore for about 6+ years. Apart from the usual complaints, I do find my job interesting. There is a lot to learn and things do get very technical. However, with the slump of oil prices in 2015, came a rude awakening. With all the talks about oil demand peak and oil&gas to be a sunset industry from the next decade onwards. Thus, I felt the need to prepare myself for any possible unfavourable scenario. I was looking at various options - web development, computer-networking, instrumentation etc. The end result was just bits of work in different areas and stagnation. Finally, one day I was enlightened by my intellectual wife :). She pointed out that its not within our capacity to predict all possible future scenarios. So, just pick up one where interest lies and it seems to have a positive future. The key is to pick one, stick to it and deeply focus on it. Thus, I have decided to zoom in on data science to build my expertise. Few reasons for my choice:
1. The maths involved is something I am very familiar with and its interesting
2. Programming is interesting to me
3. A lot of organizations predict huge growth for need of data scientists
4. The skills can be applied in various industries and it is also very relevant to refining/petrochemcials industry.
Now, after choosing to build my expertise in data science, where do I start? Which books or online courses should I follow? Should I consider masters program or bootcamp? There are a lot of questions. The answers are going to depend on what is your current skill level in founding pillars of data science (math/ progrmamming/ Domain) and also finally what is your anticipated end goal. The focus on my blog articles is mainly for non-CS Engineering graduates who want to make a living from data science. There are many paths to achieve this goal. I intend to write one article on each the 3 different path I see:
1. Self study (Books, Videos & Practice)
2. Bootcamps
3. Maters program and certification.
Once the relevant basic skills are acquired, its a very different ball game on getting the job. Thus, I also intend to write an article covering the following:
1. Jobs as Data Scientist. Differences in requirements across various organizations.
2. How to clear HR screening ( Resume, Cover Letter etc)
3. Typical job exams and interview questions. How to prepare and crack them.
I do hope this information is useful for professionals similar to my background trying to break into Data Science. Pease do send me your feedback. Both positive and negative will be deeply appreciated. :)
Reference:
1. Ibm projection of 28% DS by 2020
2. McKinzey report on big data in oil&gas
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