nageshgurram12
Nov 4, 2018
Graduate / Data Science as a mainstream career option for me [3]
Ever since my childhood I was always at ease when solving complex mathematical problems (especially in algebra and calculus), I can even recall some memories of my school life where I was helping my seniors to solve their problems. I even won many local mathematical contests and was always a merit student in this subject. Because of the interest in this subject and boom of the computers in 90's, after school I studied computer science where I found my next academic interest as programming to computers. However, after experiencing few years in software development I realized I've sidelined my primary interest (Mathematics). Then I started exploring the career options where I can use my experience in coding and the innate inclination towards mathematics, luckily with the rise of Data Science as main stream career option, I've found that this is the field where I can use both of my core capabilities.
To corroborate the facts I've mentioned above, one can take a look at my academic background. In school days I was always exceptional student by being ahead in the line. I've completed my school education with 95% grade marks with cent percentage in Mathematics. Next, I went to Andhra University College of Engineering (one of reputed colleges in India) to complete my B.Tech (Bachelor of Technology) in department of Computer Science & Systems Engineering. In the under graduate program I amassed theoretical knowledge in some of the essential subjects a software developer to have such as 'Discrete Mathematics' ,'Design & Analysis of Algorithms', 'Object Oriented Design & Development' and 'Database Systems' etc.. At the end, I've completed it with 8.13 GPA with 5th stand (1st stand is at 8.32).
With the advent of thought to change my career into data science, I've joined in Executive Master's in Data Science (EMDS) program in Indian Institute of Technology, Hyderabad (IITH). This program is started by IITH institute for working professionals to widen or hone their skills in data science field. By attending classes in weekends, I've completed two semesters till now with 9.75 GPA (by Nov-2018) standing at 2nd position. As this is oriented for working professionals the syllabus is not exhaustive and only covers brief topics in data science. As part of this, I've studied statistics (with R programming), probability, linear algebra and calculus in first semester and as part of second semester I learnt programming GPU in CUDA, multi-core CPU in OpenMP & MPI, building recommendation systems, frequent pattern mining in transactional databases, locality sensitive hashing, link analysis in social networks and map-reduce framework. Currently, in the third semester I'm learning various classification and regression algorithms in Supervised learning, clustering and dimensionality reduction in Unsupervised learning and as part of probabilistic machine learning I have been taught Maximum-Likelihood-Estimation (MLE), Expectation-Maximization (EM), Bayesian Inference, Exponential Models and Hidden Markov Models. As part of the course, I got not only theoretical knowledge in these concepts but also many of these methods are practiced by using R/Python languages & their built-in libraries. As part of the next semester, our erudite professors will cover 'Information Retrieval' and 'Deep Learning' courses.
With the help of EMDS program in IITH I got good understanding in basics of data science, however I want to gain more knowledge in particular areas of Data Science such as machine learning, data mining, data visualization etc. for which this program is not enough to gain in depth knowledge of many kinds of algorithms that are being used widespread nowadays. , I want to acquire thorough understanding of many algorithms in machine learning by applying statistics, optimization and probability theory and also learn many concepts that are not covered as part of EMDS course like 'Time Series Analysis', 'Sentiment Analysis' and many more novel topics. For this reason, I want to enroll in full time program __PROGRAM__ offered by "__UNIVERSITY__" where I can not only expand my existing knowledge but also spend enough time to learn and dwell upon the topics in data science.
Like how any sub field in computer science requires good coding skills, even data science also requires prior experience in programming to design and development of models (in any language interest), to extract features, to wrangle the data and to visualize it and so on. With the seven years of experience in software design and development, I can confidently say the above tasks will be a cakewalk for me. After under graduation, I've joined in FTD India Pvt. Ltd (former subsidiary of United Online India Pvt. Ltd) where I was a part of the team in building and maintaining the gifts-delivery e-commerce website. In 'FTD' organization, I gained excellent coding skills to develop applications in modularized way in 'Perl', 'JavaScript' languages. After that, I joined the team developing 'Oracle commerce' product in Oracle India Pvt. Ltd which is an e-commerce platform for customers to develop and integrate e-commerce businesses. This experience in Oracle helped me to gain coding & debugging skills in 'Java' and 'JavaScript' (using different frameworks of them like Spring, Hibernate, node.js, knockout.js etc.) and designing large scale applications. Currently I'm a part of the team in Oracle commerce product that is developing a recommendation system that shows purchase suggestions to end users. Though it's in initial state, we are approaching this problem in already proven techniques such as content-based filtering, collaborative filtering and latent-factor modeling.
In future I am planning to do research in data science by analyzing the existing algorithms to improve accuracies & performances and also by contributing to build new algorithms. I believe that the __PROGRAM__ in __UNIVERSITY__ gives me an opportunity to achieve my goal as this program provides a very good structured curriculum in the field of data science, covering mathematical and computational technical skills.
Statement of Purpose for Graduate Data Science Program
Ever since my childhood I was always at ease when solving complex mathematical problems (especially in algebra and calculus), I can even recall some memories of my school life where I was helping my seniors to solve their problems. I even won many local mathematical contests and was always a merit student in this subject. Because of the interest in this subject and boom of the computers in 90's, after school I studied computer science where I found my next academic interest as programming to computers. However, after experiencing few years in software development I realized I've sidelined my primary interest (Mathematics). Then I started exploring the career options where I can use my experience in coding and the innate inclination towards mathematics, luckily with the rise of Data Science as main stream career option, I've found that this is the field where I can use both of my core capabilities.
To corroborate the facts I've mentioned above, one can take a look at my academic background. In school days I was always exceptional student by being ahead in the line. I've completed my school education with 95% grade marks with cent percentage in Mathematics. Next, I went to Andhra University College of Engineering (one of reputed colleges in India) to complete my B.Tech (Bachelor of Technology) in department of Computer Science & Systems Engineering. In the under graduate program I amassed theoretical knowledge in some of the essential subjects a software developer to have such as 'Discrete Mathematics' ,'Design & Analysis of Algorithms', 'Object Oriented Design & Development' and 'Database Systems' etc.. At the end, I've completed it with 8.13 GPA with 5th stand (1st stand is at 8.32).
With the advent of thought to change my career into data science, I've joined in Executive Master's in Data Science (EMDS) program in Indian Institute of Technology, Hyderabad (IITH). This program is started by IITH institute for working professionals to widen or hone their skills in data science field. By attending classes in weekends, I've completed two semesters till now with 9.75 GPA (by Nov-2018) standing at 2nd position. As this is oriented for working professionals the syllabus is not exhaustive and only covers brief topics in data science. As part of this, I've studied statistics (with R programming), probability, linear algebra and calculus in first semester and as part of second semester I learnt programming GPU in CUDA, multi-core CPU in OpenMP & MPI, building recommendation systems, frequent pattern mining in transactional databases, locality sensitive hashing, link analysis in social networks and map-reduce framework. Currently, in the third semester I'm learning various classification and regression algorithms in Supervised learning, clustering and dimensionality reduction in Unsupervised learning and as part of probabilistic machine learning I have been taught Maximum-Likelihood-Estimation (MLE), Expectation-Maximization (EM), Bayesian Inference, Exponential Models and Hidden Markov Models. As part of the course, I got not only theoretical knowledge in these concepts but also many of these methods are practiced by using R/Python languages & their built-in libraries. As part of the next semester, our erudite professors will cover 'Information Retrieval' and 'Deep Learning' courses.
With the help of EMDS program in IITH I got good understanding in basics of data science, however I want to gain more knowledge in particular areas of Data Science such as machine learning, data mining, data visualization etc. for which this program is not enough to gain in depth knowledge of many kinds of algorithms that are being used widespread nowadays. , I want to acquire thorough understanding of many algorithms in machine learning by applying statistics, optimization and probability theory and also learn many concepts that are not covered as part of EMDS course like 'Time Series Analysis', 'Sentiment Analysis' and many more novel topics. For this reason, I want to enroll in full time program __PROGRAM__ offered by "__UNIVERSITY__" where I can not only expand my existing knowledge but also spend enough time to learn and dwell upon the topics in data science.
Like how any sub field in computer science requires good coding skills, even data science also requires prior experience in programming to design and development of models (in any language interest), to extract features, to wrangle the data and to visualize it and so on. With the seven years of experience in software design and development, I can confidently say the above tasks will be a cakewalk for me. After under graduation, I've joined in FTD India Pvt. Ltd (former subsidiary of United Online India Pvt. Ltd) where I was a part of the team in building and maintaining the gifts-delivery e-commerce website. In 'FTD' organization, I gained excellent coding skills to develop applications in modularized way in 'Perl', 'JavaScript' languages. After that, I joined the team developing 'Oracle commerce' product in Oracle India Pvt. Ltd which is an e-commerce platform for customers to develop and integrate e-commerce businesses. This experience in Oracle helped me to gain coding & debugging skills in 'Java' and 'JavaScript' (using different frameworks of them like Spring, Hibernate, node.js, knockout.js etc.) and designing large scale applications. Currently I'm a part of the team in Oracle commerce product that is developing a recommendation system that shows purchase suggestions to end users. Though it's in initial state, we are approaching this problem in already proven techniques such as content-based filtering, collaborative filtering and latent-factor modeling.
In future I am planning to do research in data science by analyzing the existing algorithms to improve accuracies & performances and also by contributing to build new algorithms. I believe that the __PROGRAM__ in __UNIVERSITY__ gives me an opportunity to achieve my goal as this program provides a very good structured curriculum in the field of data science, covering mathematical and computational technical skills.