Roadmap to a career in Data Science

Career in Data Science: A Complete Roadmap

Introduction

A recent Harvard Law Review had claimed that data science is presently one of the hottest jobs of the 21st century. The world of data has expanded to an extent where organizations and individuals are dealing with huge capacities of data in petabytes and exabytes. With the increasing amount of data, storage has become an issue and here is where data science comes in. Learning data science will prepare you for the future and also help you add value to it.  

Data science has a world of its own with different things for different people. Some of the vital subjects encompassing data science are statistics, computer science, and mathematics. It further includes data visualization, data cleaning, and formatting. With the increasing popularity of data science, the things that come to your mind first are why we need to learn data science, how and where to start learning, and which medium of learning would be suitable. Let us gradually address these issues in this article.

A Roadmap of Data Science

Before we delve deep into understanding the learning techniques of data science, we need to know why we want to learn data science. The fact that data scientists will be fetching a lot of money in the future should not be the ultimate goal for learning data science. You need to develop an interest in machine learning, algorithms, data structure, and the science itself to sustain a career in this field. Ultimately, your love and understanding of data science will help you make a mark here.

Learning Data Science

Data scientists can come from a variety of fields and working backgrounds. However, four of the major fields that are taken into consideration are mathematics, computer science, domain knowledge, and communication skills.

Mathematics

Some of the areas of mathematics that are very important in data science are linear algebra, multivariable calculus, probability, and optimization techniques. These help a lot in understanding the machine learning algorithms in data science. Statistics, on the other hand, help a lot in understanding data analysis.

Domain Knowledge

It is a common idea that domain knowledge is not very essential in data science which is absolutely not true. For instance, if you are a data scientist in the financial sector, you need to have a basic understanding about finances, banking, stock trading, etc. This has proven to be very beneficial and also gives you an upper hand in job applications.

Computer Science

This is one of the most critical subjects in data science. You need to learn programming languages along with other computer science skills such as basics of data structure and algorithm, Linux, Git, machine learning, deep learning, distributed computing, and SQL. With regard to programming languages, most people prefer to learn Python, but that depends on several other factors.

Communication Skill

Communication skills are essential in almost all professions these days; however, it is a tad bit more important in this field. Once a data science project is analyzed, the project needs to be communicated to others through a report or a blog post or as a presentation to your boss or your group of colleagues. It has to be communicated in some form or the other and hence, it is very important for data scientists to have very good communication skills.

Learning Resources

There are several ways one can learn data science. Plenty of resources and videos are available online, to begin with. A number of educational institutions are introducing Data Science Certification courses for you to learn and also walk away with a Data Analysis Certificate at the end of the course. Even though it might be a little overwhelming at the beginning, with little time and patience, it will gradually become easier. The study of data science requires continuous practice and skill development. One needs to continue training in data science to have better chances in the job market.

Conclusion

A complete understanding of machine learning algorithms is very essential for a good base in data science. Along with the above guidance, it is also essential to read some good books on data science to expand your knowledge. This roadmap will not only guide you through your data science learning process but also help you in securing a job in this field.

There are quite a few universities that are offering data science certification courses for interested individuals. The Certificate in Data Science and Analytics for Business – Shiv Nadar University (SNU) program will be a very good start to your data science learning career. Enroll for the program immediately to expedite your career.