Is Programming knowledge Required to Pursue Data Science?
The term ‘Data Science’ has become a buzzword in the past couple of years. A lot of people who work in various domains such as IT and Business wants to make a shift to this new career option. Even people with a lot of experience as much as 15 years want to make a career shift towards Data Science. Apart from the fact that the domain has now become one of the most popular domains relatively, let us look into what it actually takes to make a career shift towards this data-driven domain. But first, let us dive into the skills that a Data Scientist would require.
The above shown Venn Diagram shows the perfect mix of skill set that one needs to acquire to become a successful Data Scientist. Data Scientist, being one of the highest paid jobs in recent times, requires a wide spectrum of skill set. Data Science is a domain which demands an ideal mix of both Technical and Non-Technical skills.
A day to day role of an ideal Data Scientist is to coherently work with both the Technical and the Non-Technical team. In fact, a Data Scientist bridges both the team thereby playing a very crucial role in any Data Science project pipeline. Hence, a Data Scientist requires a strong domain knowledge so as to not only understand the problem statement of the client but also understand the technical feasibility of the problem with the technical department. For example, if a model has to be trained to detect the type of cancer in a person, it is crucial to know the correlation of the features in the dataset with the target variable. It will help in using only the most important features to predict the same thereby increasing the accuracy of the model.
Mathematics is the backbone of the Data Science domain. Any Data Science role would require a strong mathematical foundation. Probability and Statistics are an integral part of Exploratory Data Analysis and Machine Learning. It is important to note that, a data scientist will be spending around 10% of the entire time solving mathematical problems working on the project. Since all the algorithms are based on mathematics, having a mathematical foundation is usually to understand the various algorithms that will be implemented to solve the business problem. Although most of the machine learning algorithms can be applied even without a strong mathematical foundation, having a strong mathematical base will definitely help in understanding the nature of the model and improving its accuracy. So, mathematics is definitely used at some point in the data science project.
Most of the data science job roles will require programming skills that are related to the domain. All the technical work carried out right from data cleaning, data analysis to implementation of the appropriate machine learning algorithms is carried out using a programming language (Python or R). Apart from this, having a general knowledge of how a database such as SQL will be really useful. Having basic knowledge of object-oriented programming will reduce the Data Science learning curve. Programming is a vital skill but one need not necessarily have a strong background on programming.
Now the most common question that everyone who wants to start a career in Data Science is:
The answer is No!Data Science is not just about having technical knowledge. Being a domain related to both the Computer science world as well as the Business world, the latter has a fair share of skill set that is very vital for becoming a data scientist.
