The roadmap to a career in Data Science


Data science is an umbrella term for all the related to data – data analytics, data mining, big data, machine learning, and others. Data science comprises not only draws trends and insights from the data collected over a certain period of time but also generates intelligent systems and develops prototypes, predictive models, and algorithms. Data analytics is the procedure of inspecting data, discovering problem areas, making hypotheses, creating insights from the data, and eventually providing solutions for the advancement of the product. 


Let’s find out below what skills do you need to become a data scientist:

1.Programming languages – To kick-start your journey in the field of data science, you need to have a good knowledge of these  three programming languages – Python, Java, or R.

a. Java: It is a general purpose, high performance, compiled language which makes it apt for writing complicated machine learning algorithms. It lets data science approaches to be incorporated directly into the present codebase. It is fast and enormously scalable and is therefore used by most of the startups for their product development.

b. Python: Python makes an excellent choice for data science and not just at the entry level but even for sophisticated machine learning applications. Python leads the way with TensorFlow, Pandas, and Scikit-learn. It is really powerful and easy to learn, hence recommended.

c. R: It lets you to carry out approximately all quantitative and statistical applications. Neural networks, matrix algebra, nonlinear regression, advanced plotting – it manages them! And this is what makes it the most favored language to do statistical analysis on large datasets.

d. SQL: To work on data and drive the inputs in a way so as to attain the predicted result, you first require data. And what do you require to extract data? SQL! Companies these days have enormous databases to store all of it, you require to be a master of this trade. 

2. Ms-Excel – For basic statistical modelling, MS-Excel proves to be a good tool. You can take up MS-Excel training for a complete understanding of Excel concepts.

3. Statistics and probability – Let’s recapitulate what data science is. You have a problem statement, you examine the past data, create a hypothesis, predict the future results, and ensure that you do get the projected results. Now, statistics includes analyzing the frequency of past data and probability includes predicting the likelihood of future events.

You can learn all the above skills necessary to become a good data scientist by joining a data science training program from a reputed institution. Premier institutions have right faculty and resources to facilitate your learning. 


Location: Bengaluru, Karnataka, India

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