Coding skills
Coding or programming skills are the most important skillset a person entering the data science field can possess. It is the base of data science, and without it, it is almost impossible to enter the field. No matter what you decide to do in this field, learning coding and programming languages will help you. This includes languages like R or Python and SQL as a database query language. When companies hire you, you are expected to already possess the knowledge of these programming languages.
Statistics
As a data scientist, you must be fluent in statistics. What this means is that you must know the subject like the back of your hand. It is one of the fundamental skills you can possess in this field and holds great value. Data scientists use statistics to evaluate the data acquired and make necessary predictions. While this is very similar to machine learning, statistics will help you understand the difference between usable and important data and unnecessary and unimportant data. This data needs to be presented to the stakeholders, and they will depend on you to predict the outcome.
Machine learning
Machine learning is a common technique that is used by big companies that have huge amounts of data. This is also very common in those companies where the whole product itself is data-driven and does not depend entirely on human labor. For example, Netflix and Google both give you recommendations by machine learning. Machine learning studies previous patterns and provides you with predictions for the future. Based on these predictions, the stakeholders can establish various organizational goals and take corrective measures to improve their performance. Some examples of machine learning are k-nearest neighbors, random forests, and so on.
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Multivariable Calculus and Linear Algebra
Multivariable calculus and linear algebra are mainly used for data-driven companies. These include Google, Netflix, Amazon Prime, Uber, and so on. They are mainly beneficial to those companies where small changes in their algorithm and predictive performance can help earn huge profits. Often when you go for interviews and job applications, you will most likely be asked about how to calculate multivariable calculus and linear algebra since they are the basic skills to understand most techniques, including machine learning. They are important skills to learn because they help understand most other techniques and provide you with more insight.
Data intuition
When a company hires you, this is one of the most vital skills they look for in their applicants. They want to see you as a problem solver when it comes to processing the data found. A data scientist often interacts with all parts of the company, from the product manager to the marketing manager. When you are presented with a problem, you will have to prove to the company that you can solve it. You should study the data provided to you and make necessary predictions, considering what is important and what is not.
The data science field is one of the most promising fields that one can enter. With the rising demand, you only see more opportunities being created in the field. With the right set of skills, you will become an expert in the field and even excel at what you want to achieve. If you are thorough in the skills mentioned above, companies will value you as an asset and hire you. Since data science is an ever-evolving career, you must always be updated on the skills you require in the current times.
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