Before going to the answer of how to become a good data science and what are skills required? you should know what data science is. Data science is a field that uses different scientific techniques, algorithms, and statistical methods to eliminate knowledge from given data. Given data will be in a structured or unstructured format.
Top Seven Essential Technical Skills to Become a Good Data Scientist
There are many skill-sets and techniques to become a good data scientist but we will discuss that skill sets which are essential and enough to start a carrier as a data scientist.
Passionate your mind to become a Data Scientist
No doubt, Data science is a very enormous area. The most basic and most important thing to become a good data scientist is that you have to prepare yourself for the data science field. You should have to believe in yourself that you can become a good data scientist. You have to make your thoughts potentially to learn data science. When you find yourself hungry to learn to become a data scientist, you will adopt data science techniques very quickly.
Statistics and Probability
Skill sets that a data scientist needs, it always starts with statics and probability. Statistics will give your number of data. So, a very good understanding of statistics is very important for becoming a good data scientist. You have enough knowledge about statistical formulas, data distribution, data, standard derivation, and much more. You should have a worthy concepts of probability theories. These concepts will make a good understanding of business requirements.
To use statistical formulas and techniques, you should familiar with programming languages like R and Python. R and Python programming are mostly used in the data science field because these languages have several pre-defined packages to solve statistical problems. You have to just load desired packages from libraries and run it.
Data Extraction and Processing
Data extraction means to extract data from different resources such as form websites, MySQL database, mongo database, etc. After extraction data, you have to order data according to the prerequisite and examine it.
Data Wrangling and Exploration
Data wrangling and exploration is the most time-consuming task in the data science field because it is all about cleaning the data. There will be a lot of instances that have missing values, or null values or have an inconsistent format. You have to recognize how to treat such values.
Machine learning plays a backbone role in the data science field. In machine learning, we implement different algorithms (such as KNN, linear regression, support vector machine, clustering, etc.) to predict the required outcome. Machine learning algorithms and machine learning concepts are most important to become a good data scientist.
In data visualization, you have to visualize data so that anybody can understand the flow of data. If you want to communicate data with end-users in a better way, then data visualization is a must. A lot of tools used for data visualization such as tableau and power BI are the most popular to visualize data.
So, above are the entire skill sets that essential to become a good data scientist.