Data Science is such a broad field that includes several subdivisions like data preparation and exploration, data representation and transformation, data visualization and presentation, predictive analytics, and machine learning, etc. For beginners, it’s only natural to raise the following question: What skills do I need to become a data scientist?

This article will discuss 10 essential skills that are necessary for practicing data scientists. These skills could be grouped into 2 categories, namely, technological skills (Math & Statistics, Coding Skills, Data Wrangling & Preprocessing Skills, Data Visualization Skills, Machine Learning Skills, and Real World Project Skills) and** soft skills** (Communication Skills, Lifelong Learning Skills, Team Player Skills, and Ethical Skills).

Data science is a field that is ever-evolving, however mastering the foundations of data science will provide you with the necessary background that you need to pursue advanced concepts such as deep learning, artificial intelligence, etc. This article will discuss 10 essential skills for practicing data scientists.

1. Mathematics and Statistics Skills

(i) Statistics and Probability

Statistics and Probability is used for visualization of features, data preprocessing, feature transformation, data imputation, dimensionality reduction, feature engineering, model evaluation, etc. Here are the topics you need to be familiar with:

a) Mean

b) Median

c) Mode

d) Standard deviation/variance

e) Correlation coefficient and the covariance matrix

f) Probability distributions (Binomial, Poisson, Normal)

g) p-value

h) MSE (mean square error)

i) R2 Score

j) Baye’s Theorem (Precision, Recall, Positive Predictive Value, Negative Predictive Value, Confusion Matrix, ROC Curve)

k) A/B Testing

l) Monte Carlo Simulation

#2020 oct opinions #uncategorized #data science #data science skills