It is exceedingly important for aspiring Data Scientists to understand every fundamental of Statistics.
Python is the programming language of choice for scientific computing, offering a powerful environment for statistical data analysis.
R programming is great for statistical computing and graphics, with powerful packages optimized for data analysis and data visualization.
Learn Python for Data Science, including Pandas, NumPy, Matplotlib and Bokeh, to manipulate, analyze, and visualize datasets.
Behind every Data Science success, there is Probability and Statistics.
SQL is a highly relevant programming language in data science and has been the requested skill in the tech industry for a long period.
TensorFlow is a machine learning system that operates in heterogeneous environments
Geo Spatial Analysis is considered as a core infrastructure of the modern tech industry
Jupyter notebook is excellent for beginners and even better for experienced programmers as it supports more than 40 programming languages, primarily focused on Python.
Pandas is a Python library widely used by Data Scientists and Machine Learning engineers/ researchers.