Scientific Python: Data Science Visualization Bundle 18 Hrs!

About this course

18 HRS OF AWESOME FIVE STARS ⭐⭐⭐⭐⭐ VIDEOS!This is the Best and Most Complete Scientific Python Course on the Udemy platform that will walk you through the required skills for Data Sciences and useful Machine Learning (ML) libraries such as NumPy, Pandas, Scikit-Learn, Seaborn, Python RE (REGEX), PyTorch and Matplotlib. Furthermore, you learn how to work with different real datasets and use them for developing your models. All the Python code templates that we write during the course together are available, and you can download them with the resource button of each section.WHAT YOU WILL GET & LEARN?In this awesome 18 hours long course we will cover:SciPy is a free and open-source Python library used for scientific computing and technical computing. It contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering. The SciPy library is currently distributed under the BSD license, and its development is sponsored and supported by an open community of developers. NumPy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Most of the Matplotlib utilities lies under the pyplot submodule, and are usually imported under the plt alias.Pandas is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is free software released

Course objectives

• gain practical experience with real datasets
• understand key Python libraries for data science
• develop skills in data visualization and machine learning