Full Stack Data Science with Python, Numpy and R Programming

Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 48000 Hz

Language: English | VTT | Size: 6.21 GB | Duration: 36 sections | 149 lectures | (19h 52m)

What you'll learn

Learn R programming without any programming or data science experience

If you are with a computer science or software development background you might feel more comfortable using Python for data science

In this course you will learn R programming, Python and Numpy from the beginning

Learn Fundamentals of Python for effectively using Data Science

Fundamentals of Numpy Library and a little bit more

Data Manipulation

Learn how to handle with big data

Learn how to manipulate the data

Learn how to produce meaningful outcomes

Learn Fundamentals of Python for effectively using Data Science

Learn Fundamentals of Python for effectively using Numpy Library

Numpy arrays

Numpy functions

Linear Algebra

Combining Dataframes, Data Munging and how to deal with Missing Data

How to use Matplotlib library and start to journey in Data Visualization

Also, why you should learn Python and Pandas Library

Learn Data Science with Python

Examine and manage data structures

Handle wide variety of data science challenges

Create, subset, convert or change any element within a vector or data frame

Most importantly you will learn the Mathematics beyond the Neural Network

The most important aspect of Numpy arrays is that they are optimized for speed. We’re going to do a demo where I prove to you that using a Numpy vectorized operation is faster than using a Python list.

You will learn how to use the Python in Linear Algebra, and Neural Network concept, and use powerful machine learning algorithms

Use the “tidyverse” package, which involves “dplyr”, and other necessary data analysis package

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