100% Discount || Complete Data Science, Deep Learning, R | Data Science 2021

Requirements
No prior knowledge is required
Free software and tools used during the course
Basic computer knowledge
Desire to learn data science
Nothing else! It’s just you, your computer and your ambition to get started today
Description
Welcome to Complete Data Science, Deep Learning, R | Data Science 2021 course.

Ready for the Data Science career?

Are you curious about Data Science and looking to start your self-learning journey into the world of data ?

Are you an experienced developer looking for a landing in Data Science!

In both cases, you are at the right place!

The two most popular programming tools for data science work are Python and R at the moment. It is hard to pick one out of those two amazingly flexible data analytics languages. Both are free and open-source.

R for statistical analysis and Python as a general-purpose programming language. For anyone interested in machine learning, working with large datasets, or creating complex data visualizations, they are absolutely essential.

With my full-stack Data Science course, you will be able to learn R and Python together.

If you have some programming experience, Python might be the language for you. R was built as a statistical language, it suits much better to do statistical learning with R programming.

But do not worry! In this course, you will have a chance to learn both and will decide to which one fits your niche!

Throughout the course’s first part, you will learn the most important tools in R that will allow you to do data science. By using the tools, you will be easily handling big data, manipulate it, and produce meaningful outcomes.

Throughout the course’s second part, we will teach you how to use the Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms and we will also do a variety of exercises to reinforce what we have learned in this Python for Data Science course.

We will open the door of the Data Science world and will move deeper. You will learn the fundamentals of Python and its beautiful libraries such as Numpy, Pandas, and Matplotlib step by step. Then, we will transform and manipulate real data. For the manipulation, we will use the tidyverse package, which involves dplyr and other necessary packages.

At the end of the course, you will be able to select columns, filter rows, arrange the order, create new variables, group by and summarize your data simultaneously.

Because data can mean an endless number of things, it’s important to choose the right visualization tools for the job. Whether you’re interested in learning Tableau, D3.js, After Effects, or Python, Udemy has a course for you.

In this course we will learn what is the data visualization and how does it work with python.

This course has suitable for everybody who interested data vizualisation concept.

First of all, in this course we will learn some fundamentals of pyhton, and object oriented programming ( OOP ). These are our first steps in our Data Visualisation journey. After then we take a our journey to Data Science world. Here we will take a look data literacy and data science concept. Then we will arrive at our next stop. Numpy library. Here we learn the what is numpy and how we can use it. After then we arrive at our next stop. Pandas library. And now our journey becomes an adventure. In this adventure we’ll enter the Matplotlib world then we exit the Seaborn world. Then we’ll try to understand how we can visualize our data, data viz. But our journey won’t be over. Then we will arrive our final destination. Geographical drawing or best known as Geoplotlib in tableau data visualization.

Learn python and how to use it to python data analysis and visualization, present data. Includes tons of code data vizualisation.

In this course, you will learn data analysis and visualization in detail.

Also during the course you will learn:

The Logic of Matplotlib

What is Matplotlib

Using Matplotlib

Pyplot – Pylab – Matplotlib – Excel

Figure, Subplot, Multiplot, Axes,

Figure Customization

Plot Customization

Grid, Spines, Ticks

Basic Plots in Matplotlib

Overview of Jupyter Notebook and Google Colab

Seaborn library with these topics

What is Seaborn

Controlling Figure Aesthetics

Color Palettes

Basic Plots in Seaborn

Multi-Plots in Seaborn

Regression Plots and Squarify

Geoplotlib with these topics

What is Geoplotlib

Tile Providers and Custom Layers

In this course you will learn;

How to use Anaconda and Jupyter notebook,

Fundamentals of Python such as

Datatypes in Python,

Lots of datatype operators, methods and how to use them,

Conditional concept, if statements

The logic of Loops and control statements

Functions and how to use them

How to use modules and create your own modules

Data science and Data literacy concepts

Fundamentals of Numpy for Data manipulation such as

Numpy arrays and their features

How to do indexing and slicing on Arrays

Lots of stuff about Pandas for data manipulation such as

Pandas series and their features

Dataframes and their features

Hierarchical indexing concept and theory

Groupby operations

The logic of Data Munging

How to deal effectively with missing data effectively

Combining the Data Frames

How to work with Dataset files

And also you will learn fundamentals thing about Matplotlib library such as

Pyplot, Pylab and Matplotlb concepts

What Figure, Subplot and Axes are

How to do figure and plot customization

Examining and Managing Data Structures in R

Atomic vectors

Lists

Arrays

Matrices

Data frames

Tibbles

Who this course is for:
Anyone interested in data sciences
Anyone who plans a career in data scientist,
Software developer whom want to learn data science,
Anyone eager to learn Data Science with no coding background
Statisticians, academic researchers, economists, analysts and business people
Professionals working in analytics or related fields
Anyone who is particularly interested in big data, machine learning and data intelligence