Description


Welcome to Full Stack Data Science with Python, Numpy, and R Programming course.


Do you want to learn Python from scratch?


Do you think the transition from other popular programming languages like Java or C++ to Python for data science?


Do you want to be able to make data analysis without any programming or data science experience?

Why not see for yourself what you prefer?
It may be hard to know whether to use Python or R for data analysis, both are great options. One language isn’t better than the other—it all depends on your use case and the questions you’re trying to answer.

In this course, we offer R Programming, Python, and Numpy! So you will decide which one you will learn.

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.

In the 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 course.

In this course, you will also learn Numpy which is one of the most useful scientific libraries in Python programming.

Throughout the course, we will teach you how to use the Python in Linear Algebra, and Neural Network concept, and use powerful machine learning algorithms and we will also do a variety of exercises to reinforce what we have learned in this Full Stack Data Science with Python, Numpy and R Programming course.

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.

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


Numpy functions


Numexpr module


How to do indexing and slicing on Arrays


Linear Algebra


Using NumPy in Neural Network


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


Factors


Data Transformation in R


Transform and manipulate a deal data


Tidyverse and more

And we will do many exercises. Finally, we will also have hands-on projects covering all of the Python subjects.

Why would you want to take this course?

Our answer is simple: The quality of teaching.

When you enroll, you will feel the OAK Academy's seasoned instructors' expertise.

Fresh Content

It’s no secret how technology is advancing at a rapid rate and it’s crucial to stay on top of the latest knowledge. With this course, you will always have a chance to follow the latest trends.

Video and Audio Production Quality

All our content are created/produced as high-quality video/audio to provide you the best learning experience.

You will be,


Seeing clearly


Hearing clearly


Moving through the course without distractions




You'll also get:


Lifetime Access to The Course


Fast & Friendly Support in the Q&A section


Udemy Certificate of Completion Ready for Download

Enroll