Data Science with R and Python | R Programming (Udemy.com)

Welcome to Data Science with R and Python | R Programming course

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Python and R programming! Learn data science with R & Python all in one course You'll learn NumPy, Pandas, and more

OAK Academy offers highly-rated data science courses that will help you learn how to visualize and respond to new data, as well as develop innovative new technologies Whether you’re interested in machine learning, data mining, or data analysis, Udemy has a course for you

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Python instructors at OAK Academy specialize in everything from software development to data analysis and are known for their effective, friendly instruction for students of all levels
Whether you work in machine learning or finance or are pursuing a career in web development or data science, Python is one of the most important skills you can learn Python's simple syntax is especially suited for desktop, web, and business applications Python's design philosophy emphasizes readability and usability Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization The core programming language is quite small and the standard library is also large In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks
Machine learning and data analysis are big businesses The former shows up in new interactive and predictive smartphone technologies, while the latter is changing the way businesses reach customers Learning R from a top-rated OAK Academy instructor will give you a leg up in either industry R is the programming language of choice for statistical computing Machine learning, data visualization, and data analysis projects increasingly rely on R for its built-in functionality and tools And despite its steep learning curve, R pays to know

Ready for a 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, manipulating it, and producing meaningful outcomes

Throughout the course's second part, we will teach you how to use 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, and 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

• 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 the 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