Full Stack Data Science with Python, Numpy and R Programming (Udemy.com)

Hello Dear,

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

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Learn data science with R programming and Python. Use NumPy, Pandas to  manipulate the data and produce outcomes | R

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.

It’s hard to imagine our lives without machine learning. Predictive texting, email filtering, and virtual personal assistants like Amazon’s Alexa and the iPhone’s Siri, are all technologies that function based on machine learning algorithms and mathematical models.
Data science is everywhere. Better data science practices are allowing corporations to cut unnecessary costs, automate computing, and analyze markets. Essentially, data science is the key to getting ahead in a competitive global climate.
Python instructors on 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.

• 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 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

• Machine learning,

• machine learning python,

• python,

• data science,

• python for data science and machine learning bootcamp,

• r,

• machine learning a-z,

• python data science,

• deep learning