Oak Academy

Full Stack Data Science with Python, Numpy and R Programming

  • Learn data science with R programming and Python. Use NumPy, Pandas to manipulate the data and produce outcomes
  • Oak Academy
  • Instructor : Oak Academy
  • Category : Development
Full Stack Data Science with Python, Numpy and R Programming

Full Stack Data Science with Python, Numpy and R Programming

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

  • Description
  • Curriculum
  • Instructors
  • Reviews

Course Details

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

Dive in now!

We offer full support, answering any questions.

See you in the course!

Requirements

  • No prior python and r 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
  • Curiosity for r programming
  • Desire to learn Python
  • Desire to work on r and python

What you will 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.
  • 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
  • OAK 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.
  • Data science is everywhere. Better data science practices are allowing corporations to cut unnecessary costs, automate computing, and analyze markets.
  • Data science is the key to getting ahead in a competitive global climate.
  • Data science uses algorithms to understand raw data. The main difference between data science and traditional data analysis is its focus on prediction.
  • Data Scientists use machine learning to discover hidden patterns in large amounts of raw data to shed light on real problems.
  • Python is the most popular programming language for data science. It is a universal language that has a lot of libraries available.
  • Data science requires lifelong learning, so you will never really finish learning.
  • It is possible to learn data science on your own, as long as you stay focused and motivated. Luckily, there are a lot of online courses and boot camps available
  • Some people believe that it is possible to become a data scientist without knowing how to code, but others disagree.
  • A data scientist requires many skills. They need a strong understanding of statistical analysis and mathematics, which are essential pillars of data science.
  • The demand for data scientists is growing. We do not just have data scientists; we have data engineers, data administrators, and analytics managers.
  • The R programming language was created specifically for statistical programming. Many find it useful for data handling, cleaning, analysis, and representation.
  • R is a popular programming language for data science, business intelligence, and financial analysis. Academic, scientific, and non-profit researchers use the R
  • Whether R is hard to learn depends on your experience. After all, R is a programming language designed for mathematicians, statisticians, and business analysts

Who should attend

  • Anyone interested in data sciences
  • Anyone who plans a career in data scientist,
  • Software developer whom want to learn python,
  • Anyone eager to learn python and r 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
  • Anyone eager to learn Python with no coding background
  • Anyone who wants to learn Pandas
  • Anyone who wants to learn Numpy
  • Anyone who wants to work on real r and python projects
  • Anyone who wants to learn data visualization projects.
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Oak Academy

Oak Academy

Web & Mobile Development, IOS, Android, Ethical Hacking, IT

Hello, I'm OAK. 

By 2020 there will be a shortage of 1 million more tech jobs than computer science grads and the skills gap is a global problem. This was our starting point.

At OAK Academy, we are the tech experts have been in the sector for years and years. We are deeply rooted in the tech world. We know the tech industry. And we know the tech industry` biggest problem is  “tech skills gap” and here is our solution.

OAK Academy we will be the bridge to between the tech industry and people who

-are planning a new career

-are thinking career transformation

-want career shift or reinvention,

-the desire to learn new hobbies at their own pace

Because we know we can help this generation gain the skill to fill these jobs and enjoy happier, more fulfilling careers. And this is what motivates us every day.

We specialize in critical areas like cybersecurity, coding, IT, game development, app monetization, and mobile. Thanks to our practical alignment we are able to constantly translate industry insights into the most in-demand and up-to-date courses,

OAK Academy will provide you the information and support you need to move through your journey with confidence and ease.

Our courses are for everyone. Whether you are someone who has never programmed before, or an existing programmer seeking to learn another language or even someone looking to switch careers we are here.

OAK Academy here to transforms passionate, enthusiastic people to reach their dream job positions.

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Full Stack Data Science with Python, Numpy and R Programming

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