What you would learn in Data Science with R and Python course?
- R and Python in the same course. You decide which one you would go for!
- R was built as a statistical language, it suits much better to do statistical learning and R is a statistical programming software favoured by many academia
- If you have some programming experience, Python might be the language for you
- Since R was built as a statistical language, it suits much better to do statistical learning. It represents the way statisticians think pretty well, so anyone with a formal statistics background can use R easily. Python, on the other hand, is a better choice for machine learning with its flexibility for production use, especially when the data analysis tasks need to be integrated with web applications. If you enroll this course you will have a chance to learn both
- You will learn R and Python from scratch
- Learn Fundamentals of Python for effectively using Data Science
- 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
- Numpy arrays
- Series and Features
- 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
- Select columns and filter rows
- Arrange the order and create new variables
- Create, subset, convert or change any element within a vector or data frame
- Transform and manipulate an existing and real data
- 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
Welcome to Full Stack Data Science R and Python with Hands-on Projects 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 producemeaningfuloutcomes.
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.
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
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
Data Transformation in R
Transform and manipulate a deal data
Tidyverse and more
And we will do many exercises. Finally, we will also have 4 different final projects covering all of 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.
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 data science trends.
Video and Audio Production Quality
All our content is created/produced as high-quality video/audio to provide you the best learning experience.
You will be,
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!
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
Download Data Science with R and Python from below links NOW!
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