You will learn to make use of the R language to access databases, clean, analyze, and visualize data with R. Through our guided lectures and access to labs, you will get hands-on experience tackling fascinating data issues. This's an action-packed learning path for data science enthusiasts who wish to work on real-life problems with R.
DataTrained
Access to 15 real life projects and a capstone project
Access to analyticsjobs.in curated jobs
IBM Watson labs and $1200 equivalent Cloud Credits
R is actually an effective language for data analysis, data visualization, machine learning, stats. Initially created for statistical programming, it's currently one of the most favored languages in data science.
With this program, you will be to learn about the fundamentals of R, and you will end with the confidence to begin writing your very own R scripts. But this is not your normal textbook launch to R. You are not only understanding about R fundamentals, but you will also be using R to resolve problems related to films data. A concrete case can make learning painless. You are going to learn about the basic principles of R syntax, which includes assigning variables and doing small activities with R's most crucial details structures -- vectors! From vectors, you will then learn about data frames, arrays, matrix, and lists. After that, you will leap into conditional statements, functions, debugging and classes. As soon as you have covered the fundamentals - you will find out about reading and writing data in R, whether it is a table format(CSV, Excel) or maybe a text file (.txt). Lastly, you will end with a few crucial functions for character strings as well as dates in R.
Course ContentData is among the most crucial assets of a company. Data must have a database to store and procedure information quickly. SQL is actually a language for a database to query information.
In this introductory program, you will master the fundamentals of the SQL language and also relational databases. You will start by understanding the relational style as well as relational model principles and constraints. By the end of this particular program, you'll have mastered and used the 5 fundamental SQL statements, several innovative SQL syntaxes, as well as join statements. This is not your normal textbook introduction. You are not only learning through lectures. At the conclusion of each module, you will find assignments, hands-on exercises, review concerns, and additionally a final examination. Successfully completing this program earns you a certificate. Why don't we get started!
Course ContentIt is going to introduce you to the profits of utilizing R with databases. Teach you exactly how to link directories from R. Teach you exactly how to make database items, populate the data source, as well as issue SQL queries to access and alter the data of yours from R. The program will even delve into complex subjects of using saved methods and utilizing in-database analytics with R
Course ContentThe curriculum has been designed by faculty from IITs and Expert Industry Professionals.
Hours of Content
Live Sessions
Tools and Software
Data Science is an approach to gain knowledge and deep insights from raw data through the application of statistics, mathematics, and computer science. Statistics is paramount to data science. That’s where R comes into play.
R is an open-source language and environment for statistical analysis and graphics. R is specifically designed for statistical analysis purposes. If you are interested in learning data science then R is for you. Few important things to know about R:
Python and R are both regarded to be quite simple to learn. Python was developed for software development. Python may come more readily to you than R if you have prior familiarity with Java or C++. R, on the other hand, may be a little easier only if you have a strong foundation in statistics.
Generally, Python's easy-to-understand syntax makes it easier to learn. R has a steeper learning curve at first, but it becomes substantially easier as users learn to use its capabilities.
We provide the best Certificate Course On Applied Data Science With R, therefore, you don’t have to think about whether R is hard to learn. Our curriculum and faculty make all the concepts digestible. If you have any questions, contact us, we would be happy to guide you.
We have witnessed how data is revolutionizing the world. Everyone should adapt to new technologies, otherwise, it will result in the fall of that entity. For instance, Nokia failed to innovate.
Applied data science certification opens the door for future opportunities. It not only helps you in your career but also upskills you for the future. Here is the list of a few careers in data science where you can apply data science:
Our data science professional certificate will significantly add weight to your resume. It will help you to upskill and make you ready for the future of data science.
For more information on the importance of data science, click here.
R with data science is an approach to extracting knowledge from data using the R programming language. R is a language made purely for statistical analysis. R environment is an integration of objects for data manipulation and data analysis.
R environment includes:
Data science and applied data science are not similar. Although it’s easy to use these words interchangeably. Let’s understand the difference in brief
Data scienceR is an open-source programming language and python is too. Both languages are significant in the world of data science. It’s important to know what programming languages will be effective to use in Data Science.
Python is a high-level programming language and it is the most popular programming language. There are a lot of libraries and modules in python. It is used across multiple disciplines :
R is also an open-source language like python, However, python is more specific to building statistical models. It depends on your goals and objectives. If you want to build a predictive model, in that case, Python is better. If you want to do data manipulation and exploration, then R would be your best choice.
No, programming is not hard, although, it has a steeper learning curve that means, at first, many people find it difficult to learn to code. However, after learning the basics of coding, they also find it very fun and interesting. Coding and programming are like learning a new language. Since code is a language too.
Data science certification course has been designed by faculty from IITs and Expert Industry Professionals. Therefore, you can go ahead and add remarkable credentials with these certifications.
For more information on coding, click here
An applied data scientist responsible for researching the application of data science into the different multiples. Not only he needs to find answers to where he can apply data science but also how it can be applied. Data science is the future and its increasing rapidly. According to the Forbes report, we have generated 90% of data in the last two years.
Data is fuel for industries and data science. Let's see the applications of data science:
For more detailed information, click here.
Yes, you can become an applied data scientist with an online course. Data science is easy to learn online since all you need is a computer. Other benefits of the online course include:
You’ll learn multiple tools and software with the programming language R. You will learn to make use of the R language to access databases, clean, analyze, and visualize data with R.
Programming and tools covered in this course will be
Our data science program curriculum has been designed by faculty from IITs and Expert Industry Professionals. Our mission is to provide quality education at an affordable cost with the best counseling sessions and industry interface.
Pathway of learning data science program:
You are eligible for a refund of the Booking Amount if you cancel your course within 7 calendar days of the Course Registration Date, which is the date of payment. However, this refund policy does not supersede any course-specific refund terms. Please consult your counselor for more information about the respective course's refund terms.