Data Science with R Programming Certification Training Course

The prerequisites for Edureka's Data Science with R training include the fundamental understanding of Computer Programming Languages. However, you will be provided with complimentary “R Essentials” as a self-paced course once you enroll in the Data Science with R Programming certification course.

After completing this Data Science with R Programming Certification course, you will be able to:

Edureka offers the best online course for Data Science with R. Enroll now in our Data Science with R Programming training and get a chance to learn from industrial giants.

Data science is an evolutionary step in interdisciplinary fields like the business analysis that incorporate computer science, modelling, statistics and analytics. To take complete benefit of these opportunities, you need a structured training with an updated curriculum as per current industry requirements and best practices. Besides strong theoretical understanding, you need to work on various real-life projects using different tools from multiple disciplines to gather a data set, process and derive insights from the data set, extract meaningful data from the set, and interpret it for decision-making purposes. Additionally, you need the advice of an expert who is currently working in the industry tackling real-life data-related challenges.

Data Science Training will help you become a Data Science Expert. It will hone your skills by helping you to understand and analyze actual phenomena with data and provide the required hands-on experience for solving real-time industry-based projects.

During this Data Science course, you will be trained by our expert instructors to:

R has been one of the most widely used, premier, and powerful open-source languages that offers comprehensive libraries which provide interactive graphics and makes data visualization and representation easy to analyze. It has been used for over a decade to perform simple and complex mathematical and statistical calculations on data. R produces plots and graphics that are free of error. It continues to be a favorite choice for data scientists who build and use machine learning applications and other scientific computations. It has also evolved into the most preferred language for Data Science. The increasing search trends also indicate that it is a must for professionals delving into the Data Science domain.

Your system should have a minimum 4GB RAM and i3 processor or above.

For executing the practicals, you will set-up R programming IDE on your machine, you can:

The detailed step by step installation guides will be present in your LMS which will help you to install and set-up the required environment. In case you come across any doubt, the 24*7 support team will promptly assist you.

Edureka's Data Science Training includes real-time industry-based projects, which will hone your skills as per current industry standards and prepare you for the upcoming Data Scientist roles.

Project#1: Movies Collection

Industry: Entertainment Industry

Description: The goal of this Use-Case is to explore the movie dataset, given the parameters like: "duration", "movie title", "gross collection", "budget", "title year", etc. You will explore the following:

Project #2: Real Estate Price Prediction

Industry: Business Intelligence and Analytics

Description: The goal of this Use-case is to make predictions using Real Estate market data. The dataset contains the of the price of apartments in Boston. This data contains values such as "crime rate", "age", "accessibility", "population" etc. Based on this data, decide on the price of new apartments.

Project #3: Diabetes Prediction

Industry: Healthcare

b>Description: The Use-Case focuses on making predictions based on the patient’s characteristic data set, the dataset contains attributes such as "glucose level", "blood pressure", "age" etc. At last, the goal is to make a high accuracy machine learning model to predict, whether a patient is Diabetic or not.

Project #4: Recommendation System for Grocery Store

Industry: Food Retail Industry

Description: The Use-Case scenario is to create recommendations for customers of a grocery store based upon historical transaction data, which could recommend preferable articles.

Project #5: Twitter Analytics

Industry: Social Media Analytics

Description: This Use-Case focuses on social media analytics. The problem can be defined as Measuring, Analyzing, and Interpreting interactions and associations between people, topics and ideas. The dataset to be analyzed is captured by Live Twitter Streaming. You have to do the following:

Project #6: Air Passengers Forecasting

Industry: Commercial Aviation

Description: This Use-Case is about analyzing the data and applying time series model to forecast the number of bookings an Airline firm can expect each month. The dataset we will analyze contains monthly totals of international airline passengers between 1949 to 1960.You have to make informed decisions on staffing, hospitality and pricing for tickets.