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Data Science with R Programming Certification Training Course
Data Science with R Programming Certification Training Course
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Why enroll for Data Science with R Certification?
Data Science with R Certification Training Benefits
The number of Data Science jobs is expected to grow by 30 % yearly. Knowledge of Data Science coupled with R programming skills opens up enormous opportunities for Data Science job aspirants. This Data Science with R training course from Edureka will teach you the essential concepts from scratch and enable you to launch your dream career in this domain.
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Why Data Science with R Certification from edureka
Live Interactive Learning
- World-Class Instructors
- Expert-Led Mentoring Sessions
- Instant doubt clearing
Lifetime Access
- Course Access Never Expires
- Free Access to Future Updates
- Unlimited Access to Course Content
24x7 Support
- One-On-One Learning Assistance
- Help Desk Support
- Resolve Doubts in Real-time
Hands-On Project Based Learning
- Industry-Relevant Projects
- Course Demo Dataset & Files
- Quizzes & Assignments
Industry Recognised Certification
- Edureka Training Certificate
- Graded Performance Certificate
- Certificate of Completion
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About your Data Science with R Certification
Skills Covered
Tools Covered
Data Science with R Course Curriculum
Curriculum Designed by Experts
Introduction to Data Science with R
10 Topics
Topics:
- What is Data Science?
- What does Data Science involve?
- Era of Data Science
- Business Intelligence vs Data Science
- Life cycle of Data Science
- Tools of Data Science
- Introduction to Big Data and Hadoop
- Introduction to R
- Introduction to Spark
- Introduction to Machine Learning
![skill]( "Hands On Experience")
- Data Science Tools
- Big Data with Hadoop and Spark
![skill]( "skill you will learn")
- Data Science with R
- Hadoop
- Spark
- Machine Learning
Statistical Inference
7 Topics
Topics:
- What is Statistical Inference?
- Terminologies of Statistics
- Measures of Centers
- Measures of Spread
- Probability
- Normal Distribution
- Binary Distribution
![skill]( "Hands On Experience")
- Statistical Techniques: Measures of Center Measures of Spread
- Probability Concepts
![skill]( "skill you will learn")
- Statistical Foundations
- Probability Distributions
Data Extraction, Wrangling and Exploration
7 Topics
Topics:
- Data Analysis Pipeline
- What is Data Extraction
- Types of Data
- Raw and Processed Data
- Data Wrangling
- Exploratory Data Analysis
- Visualization of Data
![skill]( "Hands On Experience")
- Loading different types of dataset in R
- Arranging the data
- Plotting the graphs
![skill]( "skill you will learn")
- Data Extraction
- EDA
- Data Visualization
Introduction to Machine Learning
5 Topics
Topics:
- What is Machine Learning?
- Machine Learning Use-Cases
- Machine Learning Process Flow
- Machine Learning Categories
- Supervised Learning algorithm: Linear Regression and Logistic Regression
![skill]( "Hands On Experience")
- Implementing Linear Regression model in R
- Implementing Logistic Regression model in R
![skill]( "skill you will learn")
- Machine Learning Process Flow
- Linear Regression model implementation
- Logistic Regression model implementation
Classification Techniques
8 Topics
Topics:
- What are classification and its use cases?
- What is Decision Tree?
- Algorithm for Decision Tree Induction
- Creating a Perfect Decision Tree
- Confusion Matrix
- What is Random Forest?
- What is Naive Bayes?
- Support Vector Machine: Classification
![skill]( "Hands On Experience")
- Implementing Decision Tree model in R
- Implementing Linear Random Forest in R
- Implementing Naive Bayes model in R
- Implementing Support Vector Machine in R
![skill]( "skill you will learn")
- Classification ML models implementation
Data Visualization in R
5 Topics
Topics:
- What is Clustering & its use cases
- What is K-means Clustering?
- What is C-means Clustering?
- What is Canopy Clustering?
- What is Hierarchical Clustering?
![skill]( "Hands On Experience")
- Implementing K-means Clustering in R
- Implementing C-means Clustering in R
- Implementing Hierarchical Clustering in R
![skill]( "skill you will learn")
- Unsupervised ML: Clustering models implementation
Recommender Engines
7 Topics
Topics:
- What is Association Rules & its use cases?
- What is Recommendation Engine & it’s working?
- Types of Recommendations
- User-Based Recommendation
- Item-Based Recommendation
- Difference: User-Based and Item-Based Recommendation
- Recommendation use cases
![skill]( "Hands On Experience")
- Implementing Association Rules in R
- Building a Recommendation Engine in R
![skill]( "skill you will learn")
- Association Rule Mining
- User-Based and Item-Based Recommendation
Text Mining
6 Topics
Topics:
- The concepts of text-mining
- Use cases
- Text Mining Algorithms
- Quantifying text
- TF-IDF
- Beyond TF-IDF
![skill]( "Hands On Experience")
- Implementing Bag of Words approach in R
- Implementing Sentiment Analysis on Twitter Data using R
![skill]( "skill you will learn")
- Text Mining Algorithms
- Sentiment Analysis
Time Series
8 Topics
Topics:
- What is Time Series data?
- Time Series variables
- Different components of Time Series data
- Visualize the data to identify Time Series Components
- Implement ARIMA model for forecasting
- Exponential smoothing models
- Identifying different time series scenario based on which different Exponential Smoothing model can be applied
- Implement respective ETS model for forecasting
![skill]( "Hands On Experience")
- Visualizing and formatting Time Series data
- Plotting decomposed Time Series data plot
- Applying ARIMA and ETS model for Time Series Forecasting
- Forecasting for given Time period
![skill]( "skill you will learn")
- Time Series Modelling
Deep Learning
9 Topics
Topics:
- Reinforced Learning
- Reinforcement learning Process Flow
- Reinforced Learning Use cases
- Deep Learning
- Biological Neural Networks
- Understand Artificial Neural Networks
- Building an Artificial Neural Network
- How ANN works
- Important Terminologies of ANN’s
![skill]( "Hands On Experience")
- Working of ANNs
![skill]( "skill you will learn")
- Reinforcement learning Process Flow
- Building Artificial Neural Networks
Data Science with R Programming Certification Course Description
About Data Science with R Training
Data science is a "concept to unify statistics, data analysis and their related methods" to "understand and analyze actual phenomena" with data. Edureka’s Data Science with R Certification Training employs techniques and theories drawn from many fields within the broad areas of mathematics, statistics, information science, and computer science from the sub-domains of machine learning, classification, cluster analysis, data mining, databases, and visualization. This training enables you to understand the entire life cycle of Data Science, analyze and visualize different datasets, implement various Machine Learning Algorithms such as K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes. Towards the end of this Data Science with R online course, we will be discussing various practical use cases of Data Science in several domains to enhance your learning experience.
What are the prerequisites for this Data Science with R Training?
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.
What are the objectives of our Data Science with R Training?
After completing this Data Science with R Programming Certification course, you will be able to:
- Understand the concepts and life-cycle of Data Science
- Apply various supervised machine learning techniques
- Learn how and where to use ML algorithms such as Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc.
- Explore Recommendation Systems with functions like Association Rule Mining,, user-based collaborative filtering and Item-based collaborative filtering among others
- Use various packages in R to create fancy plots
- Visualize and format Time Series data
- Understand Artificial Neural Networks
- Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights
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.
Why should you go for Data Science with R Training?
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.
What are the skills that you will be learning with our Data Science using R Training?
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:
- Gain insight into the 'Roles' played by a Data Scientist
- Analyze several types of data using R
- Describe the Data Science Life Cycle
- Work with different data formats like XML, CSV, etc.
- Learn tools and techniques for Data Transformation
- Discuss Data Mining techniques and their implementation
- Analyze data using Machine Learning algorithms in R
- Explain Time Series and it’s related concepts
- Perform Text Mining and Sentimental analyses on text data
- Gain insight into Data Visualization and Optimization techniques
- Understand the concepts of Deep Learning
Who should go for this Data Science with R online course?
- Programmers, Developers, Technical Leads
- Developers aspiring to be a ‘Machine Learning Engineer.'
- Analytics Managers who are leading a team of analysts
- Business Analysts who want to understand Machine
- Learning (ML) Techniques
- Information Architects who want to gain expertise in
- Professionals who want to design automatic predictive models
Why Learn R for Data Science?
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.
What are the system requirements for this Data Science with R Certification Training?
Your system should have a minimum 4GB RAM and i3 processor or above.
How will I execute the practicals in this Data Science with R Certification Training Course?
For executing the practicals, you will set-up R programming IDE on your machine, you can:
- Download RStudio Desktop Open Source License from the Rstudio Official Website for free
- Or, purchase the licensed Full- version of RStudio Desktop Commercial License
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.
Data Science with R Certification Projects
Industry: Entertainment
Explore the movie dataset, given the parameters like: "duration", "movie title", "gross collection", "budget", "title year", etc.Industry: Food Retail
Create a recommender engine for customers of a grocery store based upon historical transaction data, which could recommend preferable articles.Data Science with R Certification
To unlock Edureka’s Data Science with R Programming course completion certificate, you must ensure the following:
- Completely participate in this Data Science with R Certification Course.
- Evaluation and completion of the quizzes and projects listed.
Data Science is one of the most in-demand and highly-lucrative, and fastest-growing careers in computer science right now. It is constantly evolving and growing and you can apply it to many industries, including aviation, transport, as well as medical sciences. It is a highly sought-after job option, but it can be very competitive. Data Scientists who are interested in becoming certified can distinguish themselves from their competition by attending boot camps, submissions of code repositories and hands-on experience.
Beginners delving into Data Science need to get familiar with core mathematics, probability & statistics, and polish their basic programming skills in R. They can then move on to understanding Machine Learning concepts, Data Analysis, Visualization, and how to process complex data in large amounts using R. Edureka provides free articles and YouTube videos that will help you master these concepts and techniques.
The demand for professionals skilled in Data Science and R Programming is on the rise and there are many profitable employment possibilities and positions in tech organizations, making this the ideal time for candidates to enroll and earn a certification. Due to the wide range of job prospects and high demand, getting certified is an excellent way to showcase your skills as a Data Scientist and stand out. It's one of the most valuable entry-level certifications to pursue a career in Data Science.
Our Data Science with R certification course is designed to develop skills and evaluate candidates' knowledge. Following the completion of this certification, you will have access to a wide range of job possibilities. Some of the most important employment roles include Data Scientist, Machine Learning Engineer, Data Analyst, Data Engineer, Quantitative Analyst, and so on.
Please visit the page which will guide you through the top 50 R interview questions you must prepare in 2023.
John Doe
Title
with Grade X
XYZ123431st Jul 2024
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R Programming for Data Science Training FAQs
What if I miss a live Data Science with R Programming class?
You will never lose any lecture. You can choose either of the two options:
- View the recorded session of the class available in your LMS.
- You can attend the missed session, in any other live batch.
Will I Get Placement Assistance once the Data Science with R training is over?
To help you in this endeavor, we have added a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. You will have unlimited access to use these templates across different roles and designations. All you need to do is, log in to your LMS and click on the "create your resume" option.
What is the most recommended learning method after completing the Data Science with R Programming certification course?
Upon completing the Data Science with R Course, You can consider taking the Data Scientist Course.
Can I attend a Data Science with R Demo Session before Enrolment?
We have limited number of participants in a live session to maintain the Quality Standards. So, unfortunately participation in a live class without enrolment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in the class.
Who are the instructors at Edureka R Programming online course?
All the instructors at Edureka are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by Edureka for providing an awesome learning experience.
How do I become Data Science with R Programmer?
To become an R programmer, you require education in IT, Computer Science, or any related field. Once you have this, you can pursue an R certification for a more in-depth understanding.
What if I have more queries related to the R language certification course?
You can Call us at +91 98702 76457 /1844 230 6362 ( US Tollfree ) OR Email us at sales@edureka.co . We shall be glad to assist you.
What is R Programming used for?
R programming language is utilized to cleanse statistical computing graphics and analyze and display data. Enrolling in a Data Science with R course will allow you to learn about R and its applications in greater detail.
What are the other Data Science courses offered by Edureka apart from this?
Other Data Science courses offered by Edureka are:
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