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Data Analytics with R Programming Certification Training
Data Analytics with R Programming Certification Training
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Instructor-led Business Analytics with R live online Training Schedule
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Why enroll for Data Analytics with R?
Data Analytics with R Certification Training Benefits
The number of Data Analytics jobs is expected to grow by 30% yearly. Knowledge of Advanced Analytics coupled with R programming skills opens up enormous opportunities for Data Analyst job aspirants. This Data Analytics 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 Analytics with R 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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Data Analytics with R Course Curriculum
Curriculum Designed by Experts
Introduction to Data Analytics
11 Topics
Topics:
- Introduction to terms Business Intelligence, Business Analytics, Data, Information
- How information hierarchy can be improved/introduced
- Understanding Business Analytics and R
- Knowledge about the R language, its community, and its ecosystem
- Understand the use of 'R' in the industry
- Compare R with other software in analytics
- Install R and the packages useful for the course
- Perform basic operations in R using the command line
- Learn the use of IDE R Studio and Various GUI
- Use the โR helpโ feature in R
- Knowledge about the worldwide R community collaboration
![skill]( "Hands On Experience")
- Install R and related packages
- R operations using command line
![skill]( "skill you will learn")
- IDE R-studio
- R operations
Introduction to R Programming
7 Topics
Topics:
- Various kinds of data types in R and their appropriate uses
- Built-in functions in R like seq(), cbind (), rbind(), merge()
- Knowledge of the various subsetting methods
- Summarize data by using functions like: str(), class(), length(), nrow(), ncol()
- Use of functions like head(), tail() for inspecting data
- Indulge in a class activity to summarize data
- dplyr package to perform SQL join in R
![skill]( "Hands On Experience")
- Data Types in R
- R Functions: seq(), cbind (), rbind(), merge(). str(), class(), length(), nrow(), ncol() head(), tail()
- SQL joins in R
![skill]( "skill you will learn")
- R Functions
- dplyr package in R
Data Manipulation in R
4 Topics
Topics:
- Steps involved in Data Cleaning
- Functions used in Data Inspection
- Tackling the problems faced during Data Cleaning
- Uses of the functions like grepl(), grep(), sub(), Coerce the data, uses of the apply() functions
![skill]( "Hands On Experience")
- Data Cleaning in R
- Data Inspection in R
- Data Coercion in R
![skill]( "skill you will learn")
- R Functions: grepl(), grep(), sub(), apply()
Data Import Techniques in R
6 Topics
Topics:
- Import data from spreadsheets and text files into R
- Import data from other statistical formats like sas7bdat and spss, packages
- Installation used for database import
- Connect to RDBMS from R using ODBC
- Basic SQL queries in R
- Basics of Web Scraping
![skill]( "Hands On Experience")
- Database import
- Connect to RDBMS using R
- SQL queries in R
- Web Scraping in R
![skill]( "skill you will learn")
- Database import
- R SQL queries
- Web Scraping
Exploratory Data Analysis
7 Topics
Topics:
- Exploratory Data Analysis(EDA)
- Implementation of EDA on various datasets
- Boxplots
- Understanding the cor() in R
- EDA functions like summarize(), llist()
- Multiple packages in R for data analysis
- Fancy plots like the Segment plot, and HC plot in R
![skill]( "Hands On Experience")
- EDA using R
- cor() in R
- Plotting fancy graphs using R
![skill]( "skill you will learn")
- EDA
- Plotting Graphs
Data Visualization in R
6 Topics
Topics:
- Data Visualization
- Graphical functions present in R
- Plot various graphs like tableplot, histogram, and Boxplot
- Customizing Graphical Parameters to improvise plots
- Understanding GUIs like Deducer and R Commander
- Introduction to Spatial Analysis
![skill]( "Hands On Experience")
- Graphical Functions in R
- Customizing Plots using R
- Spatial Analysis
![skill]( "skill you will learn")
- Data Visualization
- GUIs
- Spatial Analysis
Data Mining: Clustering Techniques
4 Topics
Topics:
- Introduction to Data Mining
- Understanding Machine Learning
- Supervised and Unsupervised Machine Learning Algorithms
- K-means Clustering
![skill]( "Hands On Experience")
- Data Mining
- Machine Learning Algorithms: Supervised Unsupervised
![skill]( "skill you will learn")
- Data Mining
- Machine Learning Algorithms
Data Mining: Association Rule Mining & Collaborative filtering
3 Topics
Topics:
- Association Rule Mining
- User Based Collaborative Filtering (UBCF)
- Item Based Collaborative Filtering (IBCF)
![skill]( "Hands On Experience")
- Association Rule Mining
- Recommender Engines: User Based Collaborative Filtering (UBCF) Item Based Collaborative Filtering (IBCF)
![skill]( "skill you will learn")
- Association Rules
- Recommender Engines
Linear and Logistic Regression
2 Topics
Topics:
- Linear Regression
- Logistic Regression
![skill]( "Hands On Experience")
- Linear Regression algorithm
- Logistic Regression algorithm
![skill]( "skill you will learn")
- Regression Techniques in R
Anova and Sentiment Analysis
2 Topics
Topics:
- Analysis of Variance (Anova) Technique
- Sentiment Analysis: fetch, extract and mine live data from Twitter
![skill]( "Hands On Experience")
- Anova
- Sentiment Analysis
![skill]( "skill you will learn")
- Anova Technique
- Sentiment Analysis on Twitter data
Data Mining: Decision Trees and Random Forest
9 Topics
Topics:
- Decision Tree
- Entropy
- Gini Index
- Pruning and Information Gain
- Algorithm for creating Decision Trees
- Bagging of Regression and Classification Trees
- Random Forest
- Working on Random Forest
- Features of Random Forest, among others
![skill]( "Hands On Experience")
- Decision Tree algorithm
- Working of Random Forest
![skill]( "skill you will learn")
- ML Algorithms: Decision Tree and Random Forest
Project Work
3 Topics
Topics:
- Analyze census data to predict insights on the income of the people based on the factors like age, education, work class, and occupation using Decision Trees
- Logistic Regression and Random Forest
- Analyze the Sentiment of Twitter data, where the data to be analyzed is streamed live from Twitter, and sentiment analysis is performed on the same
![skill]( "Hands On Experience")
- Decision Trees
- Logistic Regression
- Random Forest
- Sentiment Analysis
![skill]( "skill you will learn")
- Data Analysis using R
- ML Algorithms: Decision Tree, Logistic Regression and Random Forest
- Sentiment Analysis
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Data Analytics with R Course Description
About Data Analytics with R Training
Edurekaโs Data Analytics 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 Analytics and Data Science, analyze and visualize different datasets, implement various Machine Learning Algorithms such as Clustering, Regression, Decision Trees, and Random Forest. Towards the end of this Data Analytics with R online course, we will be discussing various practical use cases of Data Analytics in several domains to enhance your learning experience.
What are the prerequisites for this Data Analytics with R Training?
The prerequisites for Edureka's Data Analytics with R training include the fundamental understanding of Computer Programming Languages. Fundamentals of Data Analysis practiced over any data analysis tool like SAS/R will be a plus. However, you will be provided with complimentary โR Essentialsโ as a self-paced course once you enroll in the Data Analytics with R Programming certification course.
What are the objectives of our Data Analytics with R Training?
After completing this Data Analytics with R Programming Certification course, you will be able to:
- Understand concepts around Business Intelligence and Business Analytics
- Explore Recommendation Systems with functions like Association Rule Mining, user-based collaborative filtering and Item-based collaborative filtering among others
- Apply various supervised machine learning techniques
- Perform Analysis of Variance (ANOVA)
- Learn where to use ML algorithms such as Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc.
- Use various packages in R to create fancy plots
- 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 Analytics with R. Enroll now in our Data Analytics with R Programming training and get a chance to learn from industrial giants.
Why learn Data Analytics with R?
The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists.
Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career
Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course
Who should go for this Data Analytics with R online course?
- Programmers, Developers, Technical Leads
- Developers aspiring to be R programmers
- 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 Analytics?
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 Analytics. The increasing search trends also indicate that it is a must for professionals delving into the Data Analytics domain.
What are the system requirements for this Data Analytics 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 Analytics with R Certification Training Course?
For doing your practicals, you would need to install R set-up or R-Studio on your system. The step-wise installation guides for setting up the environment on various operating systems are present in the LMS. In case you come across any doubt, the 24*7 support team will promptly assist you.
Data Analytics with R Certification Projects
Sentiment Analysis on Twitter Data
Evaluate two different teams of IPL based on their social media popularity and the team which is more popular on twitter will be chosen for brand endorsement. The dataset to be a....Census Data Analysis
Analyze the census data and predict whether the income exceeds $50K per year. Follow end-to-end modelling process involving:- Perform Exploratory Data Analysis and est....
Data Analytics with R Certification
To unlock Edurekaโs Data Analytics with R Programming course completion certificate, you must ensure the following:
- Completely participate in this Data Analytics with R Certification Course.
- Evaluation and completion of the quizzes and projects listed.
- You must complete the course and earn a minimum score of 80% in the assessment.
Data Analytics is a constantly evolving domain and highly useful 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 Analysts 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 Analytics need to get familiar with different types of data and polish their basic programming skills in R. They can then move on to understanding Data Visualization, Decision Making, Machine Learning, Data Science, 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 Analytics 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 Analyst and stand out. It's one of the most valuable entry-level certifications to pursue a career in Data Analytics.
Our Data Analytics 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 Analyst, Data Scientist, R Programmer, Data Engineer, Quantitative Analyst, and so on.
Please visit the page which will guide you through the top Data Analytics with R Interview Questions and answers.
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Edureka is a revolution in Big Data training. I have taken 5 courses through Edureka from Hadoop, R, Data Science and Python. They have perfect materi...
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FAQ's
What if I miss a 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?
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.
Can I Attend a 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 Instructor at Edureka?
All our instructors are working professionals from the Industry and have at least 10-12 yrs of relevant experience in various domains. They are subject matter experts and are trained by Edureka for providing online training so that participants get a great learning experience.
What if I have more queries?
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.
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