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Data Analytics with R Rated 4.0/5 based on 122 customer reviews

Data Analysis with R Training in Seattle-WA, United States

Learn and polish your skills in techniques such as Predictive Analytics, Association Rule Mining and create your own functions, objects and packages

  • 30 hours of Instructor-led training
  • Beginner to Advanced level
  • Hands-on training
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Modes of Delivery

Key Features

30 hours of intensive mentoring
Engaging hands-on learning sessions
Acquire end-to-end knowledge on Data Analytics and R tools
Master core analysis concepts and apply in predictive data modeling
Enjoy the benefits of post-training assistance from our trainers
Get assistance from our trainers in implementing business analytics and mining techniques in real time projects

Description

Data Analytics training course

The open source programming language R has increased in popularity in recent years, and is now universally accepted by statisticians and data miners as the number one language for data science. R uses cutting-edge technology to manipulate data and create statistical models and charts that can be used for predictive modelling. It gives quick results and because it is open source, it is supported by a worldwide community of over two million users and developers. Zeolearn’s Data Analytics training will take you through the basics of this powerful language R. From the ground up, you will learn how to develop data for analysis and apply statistical measures to create data visualisations. By exploring the characteristics of data sets, you can analyse and achieve optimum results based on past data.

Data Analytics course at our institute will prepare you to handle complex, multifaceted projects and Data Analytics certification improves your career opportunities. Our academy also offers Data Analytics online coaching at affordable cost to the individuals who are not able to attend the classroom training. We have industry experts with great experience as trainers. Register now and prove your expertise to your potential employers.

Here’s what you will learn!

  • Learn to explore and visualize data and polish your skills in techniques such as Predictive Analytics, Association Rule Mining and much more
  • Derive meaning from custom created charts that are used to represent complex data, manipulate this data and create statistical models for predictive analysis
  • Learn to use R, not just as a statistical tool but to create your own functions, objects and packages

Is this course right for you?

Statisticians, Data Analysts, Business Analysts and professionals keen to learn more about the science and practice of data analysis using R, will benefit from this data analytics certification course.

What do you need to be familiar with?

  • Basic knowledge of a programming language such as Python or Java
  • A background in Mathematics will be beneficial

Curriculum

  1. R tools and their uses in Business Analytics
  2. Objectives
  3. Analytics
  4. Where is analytics applied?
  5. Responsibilities of a data scientist
  6. Problem definition
  7. Summarizing data
  8. Data collection
  1. Difference between R and other analytical languages
  2. Different data types in R
  3. Built in functions of R: seq(), cbind (), rbind(), merge()
  4. Subsetting methods
  5. Use of functions like str(), class(), length(), nrow(), ncol(),head(), tail()
  1. Steps involved in data cleaning
  2. Problems and solutions for Data cleaning
  3. Data inspection
  4. Use of functions grepl(), grep(), sub()
  5. Use of apply() function
  6. Coerce the data
  1. How R handles data in a variety of formats
  2. Importing data from csv files, spreadsheets and text files
  3. Import data from other statistical formats like sas7bdat and sps
  4. Packages installation used for database import
  5. Connect to RDBMS from R using ODBC and basic SQL queries in R
  6. Basics of Web Scraping
  1. Understanding the Exploratory Data Analysis(EDA)
  2. Implementation of EDA on various datasets
  3. Boxplots
  4. Understanding the cor() in R
  5. EDA functions like summarize()
  6. llist()
  7. Multiple packages in R for data analysis
  8. Segment plot HC plot in R
  1. Understanding on Data Visualization
  2. Graphical functions present in R
  3. Plot various graphs like tableplot
  4. Histogram
  5. Box Plot
  6. Customizing Graphical Parameters to improvise the plots
  7. Understanding GUIs like Deducer and R Commander
  8. Introduction to Spatial Analysis
  1. Introduction to Data Mining
  2. Understanding Machine Learning
  3. Supervised and Unsupervised Machine Learning Algorithms
  4. K-means Clustering
  1. Association Rule Mining
  2. Sentiment Analysis
  1. Linear Regression
  2. Logistic Regression
Anova
Predictive Analysis
  1. Decision Trees
  2. Algorithm for creating Decision Trees
  3. Greedy Approach: Entropy and Information Gain
  4. Creating a Perfect Decision Tree
  5. Classification Rules for Decision Trees
  6. Concepts of Random Forest
  7. Working of Random Forest
  8. Features of Random Forest

Frequently Asked Questions

This is the world of big data, and professionals who are well versed in data analysis and applied statistics are much sought after in companies across the globe. By discovering the important patterns in large quantities of data, companies can steer the direction of their work strategies and shape business success.R is a strongly functional programming language and environment that is used to statistically explore data sets. Increasingly popular in academia and industry circles, it has become the most important tool for statistical data science. This course gives a smooth transition into working with R, and gives you hands-on experience in working on a project that tests your knowledge and practical skills.
After completing our course, you will be able to:
  • Get a comprehensive understanding of the fundamentals of R
  • Know the steps needed to get started with R and the R Console
  • Have knowledge of Data types and Structures
  • Get an understanding of how to Explore and Visualize Data
  • Have familiarity with Programming Structures, Functions and Data Relationships
  • Get skills in techniques such as Predictive Analytics, Association Rule Mining and so on
Towards the end of the course, all participants will be required to work on a project to get hands on familiarity with the concepts learnt. You will perform predictive analyses on the provided data using R programming language. This project, which can also be a live industry project, will be reviewed by our instructors and industry experts. On successful completion, you will be awarded a certificate.
Classes are held on weekdays and weekends. You can check available schedules and choose the batch timings which are convenient for you.
You may be required to put in 10 to 12 hours of effort every week, including the live class, self study and assignments.
  • Your classes will be held online. All you need is a windows computer with good internet connection to attend your classes online. A headset with microphone is recommended.
  • You may also attend these classes from your smart phone or tablet.
Don’t worry, you can always access your class recording or opt to attend the missed session again in any other live batch.

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Data Analytics with R Course in Seattle-WA

Introduction

Seattle is one of the fastest growing major cities of the United States and is home to many multinational organisations. With companies like Microsoft and Amazon founded in the city, and Boeing as one of the first aircraft manufacturers there, the city has a booming economy.

About the course in the city

The raw industrial data can be put to many uses depending on how it came into existence and what kind of statistical analysis were it put through. These kinds of problems can be easily solved by various data analytics training courses in Seattle that’ll help you analyse the industrial data on a day to day basis and show what you’ve collected to the business managers. The zeolearn academy has come up with some exclusive data analytics courses in Seattle that are not only cost effective but also cover all the major topics required by the subject in a short time frame The workshop will be a great set to be added to your skill.

The data analytics certification in Seattle at Zeolearn institute will not only teach about the basics of data analytics and how to manipulate the data, it’ll also teach you how to predict the statistical analysis that needs to be applied on to the same based on visualization techniques. Most of the data analytics courses in Seattle also cover the R programming language as a part of their workshop as it is one of the most popular tools used for data analytics.

Customer satisfaction is crucial at Zeolearn which is why, all the courses are handled by expert trainers who hold live lectures with their audience as well as conducts practice sessions with the students for faster learning. If you’re unsatisfied with their coaching methods, you can always opt out of the workshop and get a reimbursement on your fee.

Here is what you learn

Our data analytics certification in Seattle offers

  • Fundamentals of business intelligence and data analytics
  • Fundamentals of the programming language R
  • Basics of the statistical and predictive analysis.

Objective of the course:

  • Learn about data and its underlying structure
  • How to use R language to manipulate and visualise data
  • Make use of data mining and data clustering techniques in everyday life
  • Polish your predictive analysis skills

Highlights of the course:

  • Live teaching sessions by expert tutors
  • You can decide upon your own schedule and always make time for your classes
  • Learn more about the topics with the help of various assignments

Is the course right for you?

People working in the field related to data sets and its manipulation, like business analysts, data analysts, and statistician are best suited for this course. The course will help you develop and intuition about the history of data and thus, its processing.

Prerequisites

The Zeolearn’s data analytics training in Seattle demands a basic understanding of programming languages like Python and Java as a prerequisite.

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