Data Science with R Certification Course

Data Science Certification Course Overview

The Data Science Certification with R programming training covers data exploration, data visualization, predictive analytics, and descriptive analytics techniques with the R language. You will learn about R packages, how to import and export data in R, data structures in R, various statistical concepts, cluster analysis, and forecasting.

What you'll learn

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  • Learn Research
  • Collect Usefull Data
  • Requirement Analysis Phase
  • Market competent Skills
  • Problem Solving Skills
  • Model Implementation Skills
  • Building or Developing Phase
  • Presenting and Testing Skills

    Course Includes:

  • 7+ hours on-demand video
  • 7+ articles
  • 20+ downloadable resources
  • Full access
  • Access on mobile and TV
  • Certificate of completion

Benefits

Whether you work for a small company, a large corporate or from home, a computer will be one of the first pieces of office equipment you’re going to need. And they comes in different forms, such as laptops and desktops. Computer skills are a valuable addition to any employee’s personal portfolio. Upskilling and polishing your computer literacy can greatly increase your desirability to employers. This is the perfect opportunity to take on roles you might not have previously considered. As an employer, motivating your employees to become computer literate will increase productivity and also stave off problems that can cost time and significant amounts of money. Many companies have started to depend upon computerised technology to get work done. Which is why computer skills have become increasingly important. Having the necessary and basic computer course knowledge will put you a step ahead of others. You’ll have a big advantage over those who aren’t computer literate. It’s for this specific reason that many schools and tertiary institutions encourage students to complete basic computer studies. Here are three reasons why being computer literate is beneficial in the workplace.

Helping professionals thrive, not just survive

Learning — Blended to Perfection

Learning — Blended to Perfection

Learning — Blended to Perfection

Course Inquiry

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Training Options

SELF-PACED LEARNING

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  • Lifetime access to high-quality self-paced eLearning content curated by industry experts
  • 4 hands-on projects to perfect the skills learnt
  • 2 simulation test papers for self-assessment
  • 24x7 learner assistance and support

BLENDED LEARNING

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  • Everything in Self-Paced Learning, plus
  • 90 days of flexible access to online classes
  • Live, online classroom training by top instructors and practitioners
  • 24x7 learner assistance and support

CORPORATE TRAINING

  • Blended learning delivery model (self-paced e-learning and/or instructor-led options)
  • Flexible pricing options
  • Enterprise grade Learning Management System (LMS)
  • Enterprise dashboards for individuals and teams
  • 24x7 learner assistance and support
  • 24x7 learner assistance and support

R Certification Course Curriculum

Eligibility

This Data Science online certification with R programming is beneficial for all aspiring data scientists including, IT professionals or software developers looking to make a career switch into Data analytics, professionals working in data and business analysis, graduates wishing to build a career in Data Science, and experienced professionals willing to harness Data Science in their fields.

Pre-requisites

There are no prerequisites for this Data Science Certification with R programming course. If you are a beginner in Data Science, this is one of the best courses to start with.

Course Content

Lesson 00 - Course Introduction
Course Introduction
Lesson 01 - Introduction to Business Analytics
1.001 Overview
1.002 Business Decisions and Analytics
1.003 Types of Business Analytics
1.004 Applications of Business Analytics
1.005 Data Science Overview
1.006 Conclusion
Knowledge Check
Lesson 02 - Introduction to R Programming
2.001 Overview
2.002 Importance of R
2.003 Data Types and Variables in R
2.004 Operators in R
2.005 Conditional Statements in R
2.006 Loops in R
2.007 R script
2.008 Functions in R
2.009 Conclusion
Knowledge Check
Lesson 03 - Data Structures
3.001 Overview
3.002 Identifying Data Structures
3.003 Demo Identifying Data Structures
3.004 Assigning Values to Data Structures
3.005 Data Manipulation
3.006 Demo Assigning values and applying functions
3.007 Conclusion
Knowledge Check
Lesson 04 - Data Visualization
4.001 Overview
4.002 Introduction to Data Visualization
4.003 Data Visualization using Graphics in R
4.004 ggplot2
4.005 File Formats of Graphic Outputs
4.006 Conclusion
Knowledge Check
Lesson 05 - Statistics for Data Science-I
5.001 Overview
5.002 Introduction to Hypothesis
5.003 Types of Hypothesis
5.004 Data Sampling
5.005 Confidence and Significance Levels
5.006 Conclusion
Knowledge Check
Lesson 06 - Statistics for Data Science-II
6.001 Overview
6.002 Hypothesis Test
6.003 Parametric Test
6.004 Non-Parametric Test
6.005 Hypothesis Tests about Population Means
6.006 Hypothesis Tests about Population Variance
6.007 Hypothesis Tests about Population Proportions
6.008 Conclusion
Knowledge Check
Lesson 07 - Regression Analysis
7.001 Overview
7.002 Introduction to Regression Analysis
7.003 Types of Regression Analysis Models
7.004 Linear Regression
7.005 Demo Simple Linear Regression
7.006 Non-Linear Regression
7.007 Demo Regression Analysis with Multiple Variables
7.008 Cross Validation
7.009 Non-Linear to Linear Models
7.010 Principal Component Analysis
7.011 Factor Analysis
7.012 Conclusion
Knowledge Check
Lesson 08 - Classification
8.001 Overview
8.002 Classification and Its Types
8.003 Logistic Regression
8.004 Support Vector Machines
8.005 Demo Support Vector Machines
8.006 K-Nearest Neighbours
8.007 Naive Bayes Classifier
8.008 Demo Naive Bayes Classifier
8.009 Decision Tree Classification
8.010 Demo Decision Tree Classification
8.011 Random Forest Classification
8.012 Evaluating Classifier Models
8.013 Demo K-Fold Cross Validation
8.014 Conclusion
Knowledge Check
Lesson 09 - Clustering
9.001 Overview
9.002 Introduction to Clustering
9.003 Clustering Methods
9.004 Demo K-means Clustering
9.005 Demo Hierarchical Clustering
9.006 Conclusion
Knowledge Check
Lesson 10 - Association
10.001 Overview
10.002 Association Rule
10.003 Apriori Algorithm
10.004 Demo Apriori Algorithm
10.005 Conclusion
Knowledge Check

Course Training Session FAQ'S

IT Nuggets Online is a progressive IT company engaged in creating eye-grabbing computer-based content in English, for the benefit of students. we offer learning process that blends texts, visuals, animation, video clips, and sound to give a complete learning experience to students.
Everyone Take an Online Classes in Your Flexible Times.
Yes, You Can Enroll More Than Courses.
After Meeting the Certification Criteria Explained By Instructor which will be contain some quiz and hands on exercise then definitely you will get certification.