50 Hrs
3712+ Enrollments
Data Science With R Training
This course is designed to help learners become proficient in R programming and data science. The course covers various topics, including data manipulation, visualization, exploratory data analysis, statistical inference, machine learning, and predictive modeling. The course is taught by industry experts and includes practical exercises and real-world case studies to help learners develop the skills and knowledge needed to succeed in the field of data science.
50 Hrs
3712+ Enrollments
Data Science With R Training
Data Science With R
Overview of Course
Data Science With R Training is a comprehensive online course designed to provide learners with a solid foundation in data science using the R programming language. This course covers everything from data manipulation and visualization to machine learning and statistical analysis, making it a must-have for anyone looking to start a career in data science.
Course Highlights
Comprehensive coverage of R programming and data science
Practical exercises and real-world case studies
Industry-relevant curriculum
Key Differentiators
Personalized Learning with Custom Curriculum
Training curriculum to meet the unique needs of each individual
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Trusted by over 100+ Fortune 500 Companies
We help organizations deliver right outcomes by training talent
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Flexible Schedule & Delivery
Choose between virtual/offline with Weekend options
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World Class Learning Infrastructure
Our learning platform provides leading virtual training labs & instances
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Enterprise Grade Data Protection
Security & privacy are an integral part of our training ethos
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Real-world Projects
We work with experts to curate real business scenarios as training projects
Skills You’ll Learn
#1
R programming
#2
Data manipulation and visualization
#3
Exploratory data analysis
#4
Statistical inference
#5
Machine learning
#6
Predictive modeling
Training Options
1-on-1 Training
On Request
Access to live online classes- Flexible schedule including weekends
- Hands-on exercises with virtual labs
- Session recordings and learning courseware included
- 24X7 learner support and assistance
- Book a free demo before you commit!
Corporate Training
On Request
- Everything in 1-on-1 Training plus
- Custom Curriculum
- Extended access to virtual labs
- Detailed reporting of every candidate
- Projects and assessments
- Consulting Support
- Training aligned to business outcomes
For Corporates
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- Choose customized training to address specific business challenges and goals, which leads to better outcomes and success.
- Keep employees up-to-date with changing industry trends and advancements.
- Adapt to new technologies & processes and increase efficiency and profitability.
- Improve employee morale, job satisfaction, and retention rates.
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- Obtain long-term organizational growth and success.
Course Reviews
Curriculum
- Data Types
- Introduction to Data Science Tools
- Statistics
- Approach to Business Problems
- An overview of Analytics
- Models and Algorithms
- Importance of Data Science
- Data Science as a Strategic Asset
- R, Python, WEKA, RapidMiner
- Overview of R
- Introduction to R
- Data Structures and Manipulation in R
- Installing R on Vsrious Operating Systems
- IDEs for R
- Steps in R Initiation
- Installing an R Package
- Overview of Business Analytics
- Introduction to Business Analytics
- Analytics Technology and Resources
- Need of Business Analytics
- Types and Features of Business Analytics
- Descriptive and Predictive Analytics
- Business Decisions
- Analytical Tools
- Data Science as a Strategic Asset
- Introduction
- Types of Graphics
- Save Graphics to a File
- Graphics in R
- Create a word cloud
- Exporting Graphs in EStudio
- Need of Hypothesis Testing in Businesses
- Chances of Errors in Sampling
- Level of Significance
- Types of Statistical Hypothesis Tests
- Test Statistic
- Types of Errors
- Use Normal and Student Probability Distribution Functions
- Objectives of Null Hypothesis Test
- Use Chi-Squared Test Statistics
- Introduction to Regression Analysis and Usage
- Types of Regression Analysis
- Interaction Regression Model
- Correlation
- Logit Function
- Lift charts
- Decile Analysis
- Introduction to Cluster Techniques
- Examples of Classification
- Classification Process - Model Construction
- Data Preparation Issues
- Basic Algorithm for a Decision Tree
- Decision Trees in Data Mining
- Naive Bayes Classifier
- Clustering Models
- Use Cases of Clustering
- DBSCAN Clustering Algorithm
- Distance Methodologies
- Hierarchical and Non-Hierarchical Procedure
- K-Means clustering
Contact Learning Advisor
Meet the instructor and learn about the course content and teaching style.- Make informed decisions about whether to enroll in the course or not.
- Get a perspective with a glimpse of what the learning process entails.
Description
Target Audience:
- Data analysts
- Business analysts
- IT professionals
- Graduates seeking a career in data science
Prerequisite:
- Basic knowledge of statistics
- Basic programming skills
Benefits of the course:
- Gain proficiency in R programming and data science
- Enhance your career prospects with in-demand skills
- Learn from industry experts
- Practical, hands-on learning experience
- Access to a community of learners and industry experts
- 24/7 online support
Exam details to pass the course:
- The course is self-paced and does not have a final exam.
- Learners will receive a certificate of completion upon finishing the course.
Certification path:
- Certified Data Scientist with R Programming by Data Science Council of America
- IBM Data Science Professional Certificate
- Microsoft Certified: Azure Data Scientist Associate
Career options after doing the course:
- Data scientist
- Data analyst
- Business analyst
- Machine learning engineer
- Data engineer
Why should you take this course from Skillzcafe:
Why should you take this course from Skillzcafe:
Industry-relevant curriculum- Taught by industry experts
- Practical, hands-on learning experience
- Access to a community of learners and industry experts
- 24/7 online support
- Affordable pricing
FAQs
Yes, this course is suitable for beginners with basic programming and statistics knowledge.
The course duration is 50 hours.
Yes, learners will receive a certificate of completion after finishing the course.
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