Live R - a powerful programming language

This course is designed for beginners who want to learn R, a powerful programming language and environment for statistical computing and data analysis. Participants will acquire foundational R skills, understand data types, and learn how to manipulate and visualize data. By the end of this course, you'll be able to use R for data analysis, visualization, and basic programming tasks.

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9712 Learners

Comprehensive Curriculum

Our experienced trainers cover a wide range of topics in data science and analytics, including data cleaning and preprocessing, statistical analysis, machine learning, data visualization, and big data technologies.

Real-World Problem Solving

Focus on practical application. Students work on real-world projects and case studies to develop problem-solving skills.

Flexibility

Online format allows students to balance their studies with other commitments, such as work or college.

Hands-On Experience

Students typically have access to tools and platforms commonly used in the industry, allowing them to gain hands-on experience.

Networking

Facilitate networking opportunities with industry professionals and fellow students, which can be valuable for career growth.

Support

Students often have access to instructors and support resources to help them succeed in the program

Industry-Responsive Curriculum

No prior programming experience is required, but basic familiarity with statistics and data analysis concepts is beneficial.

This course outline covers a broad spectrum of R programming topics, from the fundamentals to more advanced subjects. Depending on your target audience and available time, you can adjust the depth and pace of the course accordingly. Additionally, consider incorporating hands-on exercises, examples, and real-world datasets to enhance the learning experience.

Course Summary

DURATION

1 Months

STRUCTURE

6 courses + Projects

ACCESS FOR

12 months

PRICING

$199 incl. GST

Rs 5,000 incl. GST

What you'll gain knowledge in

Introduction to R

Lesson 1: What is R?

• Introduction to R and its significance in data analysis.

Lesson 2: Installing R and RStudio

• Setting up your R development environment.

Lesson 3: R Basics

• Understanding R syntax, variables, and basic operations.

Lesson 4: R Data Types

Introduction to data types in R, including vectors, matrices, data frames, and lists.

Data Visualization

Lesson 1: Introduction to ggplot2

• Creating static and dynamic plots using the ggplot2 package.

Lesson 2: Basic Plots

• Creating bar plots, histograms, scatterplots, and line charts.

Lesson 3: Customizing Plots

• Customizing plot aesthetics, labels, and themes.

Lesson 4: Interactive Visualizations

• Introduction to interactive visualization libraries like Shiny.
  

Data Manipulation

Lesson 1: Data Import and Export

• Importing data from various sources (CSV, Excel, databases) and exporting results.

Lesson 2: Data Cleaning

• Handling missing data, dealing with outliers, and data transformation.

Lesson 3: Data Subsetting

• Selecting and filtering data based on criteria.

Lesson 4: Data Aggregation

• Summarizing and aggregating data using functions like aggregate and dplyr.
  

Basic Statistics with R

Lesson 1: Descriptive Statistics

• Calculating measures of central tendency, variability, and distribution.

Lesson 2: Hypothesis Testing

• Performing t-tests, chi-squared tests, and ANOVA.

Lesson 3: Regression Analysis

• Linear and logistic regression for predictive modeling.

Lesson 4: Exploratory Data Analysis (EDA)

• Strategies for exploring data and identifying patterns.
  

R Programming Fundamentals

Lesson 1: Control Structures

• Understanding loops (for, while) and conditional statements (if-else).

Lesson 2: Functions

• Writing custom functions for repetitive tasks.

Lesson 3: Error Handling

• Handling errors and exceptions in R code.

Lesson 4: Working with Packages

• Installing and loading R packages for extended functionality.

R Projects

Project 1: Real-world Data Analysis

Apply R skills to real datasets and projects.

Project 2: Group Projects

Collaborative data analysis projects with peers.

Advanced Topics

Lesson 1: Time Series Analysis

• Analyzing time-series data using R.

Lesson 2: Machine Learning with R

• Introduction to machine learning algorithms and libraries (e.g., caret, randomForest).

Lesson 3: Web Scraping with R

• Extracting data from websites using R.

Lesson 4: R for Big Data

• Working with large datasets using tools like SparkR and data.table.

FAQ's

What is the duration of each course in this training program?

This is a 4-week program, and the duration of each course may vary. Specific course durations can be found by clicking here.

Can I take multiple courses simultaneously, or do I need to complete one before starting another?

To ensure a manageable learning experience, it's important to consider the workload and prerequisites for each course. Based on this, we offer a sequential learning program.

Are there any prerequisites for these courses?

Prerequisites vary by course. Some may require prior knowledge or experience in the subject matter, while others are suitable for beginners. Be sure to review the course descriptions for detailed prerequisites and recommended skill levels.

Is this training program suitable for beginners with no prior experience in these subjects?

Yes, many of the courses are designed to accommodate beginners. Look for courses labeled as "introductory" or "foundations" if you're new to a particular subject.

What format are the courses offered in?

Courses are offered in an online format. Be sure to check the specific course format when registering.

Can I access course materials and resources after completing the training program?

Yes, the learning platform is accessible via the internet, and video content is not available for download. However, you can download files such as video transcripts, assignment templates, readings, etc., for maximum flexibility. You can access program content from a desktop, laptop, tablet, or mobile device. Video lectures must be streamed via the internet, and any livestream webinars and office hours will require an internet connection. However, these sessions are always recorded for later viewing.

Are there any assessments offered upon completion of the courses?

We conduct regular assessments, quizzes, or projects to evaluate your understanding of the course material. Check the course details for information on assessments.

What kind of support and assistance will I receive during the training program?

Support may include access to instructors, discussion forums, peer support, and additional learning resources. The level of support can vary, so review the specific course details to understand what's provided.

Is financial assistance or scholarships available for these courses?

We may offer financial assistance or scholarships based on eligibility. Assistance requests can be sent to contact@upathi.com .

How do I enrol in this training program, and what is the registration process?

To enrol in the training program, simply submit this form to get started with the registration process.

What technology or software will I need for these courses?

Depending on the course, you may need access to specific software or tools. The course descriptions should specify any technical requirements, and our trainers will assist in providing the required software during the course.

Are there any group discounts available for organizations or teams looking to enroll in these courses?

We do offer group discounts for organizations or teams. Contact us at contact@upathi.com to inquire about group rates and availability.

Can I receive a refund if I need to cancel my enrolment or if I'm not satisfied with the course?

You may request a full refund within five days of your payment or 3 days after the published start date of the program, whichever comes later. If your enrolment had previously been deferred, you will not be entitled to a refund. Partial (or pro-rated) refunds are not offered. All withdrawal and refund requests should be sent to contact@upathi.com .

What is the policy on deferrals?

After the published start date of the program, you have until the midpoint of the program to request a deferral to a future cohort of the same program. A deferral request must be submitted along with a specified reason and explanation. Cohort changes may be made only once per enrolment and are subject to the availability of other cohorts scheduled at our discretion. This policy will not be applicable for deferrals within the refund period, and the limit of one deferral per enrolment remains. All deferral requests should be sent to contact@upathi.com .