Course Outline
- Rstudio IDE
- Data manipulation with dplyr, tidyr, reshape2
- Object oriented programming in R
- Performance profiling
- Exception handling
- Debugging R code
- Creating R packages
- Reproducible research with knitr and RMarkdown
- C/C++ coding in R
- Writing and compiling C/C++ code from R
Open Training Courses require 5+ participants.
Advanced R Training Course - Booking
Advanced R Training Course - Enquiry
Advanced R - Consultancy Enquiry
Consultancy Enquiry
Testimonials (1)
The flexible and friendly style. Learning exactly what was useful and relevant for me.
Jenny
Course - Advanced R
Upcoming Courses
Related Courses
Algorithmic Trading with Python and R
14 HoursThis instructor-led, live training in Canada (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.
By the end of this training, participants will be able to:
- Employ algorithms to buy and sell securities at specialized increments rapidly.
- Reduce costs associated with trade using algorithmic trading.
- Automatically monitor stock prices and place trades.
Programming with Big Data in R
21 HoursBig Data is a term that refers to solutions destined for storing and processing large data sets. Developed by Google initially, these Big Data solutions have evolved and inspired other similar projects, many of which are available as open-source. R is a popular programming language in the financial industry.
Introductory R (Basic to Intermediate)
14 HoursThis instructor-led, live training in Canada (online or onsite) is aimed at beginner-level data analysts who wish to use R programming to manipulate data, perform basic data analysis, and create compelling visualizations for insights.
By the end of this training, participants will be able to:
- Understand the basics of R Programming.
- Apply fundamental data science processes.
- Create visual representations of data.
Cluster Analysis with R and SAS
14 HoursThis instructor-led, live training in Canada (online or onsite) is aimed at data analysts who wish to program with R in SAS for cluster analysis.
By the end of this training, participants will be able to:
- Use cluster analysis for data mining
- Master R syntax for clustering solutions.
- Implement hierarchical and non-hierarchical clustering.
- Make data-driven decisions to help to improve business operations.
Data and Analytics - from the ground up
42 HoursData analytics is a crucial tool in business today. We will focus throughout on developing skills for practical hands on data analysis. The aim is to help delegates to give evidence-based answers to questions:
What has happened?
- processing and analyzing data
- producing informative data visualizations
What will happen?
- forecasting future performance
- evaluating forecasts
What should happen?
- turning data into evidence-based business decisions
- optimizing processes
The course itself can be delivered either as a 6 day classroom course or remotely over a period of weeks if preferred. We can work with you to deliver the course to best suit your needs.
Data Analysis with Python, R, Power Query, and Power BI
21 HoursThis instructor-led, live training in Canada (online or onsite) is aimed at beginner-level professionals who wish to clean and analyze data, make statistical projections, and create insightful visualizations using these tools.
By the end of this training, participants will be able to:
- Understand the basics of Python, R, Power Query, and Power BI for data analysis.
- Clean and organize datasets using Python and Power Query.
- Perform statistical analysis and projections with R.
- Create professional dashboards and reports with Power BI.
- Integrate and analyze data from multiple sources effectively.
Data Analytics With R
21 HoursR is a very popular, open source environment for statistical computing, data analytics and graphics. This course introduces R programming language to students. It covers language fundamentals, libraries and advanced concepts. Advanced data analytics and graphing with real world data.
Audience
Developers / data analytics
Duration
3 days
Format
Lectures and Hands-on
Data Mining with R
14 HoursR is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.
Data Mining & Machine Learning with R
14 HoursR is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.
Foundation R
7 HoursThis instructor-led, live training in Canada (online or onsite) is aimed at beginner-level professionals who wish to gain a mastery of the fundamentals of R and how to work with data.
By the end of this training, participants will be able to:
- Understand the R programming environment and RStudio interface.
- Import, manipulate, and explore datasets using R commands and packages.
- Perform basic statistical analysis and data summarization.
- Generate visualizations using both base R and ggplot2.
- Manage workspaces, scripts, and packages effectively.
Forecasting with R
14 HoursThis instructor-led, live training in Canada (online or onsite) is aimed at intermediate-level data analysts and business professionals who wish to perform time series forecasting and automate data analysis workflows using R.
By the end of this training, participants will be able to:
- Understand the fundamentals of forecasting techniques in R.
- Apply exponential smoothing and ARIMA models for time series analysis.
- Utilize the ‘forecast’ package to generate accurate forecasting models.
- Automate forecasting workflows for business and research applications.
Introduction to R with Time Series Analysis
21 HoursR is an open-source free programming language for statistical computing, data analysis, and graphics. R is used by a growing number of managers and data analysts inside corporations and academia. R has a wide variety of packages for data mining.
KNIME with Python and R for Machine Learning
14 HoursThis instructor-led, live training in Canada (online or onsite) is aimed at data scientists who wish to program in Python and R for KNIME.
By the end of this training, participants will be able to:
- Plan, build, and deploy machine learning models in KNIME.
- Make data driven decisions for operations.
- Implement end to end data science projects.
Marketing Analytics using R
21 HoursAudience
Business owners (marketing managers, product managers, customer base managers) and their teams; customer insights professionals.
Overview
The course follows the customer life cycle from acquiring new customers, managing the existing customers for profitability, retaining good customers, and finally understanding which customers are leaving us and why. We will be working with real (if anonymous) data from a variety of industries including telecommunications, insurance, media, and high tech.
Format
Instructor-led training over the course of five half-day sessions with in-class exercises as well as homework. It can be delivered as a classroom or distance (online) course.
Introduction to Data Visualization with Tidyverse and R
7 HoursThe Tidyverse is a collection of versatile R packages for cleaning, processing, modeling, and visualizing data. Some of the packages included are: ggplot2, dplyr, tidyr, readr, purrr, and tibble.
In this instructor-led, live training, participants will learn how to manipulate and visualize data using the tools included in the Tidyverse.
By the end of this training, participants will be able to:
- Perform data analysis and create appealing visualizations
- Draw useful conclusions from various datasets of sample data
- Filter, sort and summarize data to answer exploratory questions
- Turn processed data into informative line plots, bar plots, histograms
- Import and filter data from diverse data sources, including Excel, CSV, and SPSS files
Audience
- Beginners to the R language
- Beginners to data analysis and data visualization
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice