Course Schedule
Introduction:
This course provides a comprehensive introduction to the fundamentals of programming using R, designed to build a strong foundation for learners with little or no prior programming experience. It explores the essential principles, concepts and syntax of the R programming language, gradually developing learners’ confidence and understanding through introductory practical applications. Learners will be introduced to writing, executing and interpreting R code, working with different data types and structures, manipulating and organising datasets, and performing fundamental data analysis tasks. By the end of the course, learners will have developed an initial understanding of the R programming environment and acquired the foundational programming skills needed to explore data, solve basic problems and progress towards more advanced applications of R.
Prerequisite:
Not required.
Qualifications Scotland (QS) Framework:
This course is fully aligned with the PDA (Professional Development Award) in Data Science (QS) at SCQF Level 7, providing learners with a valuable opportunity to gain a recognised qualification while developing their knowledge and skills in the rapidly growing field of data science. The programme offers a substantial learning opportunity, with learners eligible to achieve an impressive total of 32 SCQF credits upon successfully completing and passing all relevant examinations and assessment requirements. This achievement represents a significant step towards strengthening learners’ academic and professional credentials, enhancing their understanding of data science, and supporting progression into further study, professional development and career opportunities within the data-driven economy.
Course Objectives:
Hands-on Experience:
This course places a strong emphasis on practical, hands-on learning, enabling learners to develop foundational R programming skills through engaging exercises and real-world data applications. Using the R programming language, RStudio and relevant datasets, learners will gain practical experience in exploring, importing, organising, cleaning, transforming and analysing data. Through a series of guided activities and practical exercises, learners will develop confidence in writing, running and interpreting R code, working with different data types and structures, and applying basic programming techniques to solve introductory data-related problems.
Learners will also gain experience in manipulating datasets using R, working with data frames, importing and exporting Excel and CSV files, performing basic statistical operations, and creating meaningful data visualisations using tools such as ggplot2. By the end of the course, learners will have acquired essential introductory R programming skills and developed the confidence to work independently with datasets, conduct basic data analysis, identify patterns and trends, and communicate their findings through clear, informative visualisations and reports.
Why Should You Attend This Course?
1. Explore the World of R Programming: If you are curious about programming, data analysis and data science and want to discover how R can be used to explore, manipulate and interpret data.
2. Develop Your Foundational R Programming Skills: If you are new to R programming or have some initial experience and want to strengthen your understanding of its core concepts, functions and practical applications.
3. Pursue a Career in Data Science: If you aspire to work in data-related roles, such as a Junior Data Analyst, Data Technician or other entry-level data science positions where R programming and analytical skills are valuable.
4. Enhance Your Data Analysis Capabilities: If you want to develop practical skills in data manipulation, data visualisation, statistical analysis and working with real-world datasets using R.
5. Gain an Industry-Relevant Qualification: If you want to strengthen your academic and professional profile through a Professional Development Award (PDA) in Data Science (QS) at SCQF Level 7.
6. Build Skills for a Data-Driven World: If you want to develop the essential programming and analytical skills needed to understand, organise, interpret and communicate data effectively in today’s increasingly data-driven workplace.
7. Progress Towards Further Learning: If you want to establish a solid foundation in R programming and data science that can support progression towards more advanced programming, statistical analysis and data science studies.
8. Earn Valuable SCQF Credits: If you want to work towards achieving the 32 SCQF credits associated with the PDA Data Science (QS) qualification, subject to successfully completing all relevant assessments and examinations.
Classes Duration:
This is a 16-week introductory R Programming and Data Science course designed to develop essential programming and data analysis skills.
Learning Modes:
ITPT is currently providing different method of learning opportunities to students. Many people are looking for learning diversity to enhance their qualifications, but they don’t have the time to take on full-time instructor led study or attending courses regularly at their appropriate venues.
| Modes of Course Delivery | Modes of Attendance |
| 1. Face to Face – Tutor Led learning | 1. Weekends |
| 2. Virtual – Tutor Led learning | 2. Weekdays |
| 3. Blended learning | 3. Part time |
| 4. eLearning | 4. Day Release |
Our Courses & Training Classes Suit the Following
Target Audience:
This course covers the foundational knowledge and practical skills associated with R programming and the SQA PDA Data Science (QS) qualification at SCQF Level 7. It is suitable for learners seeking to develop introductory programming, data analysis and data visualisation skills, whether to improve their employment prospects, prepare for further study or support career advancement.
Our R Programming and Data Science training classes are suitable for a wide range of candidates, including:
Contact Us:
For more information please do contact us:
Edinburgh Phone: 0131 552 5558
Email: info@itpt.co.uk
Contact us via website: https://www.itpt.co.uk/contact-us/
To Book an Appointment with Course Advisors:
To Book course registration or for further information about the course or its funding, please follow the below link;
https://tinyurl.com/ITPT-Appointment
