Introduction to Data Science with Python
Explore the techniques available and issues surrounding the use of Python in data processing.
Topics
- The Data Science lifecycle; frameworks for data science projects, and data strategies.
- Professional, ethical and legal issues involved within data analysis; data bias.
- Data exploration, data preparation and data cleaning methods.
- Data summarisation, data transformation and data visualisation techniques.
- Introduction to and use of Python libraries to process and analyse a range of data types, and to apply data science algorithms to datasets.
- Statistical techniques for data analysis: summary statistics; visualising data distributions; regression; correlation; clustering; classification.
On completion of this short course, students will be able to:
- Develop awareness of the data science lifecycle and data strategies.
- Develop awareness of the professional, ethical and legal issues within data analysis.
- Apply methods for cleaning and preparing data for analysis.
- Apply statistical and visualisation techniques to a variety of datasets.
- Apply algorithms to extract information from a dataset.
- Effectively communicate results through appropriate conclusions and visualisation.
RGU Upskilling
Undertaking a RGU online short course can help you to develop or change your career or support your business to grow.
We're proud to offer a range of online short courses tailored to meet the evolving needs of businesses and individuals in Scotland. If you are domiciled in Scotland, you will be eligible for a fee-waiver place, meaning you can study for free. Identified and created in collaboration with industry, these 15-credit online courses are designed to enhance employability for individuals and organisations looking to upskill their workforce.
Find out more about the range of courses on offer and the benefits of studying online with RGU:
This short course can be completed in 10 weeks. With 8 weeks to complete the online materials and exercises, and 2 weeks to apply techniques learned to a small capstone project.
Teaching
8 weeks of teaching/learning activity as follows:
- Recorded Lectures: approximately 2 hours/week in total, presented as short bite-sized (20-30 minute) lessons
- Practical exercises: a range of guided exercises applying the techniques and principles covered in lectures learning to use and apply Python to load, analysis and visualise data.
Assessment
- Regular formative quizzes to check your understanding and progress.
- A capstone project to bring together elements of the course, applying steps of the data science lifecycle to a dataset (which could optionally be workplace based) and presenting the analysis and conclusions in the form of a short report.
Independent Study
- Materials and exercises are available online, allowing participants to study flexibly and independently at time and place to fit around existing work and life commitments.
- Online tutor support and recorded code-along solutions to practical exercises.
Staff Delivering on This Course
The School has a strong history of successful, data-rich, industry and research projects in AI, applying Data analytics, Data Mining, Machine Learning, Evolutionary Computing and Optimisation techniques to areas such as energy, health care, transport, high performance computing, medicine and tourism.
Staff have developed and delivered a number of courses in the field at all levels, from BSc (Hons) to MSc to PhD. Current courses include the MSc in Data Science, the MSc IT with Business Intelligence and the BSc (Hons) in Data Science.
Staff are recognised for their Teaching and Support, with a number of staff receiving STAR awards year on year.
Data Science and Analytics is a fast-growing area of investment for businesses and organisations who want to obtain a competitive advantage by:
- Extracting and understanding the knowledge implicitly contained in data.
- Using this knowledge to strategically make and justify improved business decisions, e.g.
- Predict outcomes.
- Diagnose faults.
- Reduce lead/response time.
Python is used extensively in business and industry, and experience in using Python is a valuable and sought after skill.
Problem solvers who can draw value from business data are highly sought after for solving an ever increasing number of challenges in a data-rich world. Individuals with practical data analytics skills are well placed to make a difference in the creative solving of real-world problems.
Find out moreRGUflex
There are no prerequisites for this course.
Academic Year 2024/2025
Fee-waiver places
If you are domiciled in Scotland, you may be eligible for a fee-waiver place, meaning you can study for free.
To meet the requirements to be allocated a funded place, applicants must meet the criteria to be assessed as "Home" for the purposes of fees. Find out more about the Fee Status and the Scottish Government regulations that we use to make our assessment:
Eligibility is assessed on application and further evidence may be required.
All other applicants
Applicants who are not eligible for a fee-waiver place can pay to study the course - £500 for the entire course
Additional Costs
Some other costs are not included in the course fees:
Disclaimer
For new intakes, course fees are reviewed and published annually for each mode of delivery. Tuition fees are fixed for the duration of a course at the rate confirmed in the offer letter. For further information:
Any Questions?
Get in touch with the team and we'll do our best to help.