This course is specifically for S5 and S6 learners attending School. The field of Data Science combines digital and data skills, specific knowledge about a particular topic or subject area, and numeracy skills to extract insights and knowledge from data.
Course overview
This course is specifically for S5 and S6 learners attending School. The field of Data Science combines digital and data skills, specific knowledge about a particular topic or subject area, and numeracy skills to extract insights and knowledge from data.
The ability to identify the problem to solve, the correct data to use, carry out the analysis and then implement the outcome requires the three areas mentioned above to be brought together.
Data Science is becoming essential to how we live, learn and work. It is all about how we turn those insights extracted from data into actions. Many people are keen to learn more and understand this topic, and more employers are seeking applicants with experience in Data Science. Using the knowledge and skills from this course will help you to develop in your current or future job role.
The course has an 18-week structure and is guided by lecturer support via in-person or online learning. On successful completion of this course, you will gain a National Progression Award in Data Science at SCQF level 6.
What you will learn
Data Science is a multidisciplinary subject that combines, computer science, statistics and business knowledge. It allows the generation of insights from data.
This course will cover:
Data Management: Sorting and Analysing Data
An Introduction to Python Programming
Learn how to use industry-standard software such as Microsoft Excel.
Data in our Society: Elements of Data Security and How to Protect Your Own Data and Data Belonging to Other People
The Potential of Data Usage and Ethical Implications
How the course is assessed
This is a hybrid course where each group will have their own lecturer and the assessments will be released to students as each outcome of the course is delivered, assessments are in the form of coursework, project-based assignments and reports.
Edinburgh College was formed on 1 October 2012 as part of the merger of Edinburgh's Jewel and Esk, Telford, and Stevenson colleges. The college has four campuses, all of which were previously the campuses of the constituents of the merger:
On 17 April 2012, Edinburgh's Jewel and Esk, Telford, and Stevenson colleges collectively submitted to the Scottish Government a business case for their merger into a single "Edinburgh" college.
The merger was approved by the Scottish Ministers, and came into force on 1 October 2012. Edinburgh College values it’s rich history, especially those of the many legacy colleges that have come together over the years to better serve the learners of the Edinburgh and Lothian’s region.
A project is currently underway to collate the history of Edinburgh College and its legacy institutions and to create an archive of material to tell its story. Lots of interesting items have already been uncovered including old prospectuses, student newsletters, photographs and a log book from Ramsay Technical Institute dated 1923.
During this interactive Power BI training course, our engaging trainers will educate you of how to produce visually compelling and informative dashboards of your business’s performance data.
In this Power BI Course, you will learn how to translate data trends, summaries, statistics and insights from your data into powerful and inspirational Visualations. This course is ideal for managers and data analysts who need to make business decisions based on data.
This is a hands-on course. We give you plenty of time to play with what you are being taught and ask questions. Our expert instructors break the course into easily digestible sections so that we can make sure that no-one is left behind.
This course introduces Data Analysis Expressions (DAX) and provides you with foundational skills required to enhance data models with calculations.
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering etc.) and graphical techniques, and is highly extensible. It is available as free software.
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