Introduction to Data Storytelling with Excel (SCQF level 5)

Course overview

An Introduction to Data Storytelling with Excel course is tailored to accommodate your lifestyle, entirely free to learn, and designed to meet the demands of the rapidly expanding tech industry. On successful completion, you will awarded a National Progression Award in Data Science (NPA) in Data Science at SCQF level 5.

Data Science is fast becoming an essential part of how we live, learn and work, including the demand for data science as an employability skill. More and more employers are seeking applicants with experience and skills in data science. For example, data science is used to help businesses make better decisions; data science is also used in sports to help teams analyse their performance. It is expected that there will be many jobs in this area in the coming years. Everyone, no matter your job, will require some knowledge of data science. It is also a useful skill for your future learning, no matter what subject interests you.

About this Data Science Award:

• The course spans 18 weeks and is structured to provide comprehensive guidance through a weekly live online class.
• The course is fully funded by The Data-Driven Innovation (DDI) Skills Gateway
• You will attain an NPA in Data Science at SCQF level 5.

You will gain a range of practical skills and acquire relevant underpinning knowledge, learn how to interpret meaning from visualisations, such as graphs and charts, and create visualisations from data. You will learn about how data can be used in society for positive and negative effects. You will also learn about data security and their rights and responsibilities as data subjects and data owners

What you will learn

Data Science is a multidisciplinary subject that combines computer science, statistics, and business knowledge, enabling the generation of insights from data.

The course comprises three units across the 18-weeks

Data Science:

Suitable for everyone, particularly if you require data skills before commencing university or employment. The unit covers several topics relating to data science including the reasons for the emergence of data science as a distinct discipline, the uses and misuses of data and data science, the data science life cycle and common methods of data analysis. You will also gain practical skills in using software to identify patterns and trends in data.

Data Citizenship:

You will gain a range of practical skills and acquire relevant underpinning knowledge. You will learn how to interpret meaning from visualisations, such as graphs and charts, and to create visualisations from data. You will learn about how data can be used in society for positive and negative effects. You will also learn about data security and their rights and responsibilities as data subjects and data owners

Data Science Project:

You will work as a group to complete an end-to-end data science project. This will involve deciding the problem that you will address, understanding the importance of the problem in a project brief, jointly planning how you will carry out the project, collecting and analysing the data and communicating the findings. You will document the decisions and findings as you go, to create a group portfolio that constitutes your data science project

How the course is assessed

• The course is structured to provide a flexible approach to learning, this course is online with live classes delivered by a lecturer. 
• Assessment work consists of project-based tasks that will be released weekly, requiring an estimated 4-6 hours per week depending on your experience level.

Number of days per week

• Online Live Class, Tuesday, 09.30 AM to 12.30 PM 

Entry requirements

• Comfortable using Microsoft Office, particularly spreadsheet packages.
• SCQF level 4 qualification, or relevant experience.
• The course is accessible to individuals with diverse qualifications and work/life experiences.

Information on Tests / Auditions / Interview Requirements

• Completion of a personal statement at the application stage.

English Proficiency Requirements

Progression and Articulation Routes

On successful completion of this course and depending on your other skills you could gain entry to the following courses:

• NPA Data Science SCQF level 6
• NPA Software Development and Web/Digital Design
• NPA Cyber Security and Networking
• Graduate Apprenticeship in Data Science

Career options

• This qualification provides a great addition to your CV.
• A course for further course progression
• Data science jobs can include data analyst, systems analyst, data scientist, and software engineer.