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Quality Enhancement

Women in Data & Digital Innovation (SCQF level 7)

Campus OL - Open Learning/Cross Campus

Qualification SCQF Level 7

Study mode Part time

Start date Jan 2025

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Course overview

Edinburgh College has launched a free course for Women who would like the opportunity to develop skills in Digital and Data Innovation.

Are you currently working with data and looking to reskill or upskill? Are you seeking a flexible study option that fits your job and comes at no cost to you?

The Digital and Data innovation programme is tailored to accommodate your lifestyle, entirely free to learn, and designed to meet the demands of the rapidly expanding tech industry. Employers are actively seeking data-savvy professionals to enhance their teams, making this award a valuable asset in your career toolkit. With a focus on industry-standard software like Power BI, this course equips you with the skills needed to harness the power of data across various industries including Engineering, Health and Social Care, Marketing, Software Development, Cybersecurity, Finance, and Retail.

At Edinburgh College, we offer a wide range of Data Science qualifications to meet your specific needs, on successful completion you will awarded a Professional Development Award (PDA) in Data Science at SCQF level 7.

About this Data Science Award:

The course is an 18-week programme designed to offer comprehensive guidance, available in both online and in-person learning formats.. Fully funded by The Data-Driven Innovation (DDI) Skills Gateway, upon successful completion, you will attain a Professional Award in Data Science at SCQF level 7. This award focuses on enhancing your effectiveness in your current or future job role, regardless of its technical nature.

During the course, you will strengthen your data skills, build statistical and communication capabilities relevant to data science, and enhance your analytical skills for extracting insights from datasets. You will develop essential meta-skills for lifelong learning and professional growth. The course is available either in-person at the Milton Road Campus or through live online sessions, ensuring an interactive experience in both formats, with online video lessons provided for flexible learning.

What you will learn

You will develop analysis and communication skills necessary for a data worker role gain proficiency in industry-standard software like Microsoft Excel and PowerBI, learn to create data models using large datasets, and explore AI applications relevant to learning, life, and work.

What you will learn

You will develop analysis and communication skills necessary for a data worker role gain proficiency in industry-standard software like Microsoft Excel and PowerBI, learn to create data models using large datasets, and explore AI applications relevant to learning, life, and work.

The course comprises three units:

Working with Data

  • You will understand the data analysis process and how to use data analysis tools to extract, transform and analyse data.
  • Basic statistical methods (such as correlation) will be introduced in context.
  • You will gain insights into large datasets using several data analysis tools and techniques to facilitate data-driven decision-making.

Communicating with Data

  • You will develop practical skills in the design and creation of a range of data visualisations and learn how to interpret visualisations created by others.
  • You will learn to select visualisations for different datasets and learn techniques for communicating data effectively and accurately.

Data Science Project

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

How the course is assessed

  • The course is structured to provide in-person delivery and live online lessons.
  • You have the option of attending our Milton Road campus or online. That also offers flexible learning through online video presentations using our online learning platform, Moodle, and Microsoft Teams.
  • 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

  • In-person at Milton Road Campus, Thursday, 09.30 to 12.30
  • Onine live session - Friday, 0930 to 1230
  • Online Flexible hours

(Note you will only attend one of the above options)

Entry requirements

  • Proficient in using Microsoft Office, particularly the spreadsheet application Excel, at an intermediate level.
  • One Higher or another SCQF level 6 qualification, or relevant experience.
  • The course is accessible to individuals with diverse qualifications and work/life experiences.
  • If you choose to learn online, your device must be a Windows-based PC or laptop; for example, a Mac or Chromebook will not be suitable

 

Information on Tests / Auditions / Interview Requirements

  • Completion of a personal statement at the application stage.
  • Initial assessment task

English Proficiency Requirements

IELTS 6.5

Progression and Articulation Routes

  • Upon fulfilling the prerequisites and completing a bridging course focused on Python programming, you may progress to the PDA Data Science (SCQF level 8) programme or other related qualifications.  
  •  Articulation routes include a Graduate Apprenticeship in Data Science and a BSc in Data Science.

Career options

  • For those starting their career, this is a gateway qualification to study at a higher level at college.
  • For those with previous work experience, this qualification provides a great addition to your CV.
  • Entry-level jobs in data science, data analytics or business analysis roles
     

Study Options

Campus Study mode Start date
OL - Open Learning/Cross Campus Part time 31/01/25

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