Level 3 International Diploma (Data Science)

Data is everywhere. From the recommendations you see online and the way businesses predict customer behaviour to medical research, financial forecasting and artificial intelligence, organisations increasingly rely on people who can understand data and turn it into useful information.

This diploma introduces you to the technical and analytical foundations behind this rapidly developing field.

You will begin with What is Data and Data Science, establishing an understanding of what data science is and how data can be used to investigate questions and solve problems.

Programming is an important tool for modern data scientists. Through Introduction to Python Part 1 and Part 2, you will develop your knowledge of Python across two substantial six-credit modules, building the programming foundations needed to work with data computationally.

You will then explore how data can be understood mathematically. Data and Descriptive Statistics develops your knowledge of statistical approaches to data, while Foundation of Data Analytics introduces techniques for analysing information and drawing useful conclusions.

Artificial intelligence and machine learning form a major part of the programme. You will begin with Introduction to Artificial Intelligence, Machine Learning and Deep Learning, before progressing into Machine Learning Methods and Models and the more substantial Foundations of Machine Learning module.

Rather than simply learning what machine learning is, you will encounter specific approaches used within the field. Linear Regression introduces an important predictive technique, while Decision Trees explores another widely used approach to analysing data and making predictions.

K-means Clustering introduces unsupervised learning and the concept of grouping data according to similarities and patterns.

Data science is also about communicating what data tells us. Through Creating and Interpreting Visualisations, you will develop your ability to represent and understand data visually, while Introduction to Graphs provides a substantial exploration of another important way of representing data and relationships.

Alongside your technical subjects, Academic Study Techniques develops the independent learning and academic skills needed to make the transition into higher education.

The diploma comprises 60 Level 3 credits and 600 notional learning hours

There are no formal entry requirements for students applying for the Cambridge Online Education International Diplomas. Tutors are nevertheless, required to ensure that learners admitted onto the Diploma possess the necessary skills and personal qualities to cope with the demands of the course. We do expect candidates normally operate to at least Level Two in English and Level One in Mathematics - if this is a concern, we offer additional tuition to ensure these levels are met and can be taken forwards into assignments and to university applications. We also expect applicants show appropriate levels of commitment and motivation to have every success on their diploma.

All International Diplomas require the achievement of 60 credits. In terms of the length of time required for a learner to complete their diploma, for all International Diplomas the notional learning hours are 600. Notional learning hours comprise all learning that may be relevant to the achievement of the learning outcomes including directed and private study, practical and project work, assignments and assessment time. Your tutor will provide you with formative feedback and all units are PASS/FAIL. Your PASS grades will be then evaluated by the Examination Board. Final awards will be released to students after the External Moderation Visit.

On successful completion of the course, you will receive an accredited International Diploma at level 3, awarded by the Aim Qualifications and Assessment Group.

Aim Qualifications and Assessment Group are a national Awarding Organisation. Cambridge Online Education is a fully accredited education provider for this qualification.

Data skills are increasingly used across technology, finance, healthcare, science, engineering, business, marketing and government, making Data Science a highly versatile foundation for future university study and professional development.

Potential future career pathways include:

• Data Scientist
• Data Analyst
• Machine Learning Engineer
• Artificial Intelligence Engineer
• Data Engineer
• Business Intelligence Analyst
• Business Data Analyst
• Python Developer
• Software Developer
• Statistical Analyst
• Data Visualisation Specialist
• Machine Learning Analyst
• AI & Automation Specialist
• Financial Data Analyst
• Marketing Data Analyst
• Healthcare Data Analyst
• Research Data Analyst
• Risk Analyst
• Operations Analyst
• Data & Technology Consultant

The diploma can support progression towards university programmes such as Data Science, Artificial Intelligence, Machine Learning, Computer Science, Data Analytics, Business Analytics and related technology degrees, subject to individual university entry requirements.