Qualification Overview

The qualification is a comprehensive program designed to equip individuals with essential skills for success in the dynamic field of data science. Students will delve into foundational concepts encompassing statistical analysis, machine learning, and data visualization. The curriculum places a strong emphasis on programming proficiency, with a focus on languages such as Python and R, enabling effective manipulation and analysis of diverse datasets.

Participants will also develop practical skills in data handling, covering techniques for collecting, cleaning, and preprocessing various datasets. The program explores the practical applications of machine learning algorithms for predictive modeling and data-driven decision-making. Additionally, students will gain familiarity with big data technologies, including tools like Apache Spark and Hadoop, essential for efficient large-scale data processing.

Ethical considerations and governance in data science are emphasized, addressing privacy, security, and responsible data use. The curriculum incorporates hands-on projects, allowing students to apply theoretical knowledge and build a portfolio showcasing their practical skills in real-world scenarios. Ultimately, the Higher International Diploma in Data Science aligns with industry demands, preparing graduates for roles such as data scientist or analyst by providing a well-rounded education and practical experience in this rapidly evolving field.

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Units

Learning Outcomes

• Foundational Mastery: Understand statistical analysis, machine learning, and effective data visualization.
• Programming Proficiency: Apply Python and R skills for diverse dataset manipulation and analysis.
• Data Handling: Acquire practical techniques for real-world data collection, cleaning, and preprocessing.
• Machine Learning Application: Implement algorithms for predictive modeling and data-driven decision-making.
• Big Data Technologies: Utilize tools like Apache Spark and Hadoop for efficient large-scale dataset processing.
• Ethics and Governance: Demonstrate awareness of ethical considerations and privacy issues in data science.
• Practical Projects: Apply knowledge through hands-on projects, showcasing practical skills.
• Industry-Ready: Possess skills aligned with industry demands for roles like data scientist or analyst.

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Entry Requirements

• Learners who possess Qualifications at Level 2 and/or;
• Learners who have work experience in a business environment and demonstrate ambition with clear career goals;
• Learners who possess a level 3 qualification in another discipline and want to develop their careers in business management.