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FREDERICK UNIVERSITY
Course Information
Thematic Area
AI and Ethics
Study Format
Online
Course Type
Microcredential
Date
TBA
Sync Hours
5-10
Async Hours
40-45
Sectors
Information and Communication Technologies (ICT); Financial Services and Insurance; Retail and E-commerce; Healthcare and Life Sciences; Manufacturing
EQF Level
5
SDGs
SDG 4 – Quality Education; SDG 9 – Industry, Innovation and Infrastructure
Course Description
Hands-on analytics using Python tools (Pandas, NumPy, Matplotlib, Scikit-learn, PySpark) on cloud platforms. Learners execute the full data analytics pipeline: preparation, EDA, model development/evaluation, and data storytelling with dashboards and narratives to support data-driven decisions.
Assessment
Self-Assessment Quizzes; Practical Lab Exercises; Assignments; Essays/Reports; Knowledge Checks; Final Exam (Online); Case Studies; Projects
Study Methods
Lectures; Videos; Hands on Labs; Practical Labs; Case Studies; Live Code Demos; Code Reviews; Literature Reading
Learning Outcomes
Understand the Data Analytics Lifecycle; apply data cleaning and transformation in Python; manipulate/visualise datasets with Matplotlib/Seaborn; analyse patterns with EDA; build/evaluate basic classification models; synthesise reports/dashboards; design end-to-end analytics pipelines; communicate results to non-technical audiences.
Hard Skills
Cloud computing architecture; Big Data processing; Data Analytics Lifecycle; ETL/ELT; EDA; Regression modelling; Data visualisation & dashboarding
Soft Skills
Problem-solving; Digital literacy; Communication; Adaptability to new toolsets
Related Courses
Microcredential
Microcredential
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