Data Science and Data Analytics

This course introduces the fundamentals of Data Science and Data Analytics, covering the complete data lifecycle, data collection, preparation, cleaning, exploratory data analysis, statistical methods, data visualisation, Python programming, predictive analytics and machine learning. It equips learners with practical knowledge and essential skills to analyse datasets, identify meaningful patterns, generate actionable insights and support data-driven decision-making.

Learning Objectives

By the end of the course, you will be able to:

• Explain the fundamental concepts, terminology and importance of Data Science and Data Analytics.
• Understand the complete data lifecycle, from data collection to interpretation and reporting.
• Collect, organise, clean and preprocess structured and unstructured data.
• Perform exploratory data analysis to identify patterns, trends and relationships.
• Apply basic statistical methods to analyse and interpret datasets.
• Create meaningful charts, visualisations, dashboards and analytical reports.
• Use Python and essential libraries for data analysis.
• Understand the fundamentals of machine learning and predictive analytics.
• Analyse real-world datasets and generate actionable insights.
• Apply data-driven approaches to solve problems across different sectors.

Why This Course Matters

• Builds a strong foundation in Data Science and Data Analytics.
• Develops practical skills in data collection, cleaning, preparation and analysis.
• Introduces Python and industry-standard libraries used by data professionals.
• Enhances understanding of statistical analysis and exploratory data analysis.
• Develops the ability to create effective visualisations and dashboards.
• Introduces machine learning, predictive analytics and business intelligence.
• Improves analytical thinking, problem-solving and decision-making skills.
• Provides practical experience through real-world datasets, demonstrations and case studies.
• Prepares learners for entry-level roles in data analysis, business intelligence and Data Science.
• Supports career pathways in agriculture, business, healthcare, research and the public sector.
• Equips learners to transform raw data into meaningful insights for informed decision-making.