GPPC - Artificial Intelligence and Data Science
Gain expertise in the fundamentals of data science and AI, focusing on data cleansing, data analysis, and data visualisation, while using Power BI to create engaging and informative dashboards.
Artificial Intelligence and Data Science
This course covers essential data collection techniques, from designing unbiased questionnaires to cleaning and validating datasets. Through hands-on work with real datasets, you'll develop the ability to spot trends, handle outliers, and present findings with confidence. By the end, students will have a solid foundation in data visualization and collection, skills that are increasingly essential across every industry.
ING Tech develops innovative software solutions that streamline and enhance the operations of educational institutions.
Skill Museum and Research Centre fosters learning and innovation in data science, machine learning, and AI.
Introduction to Data Visualisation:
- Generate Meaningful Insights
- Exploring Data Visualisation Tools
Data Preparation and Visualisation:
- Data Cleaning and Preparation
- Data Analytics and Insights
Power BI for Data Visualisation:
- Creating Dashboards
- Data Import and Visualisation
Data Collection Techniques and Tools:
- Understanding Bias
- Data Collection Process
- Data Cleaning and Validation
Spreadsheet for Data Visualisation:
- Using Spreadsheets
Course Specification
- Module Approved to Run in 2024/2025
Course Title
- Artificial Intelligence and Data Science
Total Study Hours
- 12 Hours
Module Titles
- Introduction to Data Visualisation
- Exploring Data Visualisation Tools
- Power BI for Data Visualisation
- Understanding Data Collection Techniques
L01: Explain the role of data visualisation in simplifying complex data for better decision-making.
L02: Identify different types of visual representations such as graphs, maps, infographics, and charts.
L03: Create bar graphs, pie charts, and line graphs from datasets.
L04: Analyse and interpret visual data to generate meaningful insights.
L05: Demonstrate basic data cleaning techniques such as handling missing values and removing outliers.
L06: Prepare datasets for analysis and visualisation using tools like Microsoft Excel.
L07: Use Excel to create various data visualisations (bar graphs, pie charts, line graphs, etc.) from real-world datasets.
L08: Perform basic data analysis in Excel and derive insights.
L09: Develop skills in using advanced tools such as Power BI to import data, create dashboards, and visualise data.
L10: Generate and interpret histograms, scatterplots, and regression lines in Power BI.
L11: Explain key data collection methods and the importance of avoiding bias in data collection.
L12: Use tools like Google Forms and spreadsheets to collect, verify, and clean data for visualisation.
L13: Perform data validation and cleaning processes, ensuring the integrity of the dataset.
L14: Apply basic visualisations using spreadsheets to communicate insights from collected data.
L15: Integrate multiple visualisations into dashboards for comprehensive data reporting using tools like Power BI.
L16: Present data in a clear, actionable format suitable for stakeholders or decision-makers.
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