GPPC- Artificial Intelligence and Data Science
Gain expertise in the fundamentals of data science and AI, focusing on data visualisation, cleansing, and analysis, while using Power BI to create engaging and informative dashboards.
Artificial
Intelligence and Data Science
With AI and Data Science course, student will get an opportunity to conduct real business research and developing analytics using AI and to work on real-world problem cases with ING Tech and Skill Museum and Research Hub.
Students will approach businesses lacking digital presence, create and manage their social media profiles, and implement effective digital strategies to help these businesses flourish online. They’ll also empower business owners by teaching them how to digitally market their products, making a real impact while gaining invaluable experience in the field.
ING Tech develops innovative software solutions that streamline and enhance educational institution operations.
Skill Museum and Research Center fosters learning and innovation in data science, machine learning, and AI.
Introduction to Data Visualization:
- Generate Meaningful Insights
- Exploring Data Visualization Tools
Data Preparation and Visualization:
- Data Cleaning and Preparation
- Data Analytics and Insights
PowerBI for Data Visualization:
- Creating Dashboards
- Data Import and Visualization
Data Collection Techniques and Tools:
- Understanding Bias
- Data Collection Process
- Data Cleaning and Validation
Spreadsheet for Data Visualization:
- Using Spreadsheets
Course Specification
- Module approved to run in 2024/2025
Course Title
- Artificial Intelligence and Data Science
Total Study Hours
- 12 hrs
Module Title
- Introduction to Data Visualisation
- Exploring Data Visualisation Tools
- PowerBI for Data Visualisation
- Understanding Data Collection Techniques
L01: Explain the role of data visualization 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 PowerBI to import data, create dashboards, and visualise data.
L10: Generate and interpret histograms, scatterplots, and regression lines in PowerBI.
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 PowerBI.
L16: Present data in a clear, actionable format suitable for stakeholders or decision-makers.
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