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• Data Analysis Fundamentals: This unit covers the essential concepts and techniques of data analysis, including data visualization, statistical analysis, and data mining. It provides a solid foundation for learners to understand the principles of data analysis and its applications in various industries.
• Data Preprocessing with KNIME: This unit focuses on the data preprocessing techniques using KNIME, a popular data science platform. Learners will learn how to clean, transform, and prepare data for analysis, and how to use KNIME's workflow-based approach to automate data preprocessing tasks.
• Data Visualization with KNIME: In this unit, learners will learn how to create interactive and dynamic visualizations using KNIME's visualization tools. They will understand how to design effective data visualizations, communicate insights, and tell stories with data.
• Predictive Modeling with KNIME: This unit covers the principles of predictive modeling using KNIME, including regression, classification, clustering, and decision trees. Learners will learn how to build and evaluate predictive models, and how to use KNIME's machine learning algorithms to make accurate predictions.
• Data Storytelling with KNIME: In this unit, learners will learn how to communicate insights and findings effectively using data visualization and storytelling techniques. They will understand how to create compelling narratives, identify key takeaways, and present findings to stakeholders.
• Data Mining with KNIME: This unit focuses on the techniques and tools used in data mining, including association rule mining, clustering, and decision trees. Learners will learn how to discover patterns, relationships, and insights in large datasets using KNIME's data mining capabilities.
• Advanced Data Analysis with KNIME: In this unit, learners will learn advanced data analysis techniques using KNIME, including time series analysis, text analysis, and network analysis. They will understand how to apply these techniques to real-world problems and how to use KNIME's advanced features to analyze complex data.
• Data Science with KNIME: This unit covers the principles and practices of data science using KNIME, including data wrangling, data visualization, and machine learning. Learners will learn how to apply data science techniques to real-world problems and how to use KNIME's data science platform to extract insights from data.
• Business Intelligence with KNIME: In this unit, learners will learn how to use KNIME to create business intelligence solutions, including data visualization, reporting, and dashboarding. They will understand how to design and implement effective business intelligence solutions using KNIME's workflow-based approach.
• Impact of Data Analysis on Business Decision Making: This unit focuses on the impact of data analysis on business decision making, including how to use data-driven insights to inform strategic decisions, optimize business processes, and improve operational efficiency. Learners will learn how to communicate data insights effectively to stakeholders and how to use data analysis to drive business growth and success.