The sources define workplace ethics as values guiding behavior and relationships at work, underpinned by six principles: honesty, respect, confidentiality, diligence, fairness, and responsibility. These ethics are vital for creating stable, efficient environments and ensuring professional conduct. Common employer-employee conflicts arise from working hours, performance vs. ethics, welfare expectations, and loyalty.
For employees, advice includes maintaining professionalism, protecting rights, communicating rationally, and valuing integrity over immediate gains, fostering passion in their work. The "loss is gain" philosophy suggests that short-term sacrifices build better relationships, learning opportunities, and intangible assets. Supervisors are advised to enhance communication, value employees, ensure fairness, lead by example, and create meaningful work. The text also addresses generational differences, where older perspectives on hard work clash with newer emphasis on work-life balance; mutual understanding is key to resolving this.

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This content provides an insightful overview of 3D media design, highlighting its high entry barrier and significant costs for training 3D designers, with a single designer potentially costing over 5 million NTD to cultivate. 3D technology is widely applied in fields like film, television, games, architecture, and medical imaging. Key aspects of 3D design include modeling, rendering, and animation.
SketchUp is introduced as an intuitive direct modeling software suitable for beginners and architectural design. It enables users to perform basic 3D operations such as drawing lines, rectangles, and circles, and then creating 3D shapes using the Push/Pull tool. The content details essential mouse operations like orbiting (O), panning (H), and zooming (Z), along with keyboard shortcuts for various tools. Crucial steps in model creation cover setting length units and precision, grouping objects, and adding materials and textures using the paint bucket tool. Advanced concepts like rendering (ray tracing, shadows, reflections), animation techniques (keyframe, path animation, camera control), and physics simulations (subdivision, physical dynamics, particle systems) are also explained, emphasizing their role in achieving realism. The lesson includes practical exercises for creating a house, a swimming pool, and 3D text. While AI is evolving, customization and object-oriented control remain crucial in professional 3D production, making human expertise indispensable. Users are taught to create dynamic camera scenes and export short video clips of their 3D models.

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3D media is a transformative field widely utilized across diverse sectors, including movie and TV production, video game development, architecture and product visualization, medical imaging, and virtual and augmented reality. The foundational knowledge of 3D design encompasses 3D modeling, rendering, animation, materials, and lighting.
3D modeling involves creating objects in three-dimensional space by manipulating points, lines, and planes. Common techniques include direct modeling (used by software like Sketchup), parametric modeling, and sculpting (excelled by ZBrush). Rendering converts 3D models into 2D images or animations, leveraging techniques such as ray tracing, various types of shadows (hard and soft), and reflections (specular and diffuse) to achieve high realism. Materials define an object's surface properties like color, texture, and reflectivity, while lighting simulates real-world light sources to influence object appearance and create shadows.
3D animation production primarily uses keyframe animation, where a computer calculates movement between set keyframes, and path animation, which guides models along predefined paths. Camera techniques are crucial for directing audience focus and enhancing storytelling. Advanced 3D design techniques include subdivision for increased model detail, physical dynamics to simulate real-world physics like gravity and collisions, particle systems for phenomena like fire and smoke, and simulation plugins for complex behaviors such as cloth or fluid dynamics. Scripts and plugins also enhance software flexibility. Mastering 3D technology is a long-term endeavor, with significant breakthroughs now emerging in AIGC (Artificial Intelligence-Generated Content) for 3D media.

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Effective data storage is fundamental to system development success, impacting data integrity, security, performance, and maintainability. Key techniques include establishing clear file naming conventions, robust file classification strategies (considering sensitivity), using metadata for discoverability, and avoiding data redundancy. Data compression reduces storage and speeds up transfer, with options like lossless (e.g., ZIP, GZIP) and lossy (e.g., JPEG, MP3). Data encryption is crucial for protecting sensitive information, applied to both static and in-transit data using symmetric (e.g., AES) or asymmetric (e.g., RSA) algorithms, and hash functions for integrity validation. Storage validation ensures data accuracy, and comprehensive disaster recovery plans, including the 3-2-1 backup principle (at least three copies, two different methods, one offsite), are vital for business continuity.
The Transformer model, a deep learning architecture utilizing multi-head attention, is effective for sequence-to-sequence data transformation and user behavior prediction, such as customer churn prediction using RFM analysis. Despite its predictive power, the Transformer and similar complex models often lack interpretability. This leads to the need for Explainable AI (XAI), which aims to provide reasons for AI's decisions, preventing misinterpretations and guarding against adversarial attacks that can subtly alter data to cause significant misclassification. XAI seeks to explain both specific decisions (local explanation) and the overall model behavior (global explanation).

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This module equips learners with skills to analyze customer data in Power BI for strategic insights, focusing on three core areas. CoreLab 01 teaches establishing comparative indicators, such as total and same-period revenue, using calculated measures and conditional formatting to visualize year-over-year performance changes with data bars, background colors, and font colors. CoreLab 02 explores quadrant distribution application, utilizing a custom Power BI visual to categorize customers (e.g., High Member High Contribution) based on metrics like member count and average spending per person, integrating slicers, maps, and pie charts for interactive analysis. CoreLab 03 delves into RFM customer value analysis. This involves calculating Recency (R), Frequency (F), and Monetary (M) values, then segmenting customers into eight distinct value groups. A crucial step involves establishing data relationships between tables for accurate analysis. The module demonstrates visualizing customer segments through matrix visuals with data bars, and scatter plots showing product purchase and contribution trends over time via an animated play axis.

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The sources detail three practical Power BI Desktop exercises for customer data analysis, designed to help users understand market phenomena, consumer status, and customer value. The first CoreLab focuses on establishing comparison metrics, guiding the calculation and visualization of total revenue, year-over-year total revenue, and their ratio using tables and line/clustered column charts with conditional formatting. The second CoreLab introduces the Quadrant Chart for customer segmentation, categorizing customers by member count, average spending, and total spending, then displaying these insights through maps, pie charts, and cards to visualize regional distribution and contributions. The third and most complex CoreLab involves building an RFM (Recency, Frequency, Monetary) customer value analysis model. Users calculate R, F, and M scores, create an RFM table, and classify customers into eight distinct value segments. These segments are then analyzed using area charts, a matrix table, and an interactive scatter plot with an animation play axis, providing deep insights into customer behavior, purchasing patterns, and customer relationship management. The exercises emphasize hands-on operation and visual data interpretation for effective business insights.

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Administrative and Non-Government Ethics are crucial for a just society and safeguarding public interest. Administrative ethics guides public servants, emphasizing impartiality, transparency, and accountability in serving citizens. Public officials face ethical dilemmas like conflicts of interest and tough choices, requiring systems for recusal. Non-Government ethics directs NGOs in empowering communities, fostering collaboration, and championing global change, seen in organizations like the WHO. Both government and business ethics share common principles of transparency and accountability. However, government ethics focuses on public interest with stricter regulations due to its power, while business targets customers/shareholders. Government can learn from business, adopting efficiency and a citizen-centric approach for better public services. Understanding these concepts promotes social fairness.

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This text explores the global data explosion, projected to reach an astounding 181 zettabytes by 2025, largely driven by Artificial Intelligence (AI). It details earthbound storage technologies, including Hard Disk Drives (HDDs) for mass capacity and cost-effectiveness, and Solid State Drives (SSDs) for high performance (leveraging NVMe and PCIe interfaces). Cloud storage is presented as a paradigm shift, offering scalability and agility, alongside the growing market for external storage devices. Essential data management techniques such as RAID for improved performance and reliability, and the 3-2-1 backup principle for disaster recovery, are crucial. System development emphasizes effective data organization, compression, and encryption for integrity and security.
The discussion extends to the booming space economy, valued at $400 billion in 2023, with satellites accounting for 71%. New Ground Computing, which tightly integrates space (e.g., LEO satellites) and ground (cloud and edge AI) technologies, is vital for real-time data processing and analysis. AI and Machine Learning (ML) are transforming satellite image analysis, disaster warning systems, and smart operations. Major challenges in space include high costs, launch risks, space debris (Kessler syndrome), complex international legal and policy issues, space militarization, and unproven commercial markets. These advancements highlight the intertwined relationship between data storage/management and space exploration.

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The sources detail Power BI Desktop's core operations, focusing on acquiring and visualizing data from diverse external sources. Three CoreLab exercises provide hands-on experience:

• External Excel files: Users learn to download open government data (e.g., unemployment rates) and create various visualizations like cross-analysis slicers, clustered bar charts, pie charts, and line charts.
• Web data (Wiki): Connect to specific URLs to load web tables, visualizing data such as Olympic medal counts with clustered bar charts, card visualizations, and pie charts.
• Access databases: This advanced exercise emphasizes data transformation using Power Query (e.g., correcting membership IDs) and establishing accurate data relationships in the model view. Visualizations include product sales trends and member purchase analysis.

The modules highlight Power BI's capability for interactive and dynamic data visualization, integrating diverse sources for insightful analysis. Proper data cleaning and relationship management are crucial for accurate analytical results, and users are encouraged to consider the purpose of visualizations to derive business value.

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This module introduces Power BI Desktop, a powerful tool for interactive data analysis and visualization. Its core objective is to teach users how to acquire data from various external sources and create insightful, dynamic reports. The course covers importing data from external Excel text files (e.g., government open data platforms), external web data (e.g., Wikipedia Olympic data), and Access databases. Key steps emphasized include data transformation (e.g., correcting member IDs) and establishing correct data relationships between tables. Users learn to create diverse interactive visualizations, such as cross-analysis filters, grouped bar charts, pie charts, line charts, and card visuals. A significant feature highlighted is the interactive nature of dashboards, where selecting an element in one visual instantly updates all linked charts. Proficiency in BI tools like Power BI is increasingly a fundamental requirement for many job roles, aiding in the analysis of phenomena, customer behavior, and the discovery of business insights. Installation of the Power BI Desktop application is a prerequisite.

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