Certificate in Edge Visualization: Data-Driven Insights

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The Certificate in Edge Visualization: Data-Driven Insights is a comprehensive course designed to equip learners with essential skills for career advancement in today's data-driven world. This course focuses on the importance of visualizing data at the edge, providing learners with the knowledge and tools to make informed, real-time decisions based on data insights.

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In an era where businesses generate vast amounts of data, there is an increasing industry demand for professionals who can convert raw data into actionable insights. This course meets that demand by teaching learners how to collect, analyze, and visualize data using cutting-edge technologies and techniques. By the end of this course, learners will have gained hands-on experience with industry-leading tools such as Node-RED, InfluxDB, and Grafana. They will be able to create powerful data visualizations that help organizations make informed decisions, providing them with a competitive edge in their respective industries. This course is an excellent opportunity for professionals looking to advance their careers in data analytics, visualization, and edge computing.

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ใ‚ณใƒผใ‚น่ฉณ็ดฐ

โ€ข Unit 1: Introduction to Edge Visualization
โ€ข Unit 2: Data Acquisition and Processing for Edge Visualization
โ€ข Unit 3: Data Analysis Techniques for Edge Visualization
โ€ข Unit 4: Data Visualization Fundamentals
โ€ข Unit 5: Edge Visualization Tools and Technologies
โ€ข Unit 6: Real-time Data Visualization on the Edge
โ€ข Unit 7: Security Considerations for Edge Visualization
โ€ข Unit 8: Use Cases and Applications of Edge Visualization
โ€ข Unit 9: Best Practices for Designing Effective Edge Visualizations
โ€ข Unit 10: Future Trends and Research in Edge Visualization

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The Certificate in Edge Visualization: Data-Driven Insights focuses on in-demand roles that require data visualization skills. With the increasing importance of data-driven decision-making in businesses, professionals with these skills are highly sought after. 1. **Data Scientist**: Proficient in statistical analysis, machine learning, data visualization, and programming languages like Python and R. (25% of the roles) 2. **Data Analyst**: Skilled in collecting, cleaning, and interpreting large data sets to drive business decisions. (20% of the roles) 3. **Data Engineer**: Responsible for building and maintaining data architectures, pipelines, and databases. (15% of the roles) 4. **BI Analyst**: Experienced in data analysis, reporting, and business intelligence tools like Tableau and Power BI. (10% of the roles) 5. **Data Visualization Expert**: Specializes in creating interactive and informative visual representations of complex data. (10% of the roles) 6. **Machine Learning Engineer**: Develops and implements machine learning models and algorithms. (10% of the roles) 7. **Big Data Analyst**: Extracts insights from massive structured and unstructured datasets using tools like Hadoop and Spark. (10% of the roles) These roles showcase the growing demand for professionals who can derive valuable insights from data and communicate them effectively to stakeholders. As the data landscape evolves, the need for these skills will only increase.

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ใ‚ตใƒณใƒ—ใƒซ่จผๆ˜Žๆ›ธใฎ่ƒŒๆ™ฏ
CERTIFICATE IN EDGE VISUALIZATION: DATA-DRIVEN INSIGHTS
ใซๆŽˆไธŽใ•ใ‚Œใพใ™
ๅญฆ็ฟ’่€…ๅ
ใงใƒ—ใƒญใ‚ฐใƒฉใƒ ใ‚’ๅฎŒไบ†ใ—ใŸไบบ
London School of International Business (LSIB)
ๆŽˆไธŽๆ—ฅ
05 May 2025
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