Professional Certificate Twitter Data for Investigations

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The Twitter Data for Investigations Professional Certificate course is a comprehensive program that equips learners with essential skills to leverage Twitter data for investigative purposes. This course is crucial in today's digital age, where social media plays a significant role in shaping public opinion and spreading information.

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ใ“ใฎใ‚ณใƒผใ‚นใซใคใ„ใฆ

Learners will gain a deep understanding of Twitter's API, data analysis techniques, and visualization tools to uncover insights and patterns. This certification course is in high demand across various industries, including journalism, law enforcement, and marketing. By completing this course, learners will develop a strong analytical mindset, critical thinking skills, and the ability to communicate complex data insights effectively, making them highly valuable in the job market and significantly advancing their careers.

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ใฉใ“ใ‹ใ‚‰ใงใ‚‚ๅญฆ็ฟ’

ๅ…ฑๆœ‰ๅฏ่ƒฝใช่จผๆ˜Žๆ›ธ

LinkedInใƒ—ใƒญใƒ•ใ‚ฃใƒผใƒซใซ่ฟฝๅŠ 

ๅฎŒไบ†ใพใง2ใƒถๆœˆ

้€ฑ2-3ๆ™‚้–“

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ๅพ…ๆฉŸๆœŸ้–“ใชใ—

ใ‚ณใƒผใ‚น่ฉณ็ดฐ

โ€ข <data-mining-techniques>: Introduction to various data mining techniques used to extract insights from Twitter data.
โ€ข <twitter-api>: Understanding the Twitter API and how to access data from Twitter for analysis.
โ€ข <natural-language-processing>: Overview of natural language processing (NLP) techniques and their application in analyzing Twitter data.
โ€ข <social-network-analysis>: Exploration of social network analysis and its use in identifying patterns and relationships in Twitter data.
โ€ข <sentiment-analysis>: In-depth review of sentiment analysis, including supervised and unsupervised methods, and their application in analyzing Twitter data.
โ€ข <topic-modeling>: Study of topic modeling techniques, such as Latent Dirichlet Allocation (LDA), and their application in identifying themes and topics in Twitter data.
โ€ข <geographic-information-systems>: Introduction to Geographic Information Systems (GIS) and their use in analyzing geolocated Twitter data.
โ€ข <data-visualization>: Overview of data visualization techniques and tools for presenting Twitter data insights.
โ€ข <ethical-considerations>: Examination of ethical considerations when analyzing Twitter data, including privacy and consent.
โ€ข <case-studies>: Analysis of real-world case studies demonstrating the application of Twitter data for investigations.

ใ‚ญใƒฃใƒชใ‚ขใƒ‘ใ‚น

The Professional Certificate Twitter Data for Investigations features a Google Charts 3D pie chart to represent the job market trends in the UK for various data-related roles. The chart is responsive, setting its width to 100% and height to 400px for optimal viewing on any device. Each slice in the pie chart represents a specific role, with the percentage indicating the demand in the job market. Here's a concise description of the roles presented in the chart: * Data Scientist: Professionals who use scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. * Data Analyst: Professionals who translate numbers into plain English to help companies make better business decisions. * Data Engineer: Professionals who build, maintain, test, and evaluate big data solutions to ensure they perform smoothly and meet business objectives. * BI Analyst: Professionals who analyze data to gain insights, drive business planning, and support decision-making. * Data Visualization Engineer: Professionals who design and build data visualizations to help organizations make informed decisions. * Data Journalist: Professionals who combine data analysis and journalism to tell stories and inform the public. * ML Engineer: Professionals who build and maintain machine learning frameworks, platforms, and systems. These roles are essential in today's data-driven world, and understanding their demand in the job market can help individuals choose the right career path. The 3D pie chart in this certificate program allows learners to grasp the current trends and make informed decisions.

ๅ…ฅๅญฆ่ฆไปถ

  • ไธป้กŒใฎๅŸบๆœฌ็š„ใช็†่งฃ
  • ่‹ฑ่ชžใฎ็ฟ’็†Ÿๅบฆ
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  • ใ‚ณใƒผใ‚นๅฎŒไบ†ใธใฎ็Œฎ่บซ

ไบ‹ๅ‰ใฎๆญฃๅผใช่ณ‡ๆ ผใฏไธ่ฆใ€‚ใ‚ขใ‚ฏใ‚ปใ‚ทใƒ“ใƒชใƒ†ใ‚ฃใฎใŸใ‚ใซ่จญ่จˆใ•ใ‚ŒใŸใ‚ณใƒผใ‚นใ€‚

ใ‚ณใƒผใ‚น็Šถๆณ

ใ“ใฎใ‚ณใƒผใ‚นใฏใ€ใ‚ญใƒฃใƒชใ‚ข้–‹็™บใฎใŸใ‚ใฎๅฎŸ็”จ็š„ใช็Ÿฅ่ญ˜ใจใ‚นใ‚ญใƒซใ‚’ๆไพ›ใ—ใพใ™ใ€‚ใใ‚Œใฏ๏ผš

  • ่ชๅฏใ•ใ‚ŒใŸๆฉŸ้–ขใซใ‚ˆใฃใฆ่ชๅฎšใ•ใ‚Œใฆใ„ใชใ„
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  • ๆญฃๅผใช่ณ‡ๆ ผใฎ่ฃœๅฎŒ

ใ‚ณใƒผใ‚นใ‚’ๆญฃๅธธใซๅฎŒไบ†ใ™ใ‚‹ใจใ€ไฟฎไบ†่จผๆ˜Žๆ›ธใ‚’ๅ—ใ‘ๅ–ใ‚Šใพใ™ใ€‚

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ใ“ใฎใ‚ณใƒผใ‚นใ‚’ไป–ใฎใ‚ณใƒผใ‚นใจๅŒบๅˆฅใ™ใ‚‹ใ‚‚ใฎใฏไฝ•ใงใ™ใ‹๏ผŸ

ใ‚ณใƒผใ‚นใ‚’ๅฎŒไบ†ใ™ใ‚‹ใฎใซใฉใ‚Œใใ‚‰ใ„ๆ™‚้–“ใŒใ‹ใ‹ใ‚Šใพใ™ใ‹๏ผŸ

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ใ„ใคใ‚ณใƒผใ‚นใ‚’้–‹ๅง‹ใงใใพใ™ใ‹๏ผŸ

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ใ‚ณใƒผใ‚นๆƒ…ๅ ฑใ‚’ๅ–ๅพ—

่ฉณ็ดฐใชใ‚ณใƒผใ‚นๆƒ…ๅ ฑใ‚’ใŠ้€ใ‚Šใ—ใพใ™

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ใ“ใฎใ‚ณใƒผใ‚นใฎๆ”ฏๆ‰•ใ„ใฎใŸใ‚ใซไผš็คพ็”จใฎ่ซ‹ๆฑ‚ๆ›ธใ‚’ใƒชใ‚ฏใ‚จใ‚นใƒˆใ—ใฆใใ ใ•ใ„ใ€‚

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ใ‚ญใƒฃใƒชใ‚ข่จผๆ˜Žๆ›ธใ‚’ๅ–ๅพ—

ใ‚ตใƒณใƒ—ใƒซ่จผๆ˜Žๆ›ธใฎ่ƒŒๆ™ฏ
PROFESSIONAL CERTIFICATE TWITTER DATA FOR INVESTIGATIONS
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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