Chapter 2 AI

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Across
  1. 2. An AI professional who offers expert guidance to organizations on leveraging AI. [cite 40]
  2. 5. A Python library vital for building and deploying AI solutions, alongside SciPy and NumPy. [cite 53, 71]
  3. 6. A type of engineer who designs and maintains AI-powered robots. [cite 29]
  4. 9. A soft skill essential for conveying complex technical concepts to non-technical stakeholders. [cite 58]
  5. 10. The programming language widely used in AI for implementing intelligence programming and neural networks. [cite 69]
  6. 15. The specific area where NLP engineers specialize, like voice assistants. [cite 33]
  7. 17. A widely used programming language with pre-made libraries for advanced computing in AI. [cite 67]
  8. 18. A type of analyst who identifies fraudulent activities using AI models. [cite 85]
  9. 19. An essential technical skill for developing advanced AI applications, alongside machine learning and deep learning. [cite 49]
  10. 22. A platform known for its free online micro-courses to gain data science skills and host competitions. [cite 102, 103]
  11. 23. An online resource offering free video-based courses on artificial intelligence, including "Kickstart Artificial Intelligence." [cite 105]
  12. 25. A leading site on data science, machine learning, AI, and analytics, offering tutorials and courses. [cite 95, 96]
  13. 26. A field that was once confined to science fiction but now permeates daily life. [cite 5]
Down
  1. 1. Engineers who develop algorithms and systems to analyze and interpret visual information from images or videos. [cite 35]
  2. 3. An online publication where independent authors share knowledge about data science on Medium. [cite 93]
  3. 4. This organization offers insights, latest news, and a magazine featuring opinions of top industry leaders. [cite 92]
  4. 7. The overall market demand for AI talent is described as _______. [cite 13]
  5. 8. A degree often required for an AI software engineer. [cite 32]
  6. 11. A common job role in AI that bridges software engineering and data science. [cite 22]
  7. 12. One of the common job roles in AI that extracts insights from large datasets to make business decisions. [cite 24]
  8. 13. One of the top skills AI professionals need, related to analyzing and handling large datasets. [cite 50, 51]
  9. 14. This refers to the global trend of AI solutions being increasingly integrated into diverse sectors. [cite 13]
  10. 16. These professionals address ethical considerations and implications of AI technologies. [cite 38]
  11. 20. A type of program that provides personalized recommendations on streaming platforms. [cite 6]
  12. 21. A Python library for scientific computing and mathematical operations, alongside NumPy. [cite 72]
  13. 24. A specific engineering discipline crucial for Robotics Engineers, along with mechanical and electrical. [cite 30]
  14. 27. One of the programming languages necessary for developing AI models and algorithms, besides Python, R, and Java. [cite 54]