The AI Practitioner: Role & Responsibilities

Artificial Intelligence
  • 14 Videos | 52m 29s
  • Includes Assessment
  • Earns a Badge
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AI Practitioner is a cross-industry advanced AI Developer position that has a growing demand in the modern world. Candidates for this role need to demonstrate proficiency in optimizing and tuning AI solutions to deliver the best possible performance in the real world. AI Practitioners require more advanced knowledge of algorithm implementations and should have a firm knowledge of latest toolsets available. In this course, you'll be introduced to the AI Practitioner role in the industry. You'll examine an AI Practitioner's skillset and responsibilities in relation to AI Developers, Data Scientists, and ML and AI Engineers. Finally, you'll learn about the scope of work for AI Practitioners, including their career opportunities and pathways.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    describe the role of an AI Practitioner in a company and identify key responsibilities
    specify the skillset needed to become an AI Practitioner and name commonly used tools
    recognize the role of an AI Practitioner when developing AI products and their relationship with other developers
    compare AI Practitioner to AI Developer and list fundamental differences in their workflows
    compare AI Practitioner to Data Scientist/AI Scientist and list fundamental differences in their workflows
    compare AI Practitioner to ML Engineer and list fundamental differences in their workflows
  • compare AI Practitioner to AI Engineer and list fundamental differences in their workflows
    describe the mindset that needs to be adopted by an AI Practitioner to implement AI
    identify the importance of research work for an AI Practitioner
    describe the responsibilities of an AI Practitioner working in the data science domain and list the most important success factors
    describe the responsibilities of an AI Practitioner working in the AI Industry and list the most important success factors to developing AI products
    specify career paths and opportunities for an AI Practitioner, including multiple roles and responsibilities that lead to professional growth
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 37s
    UP NEXT
  • Playable
    2. 
    AI Practitioner Role Overview
    3m 48s
  • Locked
    3. 
    Skillset & Tools for AI Practitioner
    4m 9s
  • Locked
    4. 
    AI Practitioner in the Industry
    3m 38s
  • Locked
    5. 
    AI Practitioner vs. AI Developer
    3m 45s
  • Locked
    6. 
    AI Practitioner vs. Data Scientist/AI Scientist
    3m 21s
  • Locked
    7. 
    AI Practitioner vs. ML Engineer
    3m 12s
  • Locked
    8. 
    AI Practitioner vs. AI Engineer
    3m 25s
  • Locked
    9. 
    AI Practitioner Mindset
    3m 15s
  • Locked
    10. 
    AI Practitioner & Research Work
    2m 58s
  • Locked
    11. 
    AI Practitioners in the Data Science Domain
    4m 32s
  • Locked
    12. 
    AI Practitioners in the AI Industry
    4m 2s
  • Locked
    13. 
    AI Practitioner Roles & Responsibilities
    3m 54s
  • Locked
    14. 
    Course Summary
    53s

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