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AI+ Human Resources Practitioner (AP-230)

AI is changing how HR teams recruit talent, understand employee needs, and make workforce decisions.

AI+ Human Resources Practitioner focuses on applying AI across recruitment, onboarding, employee engagement, workforce analytics, and talent management. You’ll also explore ethical AI, legal requirements, future workforce trends, and practical approaches for introducing AI into HR operations.

Overview

Overview

HR teams increasingly use AI to automate repetitive work and make better use of employee and workforce data. This course explores how AI can support recruitment, onboarding, employee engagement, performance management, learning, and workforce planning.

You’ll examine machine learning, natural language processing, predictive analytics, sentiment analysis, and other technologies used across modern HR functions.

The course also addresses data privacy, bias, legal compliance, organizational readiness, and responsible AI adoption. A practical implementation module brings these areas together by showing how to plan, monitor, evaluate, and scale an HR AI initiative.

Prerequisites
  • Foundational awareness of AI concepts and practical applications

  • Creative problem-solving skills for applying AI to HR challenges

  • Curiosity and willingness to learn new technologies and approaches

Target Audience
  • HR professionals and managers introducing AI into HR processes

  • Recruitment and talent acquisition specialists

  • Learning and development professionals

  • Employee engagement coordinators

  • Performance management specialists

  • Organizational development practitioners

  • HR technology and integration professionals

Exam Blueprint
  • Foundations of AI in HR – 12%
  • AI-Enhanced Recruitment and Onboarding – 16%
  • AI-Assisted Content Creation and Strategy – 12%
  • Workforce Analytics and Talent Management – 12%
  • Ethical AI and Bias Mitigation – 12%
  • Legal Considerations in AI for HR – 12%
  • Preparing for the Future of AI in HR – 12%
  • Implementing AI in HR: A Practical Workshop – 12%
FAQs

1. Does the course cover employee engagement and workforce analytics?
Yes. You’ll explore sentiment analysis, employee feedback, turnover prediction, workforce data, talent identification, and succession planning.

2. Can the course be taken online?
Yes, the course is available through live virtual instructor-led training or a self-paced online option.

3. Is in-person training available?
Yes, classroom sessions are available through AI CERTs Authorized Training Partners.

Course Outline

Module 1: Foundations of AI in HR
  1. Artificial Intelligence in Human Resources
  2. Machine Learning
  3. Deep Learning
  4. Natural Language Processing
  5. Evolution of HR Technology
  6. From Manual HR Processes to AI-Driven Practices
  7. AI in Recruitment
  8. AI in Employee Engagement
  9. AI in Performance Management
  10. Real-World HR AI Case Studies
  11. Skills Required for AI Adoption
  12. Building an Innovative HR Culture
  13. Data Privacy
  14. Bias and Ethical Considerations

 

Module 2: AI-Enhanced Recruitment and Onboarding
  1. AI Applications in Recruitment
  2. Candidate Sourcing
  3. Automated Resume Screening
  4. Predictive Analytics for Recruitment
  5. AI Chatbots for Candidate Interactions
  6. Improving Candidate Matching
  7. AI-Driven Onboarding
  8. Personalized Onboarding Experiences
  9. Personalized Learning Paths for New Hires
  10. Automating Administrative Onboarding Tasks
  11. Social Integration for New Employees
  12. Benefits and Challenges of AI in Recruitment
  13. Strategies for Implementing AI in Recruitment
  14. Measuring Recruitment and Onboarding Success

 

Module 3: AI-Assisted Content Creation and Strategy
  1. AI for Employee Experience
  2. AI for Employee Engagement
  3. Personalized Learning and Development
  4. Adaptive Learning Environments
  5. Tailored Employee Development Paths
  6. Employee Feedback Analysis
  7. Sentiment Analysis
  8. Analyzing Employee Communication Data
  9. Identifying Areas for Employee Experience Improvement
  10. AI-Driven Engagement Strategies
  11. AI Tools for Learning and Development
  12. AI Tools for Sentiment Analysis
  13. Pilot Programs
  14. Continuous Improvement
  15. Ethical Considerations
  16. Employee Data Privacy
  17. Transparency and Employee Trust

 

Module 4: Workforce Analytics and Talent Management
  1. Fundamentals of Workforce Analytics
  2. Workforce Data Analysis
  3. Data Visualization
  4. Data Interpretation
  5. AI in Talent Management
  6. Data-Driven Talent Acquisition
  7. Employee Development
  8. Employee Retention
  9. Predictive Workforce Analytics
  10. Employee Turnover Forecasting
  11. Identifying High-Potential Employees
  12. AI-Driven Talent Identification
  13. Succession Planning
  14. Data Privacy in Workforce Analytics
  15. Bias Mitigation
  16. Transparent Talent Decisions

 

Module 5: Ethical AI and Bias Mitigation
  1. Principles of Ethical AI in HR
  2. Fairness
  3. Transparency
  4. Accountability
  5. Data Privacy
  6. Employee Consent
  7. Bias in AI Decision-Making
  8. Sources of Bias in HR AI Tools
  9. Diverse Data Sets
  10. Algorithmic Transparency
  11. Bias Mitigation Strategies
  12. Ethical AI Frameworks
  13. Stakeholder Engagement
  14. AI Monitoring
  15. HR AI Governance
  16. Responsible AI Implementation

 

Module 6: Legal Considerations in AI for HR
  1. Legal Considerations for HR AI
  2. Employee Privacy
  3. Data Protection
  4. GDPR
  5. CCPA
  6. Employment Laws and AI
  7. AI Audits
  8. Risk Assessments
  9. HR AI Compliance
  10. Monitoring Regulatory Changes
  11. Stakeholder Engagement
  12. International Legal Considerations
  13. Managing Legal Risk in AI-Enabled HR

 

Module 7: Preparing for the Future of AI in HR
  1. Future AI Trends in Human Resources
  2. AI and Remote Work
  3. AI and the Gig Economy
  4. Diversity and Inclusion
  5. Emerging HR Skills and Competencies
  6. Building Organizational AI Readiness
  7. Developing a Culture of Innovation
  8. AI in Future Talent Management
  9. Future Workforce Analytics
  10. Strategic Planning for AI Adoption
  11. Assessing Organizational Readiness
  12. Aligning AI with Business Goals
  13. Change Management
  14. Ethical Considerations
  15. Managing Unintended AI Consequences
  16. Sustainable AI Practices

 

Module 8: Implementing AI in HR: A Practical Workshop
  1. Identifying HR Challenges
  2. Selecting Appropriate AI Solutions
  3. AI Project Planning
  4. Stakeholder Engagement
  5. HR Data Management
  6. Defining Project Scope
  7. Developing Implementation Timelines
  8. AI Solution Design
  9. Monitoring AI Performance
  10. Evaluating AI Initiatives
  11. Establishing Performance Metrics
  12. Key Performance Indicators
  13. Building Feedback Loops
  14. Scaling AI Solutions
  15. Integrating AI into Existing HR Processes
  16. Fairness and Privacy Requirements
  17. Legal and Ethical Compliance
  18. Long-Term Sustainability
  19. Social Impact of HR AI Initiatives
Note : A representative from Datacipher will contact you with further details
Payment Methods

At DataCipher, we offer a variety of payment options for our Fortinet courses. Here are the methods available:

Purchase Order (PO) – If your organization prefers using a purchase order, begin the registration process by clicking the Register button. At the conclusion of the registration form, choose the option “My company will pay for it, please send an invoice with the payment details.” Our training team will then provide an official quote and any necessary additional information that your accounts department might need to issue the PO.

Bank Transfer – DataCipher maintains bank accounts in both the US and Europe, accommodating all standard bank transfer methods such as IBAN/BIC, Swift, ACH, or wire transfer. To make a payment via bank transfer, simply use the Register button to sign up for your selected course.

Credit Card Payments – We accept payments from all major credit cards, including Mastercard, VISA, American Express, Discover & Diners, and Cartes Bancaires. Payments can be made directly through the registration link or by requesting an invoice that includes a web link for online payment. All transactions are secure, and DataCipher does not store any credit card information.

These options are designed to make the registration process as smooth and flexible as possible for all participants.

Status

Guaranteed to Run – DataCipher is committed to running this class unless unforeseen events such as an instructor’s accident or illness occur.

Guaranteed on Next Booking – The course will proceed once an additional student registers.

Scheduled Class – We have scheduled this course and rarely cancel due to low enrollment. We offer a “Cancel No More Than Once” guarantee, ensuring that if a class is canceled due to insufficient enrollment, the next session will run regardless of the number of attendees.

Sold Out – If the class is fully booked, please use our contact form to join the waiting list or to inquire about additional sessions. We’re here to accommodate your training needs and keep you informed of new opportunities.

Half and Full-Day Training

At DataCipher, we offer our training courses in both traditional full-day and convenient half-day formats. Our half-day classes are specifically designed for IT professionals who cannot be away from their workplaces for consecutive full days. This flexible schedule allows participants to dedicate a few hours to learning and then return to their regular work responsibilities.

The curriculum for both the full-day and half-day formats is identical. The primary difference is that the half-day classes spread the coursework over a more extended period, providing a balanced approach to professional education. DataCipher has been successfully running these half-day training sessions for several years, receiving consistently positive feedback from our customers. They appreciate the flexibility and report that the extended timeframe facilitates a deeper understanding of the material, as it gives them more time to absorb and reflect on the information learned.

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