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Training
Course Information
Course Name
AI-HR: AI for HR System Development
Duration
5 Days
Overview
Audience Profile
Prerequisities
At Course Completion
Course Outline
Overview
Equip participants with the knowledge and skills to integrate AI technologies into HR systems, enhancing functionalities such as recruitment, employee engagement, performance analysis, and predictive analytics.
Overview
Overview
Equip participants with the knowledge and skills to integrate AI technologies into HR systems, enhancing functionalities such as recruitment, employee engagement, performance analysis, and predictive analytics.
Audience Profile
Prerequisities
At Course Completion
Course Outline
Course Outline
Module 1: Overview of AI
- Definition and history of AI
- Key AI concepts: Machine Learning, Deep Learning, Natural Language Processing (NLP)
- AI ethics and considerations
Module 2: AI in HR: Opportunities and Challenges
- Use cases of AI in HR: recruitment, employee engagement, performance management, retention
- Challenges and limitations of AI in HR
- Case studies of AI implementation in HR systems
Module 3: Setting up the AI Development Environment
- Overview of tools and frameworks: Python, TensorFlow, Keras, scikit-learn, NLTK
- Setting up the development environment
- Introduction to Jupyter Notebooks
Module 4: Machine Learning Basics
- Supervised vs. unsupervised learning
- Key algorithms: linear regression, decision trees, clustering
- Evaluation metrics
Module 5: Predictive Analytics in HR
- Building predictive models for employee turnover
- Analyzing employee performance data
- Case study: Predicting employee attrition
Module 6: Introduction to NLP
- NLP concepts and techniques
- Text preprocessing: tokenization, stemming, lemmatization
- Sentiment analysis
Module 7: Chatbots for Employee Engagement
- Designing and developing HR chatbots
- Integrating chatbots into HR systems
- Case study: HR chatbots for recruitment and onboarding
Module 8: Deep Learning Basics
- Introduction to neural networks and deep learning
- Key architectures: CNNs, RNNs, LSTMs
- Applications of deep learning in HR
Module 9: Image and Video Analysis in HR
- Using computer vision for candidate screening
- Analyzing video interviews
- Case study: Automated resume screening
Module 10: AI System Integration
- Integrating AI models into existing HR systems
- APIs and microservices for AI deployment
- Security and privacy considerations
