Applied AI for Human Resources

1h 20mIntermediate2024-01-18

Authors

Kumaran Ponnambalam

Working with data for 20+ years

Course details

A global economy and remote workforce have made it difficult for HR departments to track employee satisfaction and motivation. However, using artificial intelligence, data scientists and engineers can now generate powerful insights to improve hiring, training, retention, and more. This course explores the ways AI and big data can help HR. Examine three key use cases in the human resources world: predicting employee attrition, mapping collaboration, and creating training recommendations. For each of these use cases, instructor Kumaran Ponnambalam collects and processes data, builds machine learning models, and predicts key outcomes using tools like Python, Jupyter Notebooks, TensorFlow, and Keras. He also briefly explains how to design models to perform other common HR tasks, such as predicting future performance, screening candidates, and even tracking morale. The course concludes with some best practices, including addressing security and privacy concerns particular to HR.

Learning objectives
HR challenges and AI solutions
Acquiring data
Classification with deep learning
Processing and preparing data
Building and testing models
Predicting outcomes
Conducting sentiment analysis

Skills covered

HR AdministrationArtificial Intelligence FoundationsPythonArtificial Intelligence for BusinessHuman ResourcesArtificial Intelligence (AI)Business Analysis and StrategyOpen SourceDeep Dive (X:Y)

Concepts

0. Introduction

01 - Artificial intelligence and human resources
02 - Course prerequisites

1. Human Resources and AI

03 - Introduction to HR
04 - HR challenges
05 - AI and HR
06 - HR use cases overview
07 - Setting up the exercise files

2. Use Case 1 - Predicting Employee Attrition

08 - Employee attrition
09 - Classification with deep learning
10 - Data for employee attrition
11 - Preprocessing attrition data
12 - Building an attrition model with Keras
13 - Predicting attrition with Keras

3. Use Case 2 - Discovering Collaboration

14 - Organization design
15 - Network analysis with networks
16 - Data for network analysis
17 - Preparing network data
18 - Creating and visualizing networks
19 - Analyzing networks

4. Use Case 3 - Recommend Training Courses

20 - Employee development
21 - User item recommendations
22 - Ratings data for recommendations
23 - Prepare for embedding
24 - Building a Keras rating model
25 - Recommending courses with Keras

5. Other HR Use Cases

26 - Predict future employee performance
27 - Candidate outreach
28 - Automated candidate screening
29 - Employee virtual assistant
30 - Sentiment analysis

6. Generative AI for HR

31 - Generative AI review
32 - Text generation with LLMs
33 - Resume summarization
34 - Job description generation
35 - Employee self-help chatbot
36 - Resume skills extraction
37 - Resume skills extraction example

7. IT Ops Best Practices

38 - Model development best practices
39 - Using machine learning platforms
40 - Model serving best practices
41 - Security and privacy best practices

Conclusion

42 - Next steps