AI Applications in People Management (Coursera)

AI Applications in People Management (Coursera)

In this course, you will learn about Artificial Intelligence and Machine Learning as it applies to HR Management. You will explore concepts related to the role of data in machine learning, AI application, limitations of using data in HR decisions, and how bias can be mitigated using blockchain technology.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Machine learning powers are becoming faster and more streamlined, and you will gain firsthand knowledge of how to use current and emerging technology to manage the entire employee lifecycle. Through study and analysis, you will learn how to sift through tremendous volumes of data to identify patterns and make predictions that will be in the best interest of your business. By the end of this course, you'll be able to identify how you can incorporate AI to streamline all HR functions and how to work with data to take advantage of the power of machine learning.

Course 3 of 4 in the AI For Business Specialization.

Syllabus

WEEK 1
The Promise and Potential of AI in HR
In this module, you will learn about the challenges that the HR field has faced prior to the implementation of artificial intelligence as well as the role data and machine learning play in optimizing decision making. You will also learn about the role that training data plays in machine learning, how rule-based systems are used to mimic human intelligence and how they manipulate that data based on those rules. By the end of this module, you will be able to understand the concepts behind artificial intelligence, rule-based systems, and how data science has changed HR Management.

WEEK 2
AI Application
In this module, you will learn how AI is applied in HR, and how machine learning can change how people are managed within all HR functions. You will learn how artificial intelligence algorithms can be used in various scenarios and how data can be used to make predictions. By the end of this module, you will be able to distinguish how best to use AI algorithms to manage engagement, attrition, and internal career paths.

WEEK 3
Challenges With Applying AI to HR
In this module, you will examine the challenges that you may face when implementing AI as a tool. You will identify the changing trends in hiring and how that factors into finding the right applicants and how to best apply AI in hiring decisions. By the end of this module, you will be able to determine how to balance machine-driven decisions and input from supervisors to select the best candidates.

WEEK 4
Emerging Solutions
In this module, you will learn about biases that exist within algorithms and how to manage and avoid data adequacy bias. You will also learn how to understand and interpret results, use blockchain to keep data private and secure and understand the transformative nature of blockchain technology. By the end of this module, you will be able to explain how data science and AI have markedly changed the way we approach HR and incorporate emerging technological solutions to structure people management.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

GitHub Copilot: The AI Pair Programmer for Coding (Coursera) Coursera
Edureka

GitHub Copilot: The AI Pair Programmer for Coding (Coursera)

Welcome to the 'GitHub Copilot: The AI Pair Programmer for Coding' course, where you will embark on an insightful journey to develop a profound understanding of the AI principles that power GitHub Copilot's coding assistance. This course is designed to transform your coding practices, leveraging the advanced capabilities of GitHub Copilot.

Sep 14th 2026
1 Week
Applied Text Mining in Python (Coursera) Coursera
University of Michigan

Applied Text Mining in Python (Coursera)

This course will introduce the learner to text mining and text manipulation basics. The course begins with an understanding of how text is handled by python, the structure of text both to the machine and to humans, and an overview of the nltk framework for manipulating text. The second week focuses on common manipulation needs, including regular expressions (searching for text), cleaning text, and preparing text for use by machine learning processes. The third week will apply basic natural language processing methods to text, and demonstrate how text classification is accomplished. The final week will explore more advanced methods for detecting the topics in documents and grouping them by similarity (topic modelling).

Sep 14th 2026
4 Weeks
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera) Coursera
DeepLearning.AI

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Sep 14th 2026
4 Weeks
Matrix Methods (Coursera) Coursera
University of Minnesota

Matrix Methods (Coursera)

Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Discover the Singular Value Decomposition that plays a fundamental role in dimensionality reduction, Principal Component Analysis, and noise reduction.

Sep 14th 2026
5-12 Weeks
Machine Learning Rapid Prototyping with IBM Watson Studio (Coursera) Coursera
IBM

Machine Learning Rapid Prototyping with IBM Watson Studio (Coursera)

An emerging trend in AI is the availability of technologies in which automation is used to select a best-fit model, perform feature engineering and improve model performance via hyperparameter optimization. This automation will provide rapid-prototyping of models and allow the Data Scientist to focus their efforts on applying domain knowledge to fine-tune models. This course will take the learner through the creation of an end-to-end automated pipeline built by Watson Studio’s AutoAI experiment tool, explaining the underlying technology at work as developed by IBM Research.

Sep 14th 2026
4 Weeks
Managing Social and Human Capital (Coursera) Coursera
University of Pennsylvania

Managing Social and Human Capital (Coursera)

Based on their popular course at Wharton, this course will teach you how to motivate individual performance and design reward systems, how to design jobs and organize work for high performance, how to make good and timely management decisions, and how to design and change the your organization’s architecture. By the end of this course, you'll have developed the skills you need to start motivating, organizing, and rewarding people in your organization so that you can thrive as a business and as a social organization.

Sep 14th 2026
4 Weeks
Innovative Teaching with ChatGPT (Coursera) Coursera
Vanderbilt University

Innovative Teaching with ChatGPT (Coursera)

Despite what you may have heard, ChatGPT offers exciting possibilities for supporting innovative teaching and personalized education. This course provides practical techniques that any educator, from K-12 to higher education, can use to help support their teaching. No experience with ChatGPT, prompt engineering, or Generative AI is required.

Sep 14th 2026
1 Week
ML Pipelines on Google Cloud (Coursera) Coursera
Google Cloud

ML Pipelines on Google Cloud (Coursera)

In this course, you will be learning from ML Engineers and Trainers who work with the state-of-the-art development of ML pipelines here at Google Cloud. The first few modules will cover about TensorFlow Extended (or TFX), which is Google’s production machine learning platform based on TensorFlow for management of ML pipelines and metadata. You will learn about pipeline components and pipeline orchestration with TFX. You will also learn how you can automate your pipeline through continuous integration and continuous deployment, and how to manage ML metadata.

Sep 14th 2026
4 Weeks