Filter by
Subject
Required
Language
Required
The language used throughout the course, in both instruction and assessments.
Learning Product
Required
Build job-relevant skills in under 2 hours with hands-on tutorials.
Learn from top instructors with graded assignments, videos, and discussion forums.
Learn a new tool or skill in an interactive, hands-on environment.
Get in-depth knowledge of a subject by completing a series of courses and projects.
Earn career credentials from industry leaders that demonstrate your expertise.
Earn your Bachelor’s or Master’s degree online for a fraction of the cost of in-person learning.
Earn a university-issued career credential in a flexible, interactive format.
Level
Required
Duration
Required
Skills
Required
Subtitles
Required
Educator
Required
Results for "real-world+hr+challenges"
Status: FreeCoursera Instructor Network
Status: FreeCoursera Instructor Network
Skills you'll gain: Data Visualization
Skills you'll gain: Deep Learning, Machine Learning
Skills you'll gain: Algorithms
Skills you'll gain: Web Development
Skills you'll gain: Applied Machine Learning, Machine Learning
Università di Napoli Federico II
Skills you'll gain: Big Data, Business Intelligence, Computer Vision
Queen Mary University of London
Skills you'll gain: Econometrics, Regression, Linear Algebra
LearnKartS
Skills you'll gain: Data Management, Salesforce
LearnKartS
Skills you'll gain: Data Management
In summary, here are 10 of our most popular real-world+hr+challenges courses
- Bridging the Gap: EV Grid Integration & V2G Systems:Â Coursera Instructor Network
- Introduction to Data Visualization in Qlik Sense:Â Coursera Instructor Network
- Advanced Machine Learning and Deep Learning:Â Packt
- JavaScript Algorithm Challenges for Beginners:Â Scrimba
- Tricky JavaScript: Hoisting, Scope, Arrow Functions, Fetch:Â Scrimba
- IT Fundamentals and Hardware Essentials:Â Packt
- Four Rare Machine Learning Skills All Data Scientists Need:Â SAS
- Autonomous Vehicle Engineering: Università di Napoli Federico II
- The Classical Linear Regression Model:Â Queen Mary University of London
- Proyecto final de ingenieros de bases de datos:Â Meta
