This three-module course introduces machine learning and data science for everyone with a foundational understanding of machine learning models. You’ll learn about the history of machine learning, applications of machine learning, the machine learning model lifecycle, and tools for machine learning. You’ll also learn about supervised versus unsupervised learning, classification, regression, evaluating machine learning models, and more. Our labs give you hands-on experience with these machine learning and data science concepts. You will develop concrete machine learning skills as well as create a final project demonstrating your proficiency.
ofrecido por


Machine Learning Introduction for Everyone
IBMAcerca de este Curso
Qué aprenderás
Definition, history, fundamentals and applications of machine learning
Identify opportunities to leverage machine learning in your career
Habilidades que obtendrás
- Deep Learning
- Artificial Intelligence (AI)
- Machine Learning
- Reinforcement Learning
- Machine Learning Model Lifecycle
ofrecido por

IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
Programa - Qué aprenderás en este curso
Machine Learning for Everyone
Welcome to the world of machine learning.
Machine Learning Topics
Machine learning is a hot topic, and everyone is trying to understand what it is about. With the amount of information that is out there about machine learning, you can get quickly overwhelmed.
(Optional Honors) Final Project
Preguntas Frecuentes
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