Machine Learning Introduction for Everyone

 

What you'll learn

Compare and contrast artificial intelligence, machine learning, and deep learning 

Explain the machine learning models development lifecycle    

Differentiate between supervised and unsupervised machine learning   

Evaluate classification models using metrics such as accuracy, confusion matrices, precision, and recall

Join Free:Machine Learning Introduction for Everyone

There are 3 modules in this course

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. 

After completing this program, you’ll be able to realize the potential of machine learning algorithms and artificial intelligence in different business scenarios. You’ll be able to identify when to use machine learning to explain certain behaviors and when to use it to predict future outcomes. You’ll also learn how to evaluate your machine learning models and to incorporate best practices. 

This Course Is Part of Multiple Programs 

You can also leverage the learning from the program to complete the remaining two courses of the six-course IBM Machine Learning Professional Certificate and power a new career in the field of machine learning.