Prepare for a career in the field of machine learning. In this program, you’ll learn in-demand skills like AI and Machine Learning to get job-ready in less than 3 months.
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Prepare for a career in the field of machine learning. In this program, you’ll learn in-demand skills like AI and Machine Learning to get job-ready in less than 3 months.
Prepare for a career in the field of machine learning. In this program, you’ll learn in-demand skills like AI and Machine Learning to get job-ready in less than 3 months.
Machine Learning is the use and development of computer systems that are able to learn and adapt by using algorithms and statistical models to analyze and draw inferences from patterns in data. Machine Learning is a branch of Artificial Intelligence (AI) where computers are taught to imitate human intelligence in that they solve complex tasks. Roles available to those proficient in Machine Learning include machine learning engineer, NLP scientist, and data engineer.
This program consists of courses that provide you with a solid theoretical understanding and considerable practice of the main algorithms, uses, and best practices related to Machine Learning. Topics covered include Supervised and Unsupervised learning, Regression, Classification, Clustering, Deep learning and Reinforcement learning.
You will follow along and code your own projects using some of the most relevant open-source frameworks and libraries, and you will apply what you have learned in various courses by completing a final capstone project.
Upon completion, you’ll have a portfolio of projects and a Professional Certificate from IBM to showcase your expertise. You’ll also earn an IBM Digital badge and will gain access to career resources to help you in your job search, including mock interviews and resume support.
What's inside
Two courses
Deep Learning and Reinforcement Learning
Deep Learning and Reinforcement Learning
Machine Learning Capstone
(0 hours)
Machine Learning Capstone
(0 hours)Learning objectives
- Master the most up-to-date practical skills and knowledge machine learning experts use in their daily roles
- Learn how to compare and contrast different machine learning algorithms by creating recommender systems in python
- Develop working knowledge of knn, pca, and non-negative matrix collaborative filtering
- Predict course ratings by training a neural network and constructing regression and classification models
- Master the most up-to-date practical skills and knowledge machine learning experts use in their daily roles
- Learn how to compare and contrast different machine learning algorithms by creating recommender systems in python
- Develop working knowledge of knn, pca, and non-negative matrix collaborative filtering
- Predict course ratings by training a neural network and constructing regression and classification models
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