The Certified Artificial Intelligence Practitioner™ (CAIP) specialization prepares learners to earn an industry validated certification which will differentiate themselves from other job candidates and demnstrate proficiency in the concepts of Artificial intelligence (AI) and machine learning (ML) found in CAIP.
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The Certified Artificial Intelligence Practitioner™ (CAIP) specialization prepares learners to earn an industry validated certification which will differentiate themselves from other job candidates and demnstrate proficiency in the concepts of Artificial intelligence (AI) and machine learning (ML) found in CAIP.
The Certified Artificial Intelligence Practitioner™ (CAIP) specialization prepares learners to earn an industry validated certification which will differentiate themselves from other job candidates and demnstrate proficiency in the concepts of Artificial intelligence (AI) and machine learning (ML) found in CAIP.
AI and ML have become an essential part of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This specialization shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users.
The specialization is designed for data science practitioners entering the field of artificial intelligence and will prepare learners for the CAIP certification exam.
Your journey to CAIP Certification
1) Complete the Coursera Certified Artificial Intelligence Practitioner Professional Certificate
2) Review the CAIP AIP Exam Blueprint
3) Purchase your CAIP Exam Voucher
4) Register for your CAIP Exam
What's inside
Five courses
Solve Business Problems with AI and Machine Learning
(0 hours)
Solve Business Problems with AI and Machine Learning
(0 hours)
Follow a Machine Learning Workflow
(0 hours)
Follow a Machine Learning Workflow
(0 hours)
Build Regression, Classification, and Clustering Models
(0 hours)
Build Regression, Classification, and Clustering Models
(0 hours)
Build Decision Trees, SVMs, and Artificial Neural Networks
(0 hours)
Build Decision Trees, SVMs, and Artificial Neural Networks
(0 hours)
Preparing for Your CertNexus Certification Exam
Preparing for Your CertNexus Certification Exam
Learning objectives
- Learn about the business problems that ai/ml can solve as well as the specific ai/ml technologies that can solve them.
- Learn important tasks that make up the workflow, including data analysis and model training and about how machine learning tasks can be automated.
- Use ml algorithms to solve the two most common supervised problems regression and classification, and a common unsupervised problem: clustering.
- Explore advanced algorithms used in both machine learning and deep learning. build multiple models to solve business problems within a workflow.
- Learn about the business problems that ai/ml can solve as well as the specific ai/ml technologies that can solve them.
- Learn important tasks that make up the workflow, including data analysis and model training and about how machine learning tasks can be automated.
- Use ml algorithms to solve the two most common supervised problems regression and classification, and a common unsupervised problem: clustering.
- Explore advanced algorithms used in both machine learning and deep learning. build multiple models to solve business problems within a workflow.
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