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Be an Artificial Intelligence Practitioner. . Master strategies to implement Artificial Intelligence techniques in order to solve business problems.
Instructors: Renée Cummings
8,067 already enrolled
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(94 reviews)
Recommended experience
Intermediate level
Understanding of fundamental AI concepts, experience working with databases and a high-level programming language such as Python, Java, or C/C++.
(94 reviews)
Recommended experience
Intermediate level
Understanding of fundamental AI concepts, experience working with databases and a high-level programming language such as Python, Java, or C/C++.
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.
Add to your LinkedIn profile
The Certified Artificial Intelligence Practitioner™ (CAIP) specialization prepares learners to earn an industry validated certification which will differentiate themselves from other job candidates and demonstrate 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 current version of the CAIP Exam Blueprint, available from CertNexus
3) Purchase your CAIP Exam Voucher at the CertNexus store
4) Register for your CAIP Exam
Applied Learning Project
At the conclusion of each course, learners will have the opportunity to complete a project which can be added to their portfolio of work. Projects include:
Create an AI project outline
Follow a machine learning workflow to predict demand
Build a regression, classification, or clustering model
Build a convolutional neural network (CNN)
Identify appropriate applications of AI and machine learning within a given business situation.
Formulate a machine learning approach to solve specific business problems.
Select appropriate tools to solve given machine learning problems.
Protect data privacy and promote ethical practices when developing and deploying AI and machine learning projects.
Collect and prepare a dataset to use for training and testing a machine learning model.
Analyze a dataset to gain insights.
Set up and train a machine learning model as needed to meet business requirements.
Communicate the findings of a machine learning project back to the organization.
Train and evaluate linear regression models.
Train binary and multi-class classification models.
Evaluate and tune classification models to improve their performance.
Train and evaluate clustering models to find useful patterns in unsupervised data.
Train and evaluate decision trees and random forests for regression and classification.
Train and evaluate support-vector machines (SVM) for regression and classification.
Train and evaluate multi-layer perceptron (ML) artificial neural networks (ANN) for regression and classification.
Train and evaluate convolutional neural networks (CNN) and recurrent neural networks (RNN) for computer vision and natural language processing tasks.
Differentiate between certifications and other validation techniques.
Schedule an exam on PearsonVUE and prepare to take an exam at a PearsonVUE test center or online via Pearson OnVUE.
Discover tools to prepare for certification exams.
Post and share your success after passing your CertNexus certification exam.
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
CertNexus is a vendor-neutral certification body, providing emerging technology certifications and micro-credentials for Business, Data, Development, IT, and Security professionals. CertNexus’ exams meet the most rigorous development standards possible which outlines a global framework for developing personnel certification programs to narrow the widening skills gap.
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
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It will take learners 5 months with an average of 2 hours per week learning time. Learners can complete the specialization in shorter length of time by spending more time per week.
To ensure your success in this course, you should have at least a high-level understanding of fundamental AI concepts, including, but not limited to: machine learning, supervised learning, unsupervised learning, artificial neural networks, computer vision, and natural language processing. You should also have experience working with databases and high-level programming languages such as Python, Java, or C/C++.
It is recommended that learners take the course in order.
Please contact your university to check for eligible credits.
Upon completion learners will be prepared to take the CAIP (AIP) exam offered on Pearson VUE by CertNexus. For more information and to purchase exam vouchers visit CertNexus.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Certificate, you’re automatically subscribed to the full Certificate. Visit your learner dashboard to track your progress.
Financial aid available,
¹ Median salary and job opening data are sourced from Lightcast™ Job Postings Report. Content Creator, Machine Learning Engineer and Salesforce Development Representative (1/1/2024 - 12/31/2024) All other job roles (3/1/2024 - 3/1/2025)