CertNexus
CertNexus Certified Artificial Intelligence Practitioner Professional Certificate
CertNexus

CertNexus Certified Artificial Intelligence Practitioner Professional Certificate

Be an Artificial Intelligence Practitioner.. Master strategies to implement Artificial Intelligence techniques in order to solve business problems.

Megan Smith Branch
Stacey McBrine
Anastas Stoyanovsky

Instructors: Megan Smith Branch

Included with Coursera Plus

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Earn a career credential that demonstrates your expertise
4.4

(105 reviews)

Intermediate level

Recommended experience

Flexible schedule
2 months at 10 hours a week
Learn at your own pace
Earn a Certificate
With paid plans
Earn a career credential that demonstrates your expertise
4.4

(105 reviews)

Intermediate level

Recommended experience

Flexible schedule
2 months at 10 hours a week
Learn at your own pace
Earn a Certificate
With paid plans

What you'll learn

  • 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.

Details to know

Shareable certificate

Add to your LinkedIn profile

Industry certification
Taught in English
21 practice exercises

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Professional Certificate - 5 course series

Solve Business Problems with AI and Machine Learning

Solve Business Problems with AI and Machine Learning

Course 111 hours

What you'll learn

  • 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.

Skills you'll gain

Machine Learning, Responsible AI, Solution Design, MLOps (Machine Learning Operations), Business Ethics, AI Product Strategy, Data-Driven Decision-Making, Business Solutions, Machine Learning Algorithms, Applied Machine Learning, Project Implementation, Artificial Intelligence and Machine Learning (AI/ML), Compliance Management, and Data Ethics
Follow a Machine Learning Workflow

Follow a Machine Learning Workflow

Course 219 hours

What you'll learn

  • 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.

Skills you'll gain

Data Collection, Machine Learning, Data Analysis, Artificial Intelligence and Machine Learning (AI/ML), Data Modeling, Machine Learning Algorithms, MLOps (Machine Learning Operations), Exploratory Data Analysis, Workflow Management, Process Management, Statistical Analysis, Predictive Modeling, Data Cleansing, and Applied Machine Learning
Build Regression, Classification, and Clustering Models

Build Regression, Classification, and Clustering Models

Course 320 hours

What you'll learn

  • 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.

Skills you'll gain

Regression Analysis, Machine Learning, Supervised Learning, Linear Algebra, Machine Learning Algorithms, Unsupervised Learning, Predictive Modeling, Performance Tuning, Statistical Modeling, Classification And Regression Tree (CART), Applied Machine Learning, Dimensionality Reduction, Algorithms, and Feature Engineering
Build Decision Trees, SVMs, and Artificial Neural Networks

Build Decision Trees, SVMs, and Artificial Neural Networks

Course 421 hours

What you'll learn

  • 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.

Skills you'll gain

Artificial Neural Networks, Deep Learning, Supervised Learning, Natural Language Processing, Decision Tree Learning, Computer Vision, Random Forest Algorithm, Machine Learning Algorithms, Applied Machine Learning, and Regression Analysis
Preparing for Your CertNexus Certification Exam

Preparing for Your CertNexus Certification Exam

Course 52 hours

What you'll learn

  • 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.

Skills you'll gain

Registration, Productivity, System Requirements, Collaboration, Professional Development, Test Planning, Learning Strategies, and Goal Setting

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Megan Smith Branch
1 Course22,170 learners
Stacey McBrine
CertNexus
8 Courses23,235 learners

Offered by

CertNexus

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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 (10/1/2024 - 10/1/2025)