Профессиональная сертификация 'CertNexus Certified Artificial Intelligence Practitioner'
Be an Artificial Intelligence Practitioner. . Master strategies to implement Artificial Intelligence techniques in order to solve business problems.
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Чему вы научитесь
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.
Приобретаемые навыки
Профессиональная сертификация: общие сведения
Проект прикладного обучения
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)
Learners should have a high-level understanding of fundamental AI concepts, and have experience working with databases and a high-level programming language such as Python, Java, or C/C++.
Learners should have a high-level understanding of fundamental AI concepts, and have experience working with databases and a high-level programming language such as Python, Java, or C/C++.
Профессиональная сертификация включает несколько курсов: 5
Solve Business Problems with AI and Machine Learning
Artificial intelligence (AI) and machine learning (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.
Follow a Machine Learning Workflow
Machine learning is not just a single task or even a small group of tasks; it is an entire process, one that practitioners must follow from beginning to end. It is this process—also called a workflow—that enables the organization to get the most useful results out of their machine learning technologies. No matter what form the final product or service takes, leveraging the workflow is key to the success of the business's AI solution.
Build Regression, Classification, and Clustering Models
In most cases, the ultimate goal of a machine learning project is to produce a model. Models make decisions, predictions—anything that can help the business understand itself, its customers, and its environment better than a human could. Models are constructed using algorithms, and in the world of machine learning, there are many different algorithms to choose from. You need to know how to select the best algorithm for a given job, and how to use that algorithm to produce a working model that provides value to the business.
Build Decision Trees, SVMs, and Artificial Neural Networks
There are numerous types of machine learning algorithms, each of which has certain characteristics that might make it more or less suitable for solving a particular problem. Decision trees and support-vector machines (SVMs) are two examples of algorithms that can both solve regression and classification problems, but which have different applications. Likewise, a more advanced approach to machine learning, called deep learning, uses artificial neural networks (ANNs) to solve these types of problems and more. Adding all of these algorithms to your skillset is crucial for selecting the best tool for the job.
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CertNexus
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.
Часто задаваемые вопросы
Получу ли я зачеты в университете за прохождение специализации?
Can I just enroll in a single course?
Можно ли зарегистрироваться только на один курс?
Действительно ли это полностью дистанционный курс? Нужно ли мне посещать какие-либо занятия лично?
Сколько времени занимает получение специализации?
Do I need to take the courses in a specific order?
Will I earn university credit for completing the Specialization?
Получу ли я зачеты в университете за прохождение специализации?
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