What will I be able to do upon completing the Specialization?

Upon completion, you will be able to explain core AI and machine learning concepts, analyze data using Python, build and evaluate basic machine learning models, and apply AI solutions using AWS services in real-world and industry-relevant scenarios.

Is this course really 100% online? Do I need to attend any classes in person?

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.

Can I just enroll in a single course?

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. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Will I earn university credit for completing the Specialization?

This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

Apply AI Foundations with Python and AWS 专项课程

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Apply AI Foundations with Python and AWS 专项课程

AI Fundamentals with Python and AWS.

Build strong AI foundations and apply machine learning concepts using Python and AWS services.

位教师：EDUCBA

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4 门课程系列

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4 门课程系列

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4 周完成

在 10 小时一周

灵活的计划

自行安排学习进度

您将学到什么

Explain core artificial intelligence concepts, reasoning methods, and ethical considerations.
Apply Python libraries to analyze data and build foundational machine learning models.
Evaluate and apply AI solutions using AWS services in real-world use cases.

您将获得的技能

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专业化 - 4门课程系列

This Specialization provides a structured and practical introduction to artificial intelligence, covering core AI concepts, machine learning fundamentals, deep learning principles, and real-world AI applications. Learners gain hands-on experience using Python tools and AWS AI services to analyze data, build models, and evaluate intelligent systems. The program emphasizes ethical AI, industry-aligned workflows, and scalable cloud-based implementations to prepare learners for real-world and certification-oriented roles.

应用的学习项目

Learners will complete applied projects that involve data exploration, visualization, and the development of basic machine learning models using Python libraries and AWS AI services. These projects simulate real-world scenarios, enabling learners to apply AI reasoning, model evaluation, and cloud-based deployment concepts to solve practical business and industry problems.

Understand and Apply AI Fundamentals with AWS

第 1 门课程, 小时

您将学到什么

Explain core AI, machine learning, and deep learning concepts and how AI systems work.
Analyze AI applications such as NLP, computer vision, generative AI, and ethical AI practices.
Evaluate and apply AWS AI services to design real-world, scalable AI solutions.

您将获得的技能

类别：Artificial Intelligence

类别：Amazon Web Services

类别：Reinforcement Learning

类别：Unsupervised Learning

类别：Deep Learning

类别：Ethical Standards And Conduct

类别：Supervised Learning

类别：Natural Language Processing

类别：Convolutional Neural Networks

类别：AWS SageMaker

类别：Machine Learning

类别：Artificial Intelligence and Machine Learning (AI/ML)

类别：Applied Machine Learning

类别：Model Deployment

类别：Responsible AI

Apply Artificial Intelligence Using Python for Beginners

第 2 门课程, 小时

您将学到什么

Explain core Artificial Intelligence concepts and how Python supports AI workflows.
Apply NumPy for numerical computing and data manipulation.
Analyze and visualize data using Matplotlib and Seaborn to identify patterns and insights.

您将获得的技能

类别：AI Workflows

类别：Artificial Intelligence

Understand and Apply Artificial Intelligence Fundamentals

第 3 门课程, 小时

您将学到什么

Explain core AI concepts and analyze intelligent reasoning and search-based methods.
Apply machine learning techniques including supervised, unsupervised, and clustering methods.
Evaluate reinforcement learning approaches used in real-world intelligent systems.

您将获得的技能

类别：Artificial Intelligence and Machine Learning (AI/ML)

类别：Data-Driven Decision-Making

类别：Data Ethics

Learn & Build Machine Learning Models with Python

第 4 门课程, 小时

您将学到什么

Explain core machine learning concepts and prepare data using Python libraries.
Visualize and analyze datasets using NumPy, Pandas, and Matplotlib.
Build and evaluate basic machine learning models using Scikit-learn.

您将获得的技能

类别：Data Preprocessing

类别：Pandas (Python Package)

类别：NumPy

类别：Scikit Learn (Machine Learning Library)

类别：Regression Analysis

类别：Model Evaluation

类别：Exploratory Data Analysis

类别：Data Manipulation

类别：Applied Machine Learning

类别：Matplotlib

类别：Machine Learning

类别：Supervised Learning

类别：Python Programming

类别：Feature Engineering

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常见问题

The Specialization can be completed in approximately 15 to 16 weeks with a recommended time commitment of 3–4 hours per week. This schedule allows learners to progress comfortably through conceptual lessons, hands-on practice, assessments, and applied projects, while building a strong and practical foundation in artificial intelligence using Python and AWS.

No prior experience in artificial intelligence is required. Basic computer literacy and an interest in AI concepts are sufficient, while any familiarity with programming or mathematics is helpful but not mandatory.

Yes, the courses are designed to be taken in a structured sequence, starting with AI fundamentals and Python basics, and gradually progressing to machine learning and cloud-based AI applications to ensure a smooth learning experience.