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Microsoft Azure Developer

Creating and Integrating AI with Azure Services

AI is no longer science fiction or the exclusive domain of scientists. In this course, you will explore the landscape of AI in the Microsoft space, and will examine some practical examples to get you started.

AI is all around us, and it is no longer just the work of scientists. In this introductory course, Microsoft Azure Developer: Creating and Integrating AI with Azure Services, you will learn about the AI Landscape in Azure. You will learn about Cognitive services, which are all about bringing the power of AI within your reach, with a simple REST API call. You will also learn about Azure Machine Learning services, which is an enterprise-class AI solution, backed by the power of the cloud. And you will also get familiarized with conversational AI and the Bot Framework. By the end of this course, you will have a good understanding of the use and applicability of AI, and how Azure can help you achieve your AI goals.

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What's inside

Syllabus

Course Overview

What Is AI and Machine Learning?

Understanding Microsoft Cognitive Services

Using Microsoft Cognitive Services

Going Beyond with Custom AI Models

Building with Conversational AI

Wrapping Up

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops foundational knowledge about AI, which is a core skill for software engineers

Taught by Sahil Malik, who is recognized for their work in AI

Examines conversational AI, which is highly relevant to chatbots and virtual assistants

Uses Microsoft Cognitive Services, which is standard in industry

Explores Azure Machine Learning, which is enterprise-class

May be better suited for beginners, as it provides a solid foundation in Microsoft AI

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Career center

Learners who complete Microsoft Azure Developer: Creating and Integrating AI with Azure Services will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models. With the knowledge gained from completing this course, aspiring Machine Learning Engineers will be introduced to fundamental concepts in machine learning and practical examples to get them started in the field.

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Data Scientist

Data Scientists use scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured.

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Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. They use their findings to make recommendations and improve business processes.

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AI Engineer

The AI Engineer designs, builds, deploys, and maintains AI systems. They work with data scientists and machine learning engineers to develop and implement AI solutions. This course may be useful for those who want to become AI Engineers as it provides a foundation in AI and machine learning concepts.

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Cloud Architect

Cloud Architects design, build, and manage cloud computing systems. They work with customers to understand their business needs and develop cloud solutions that meet those needs.

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Business Analyst

Business Analysts work with stakeholders to define and solve business problems. They use their understanding of business processes and data to develop solutions that improve efficiency and effectiveness.

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Software Engineer

Software Engineers apply engineering principles to the design, development, deployment, and maintenance of software systems.

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Project Manager

Project Managers plan, execute, and close projects. They work with stakeholders to define project scope, develop project plans, and manage project budgets.

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Product Manager

Product Managers are responsible for the development and launch of new products. They work with cross-functional teams to define product requirements, develop product roadmaps, and manage product launches.

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Marketing Manager

Marketing Managers develop and execute marketing campaigns to promote products and services. They work with cross-functional teams to develop marketing strategies, create marketing materials, and manage marketing budgets.

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Technical Writer

Technical Writers create and maintain documentation for software and hardware products. They work with engineers and product managers to develop clear and concise documentation that helps users understand how to use products.

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Customer Success Manager

Customer Success Managers are responsible for ensuring customer satisfaction. They work with customers to resolve issues, provide training, and build relationships.

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UX Designer

UX Designers design the user experience for websites and mobile apps. They work with product managers and engineers to create user interfaces that are easy to use, accessible, and visually appealing.

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UI Designer

UI Designers create the visual design for websites and mobile apps. They work with UX Designers and engineers to create user interfaces that are visually appealing, consistent, and easy to use.

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Sales Manager

Sales Managers lead and motivate sales teams to achieve sales targets. They develop sales strategies, manage sales pipelines, and close deals.

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Time

81 hours

Level

Introductory

Via

Pluralsight

Instructor

Sahil Malik

Language

English

Microsoft Azure Developer: Creating and Integrating AI with Azure Services belongs to the following collections:

Good to know

Develops foundational knowledge about AI, which is a core skill for software engineers

Taught by Sahil Malik, who is recognized for their work in AI

Examines conversational AI, which is highly relevant to chatbots and virtual assistants

Uses Microsoft Cognitive Services, which is standard in industry

Explores Azure Machine Learning, which is enterprise-class

May be better suited for beginners, as it provides a solid foundation in Microsoft AI

Share and help others discover this course.

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