Google Apigee-API-Engineer : Google Cloud Apigee Certified API Engineer Exam Dumps

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Latest 2023 Updated Google Google Cloud Apigee Certified API Engineer Syllabus
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Exam Number : Apigee-API-Engineer
Exam Name : Google Cloud Apigee Certified API Engineer
Vendor Name : Google
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Apigee-API-Engineer Exam Format | Apigee-API-Engineer Course Contents | Apigee-API-Engineer Course Outline | Apigee-API-Engineer Exam Syllabus | Apigee-API-Engineer Exam Objectives

Exam Detail:
The Google Cloud Apigee Certified API Engineer (Apigee-API-Engineer) exam is designed to validate the knowledge and skills of individuals in designing, building, and managing APIs using the Apigee API platform. Here are the exam details for the Apigee-API-Engineer certification:

- Number of Questions: The exam typically consists of multiple-choice and multiple-select questions. The exact number of questions may vary, but typically, the exam includes around 50 to 60 questions.

- Time Limit: The time allocated to complete the exam is 2 hours.

Course Outline:
The Apigee-API-Engineer certification course covers various topics related to API engineering using the Apigee platform. The course outline typically includes the following areas:

1. Introduction to API Engineering:
- Understanding the role and importance of APIs in modern application development.
- Overview of the Apigee API platform and its features.

2. API Design:
- Designing RESTful APIs using best practices and industry standards.
- Implementing API design principles, such as resource modeling, versioning, and documentation.

3. API Security:
- Implementing authentication and authorization mechanisms for API access.
- Applying security controls, such as OAuth, API keys, and JWT tokens.

4. API Development and Implementation:
- Developing APIs using the Apigee Edge platform.
- Configuring API proxies, message transformation, and traffic management.

5. API Analytics and Monitoring:
- Implementing API monitoring and analytics using Apigee Edge.
- Generating reports and analyzing API usage patterns.

6. API Lifecycle Management:
- Managing the lifecycle of APIs, including versioning, deprecation, and retirement.
- Implementing change management processes and ensuring backward compatibility.

Exam Objectives:
The objectives of the Apigee-API-Engineer exam are as follows:

- Assessing candidates' understanding of API design principles and best practices.
- Evaluating candidates' ability to implement API security measures and manage access controls.
- Testing candidates' knowledge of API development and implementation using the Apigee platform.
- Evaluating candidates' proficiency in API analytics, monitoring, and lifecycle management.

Exam Syllabus:
The specific exam syllabus for the Apigee-API-Engineer certification covers the following topics:

1. API Engineering Fundamentals
2. API Design
3. API Security
4. API Development and Implementation
5. API Analytics and Monitoring
6. API Lifecycle Management

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Google Cloud Question Bank

Google Cloud Enterprise Search is getting even better with AI models

Google Cloud

In response to the limits of traditional enterprise search, Google Cloud has now lifted the lid on generative search, made possible using the company’s own generative AI technology.

In its announcement, Google explained how traditional search surfaces a list of links and requires manual investigation to locate the most relevant answers. With generative AI assistance, the company hopes to help users deal with more complex questions more quickly while handling summaries.

With Enterprise Search on Generative AI App Builder, organizations are able to create their own chatbots and semantic search applications.

Enterprise Search product lead Kalyan Pamarthy explains how organizations can build their own chatbots and semantic search applications in a matter of “a few minutes,” all with minimal coding, while leveraging Google’s enterprise-grade management and security.

> The best AI writers

> Google Cloud has finally made a profit for the first time

> Google Cloud is building its most powerful supercomputer to date

Keen to sing its own praises, Google touches on how previous attempts to combine generative AI and search technology have been poor, lacking scalability and being susceptible to data-leaks, among other concerns.

Enterprise Search, with its injection of AI, will now be able to handle multimodal data, including images, as well as multi-turn and in-line conversations to allow users to ask follow-up questions.

As a service model, Pamarthy stresses how enterprises can focus on building their best product without the worries of handling the cloud complexity behind the scenes.

For those looking to get more out of their Enterprise Search product, Gen App Builder can also be integrated with Google Cloud’s Vertex AI for foundation model tuning.

Enterprise Search on Gen App Builder is generally available for customers on the allowlist, and those looking to try out the new tool should contact Google Cloud for pricing details in relation to their own enterprise and existing Google services.

Cohesity leverages Google Cloud ties to bolster data security platform

Data security and management firm Cohesity announced that it has enhanced its partnership with Google Cloud by integrating its Cohesity Data Cloud platform with the latter's Vertex AI, VentureBeat reports. Integrating Cohesity with Vertex AI enables users to assess their data for anomalies and data patterns and perform speedy data recovery through contextual searches, according to the company. With so many potential attack vectors and rapidly growing data estates, in the event of a breach, AI could easily allow joint customers to ask natural questions, quickly search across exabytes [of data] and receive responses that are actionable and human-readable almost instantly, so that IT and security staff can assess risks quickly, and operators can streamline their response protocols, said Cohesity CEO Sanjay Poonen. Cohesity also announced Cohesity Turing, an AI-powered suite of tools that can generate profound AI-driven insights for companies. These may include ways to improve operational efficiencies, enhanced detection of security risks and greater value from data. Enterprises can detect threats and discover sensitive data. They can simplify threat detection with one-click scanning and automated threat feeds updated daily, Poonen said.

The Future of Generative AI from Google Cloud: What You Need to Know

Google has been continuously making AI accessible to everyone and in its recent initiative, it has launched Google Cloud's Generative AI course that is free of cost. Read below to learn more

Generative AI is a continuously growing field that can revolutionize many industries. Recently, Google Cloud is launching a lot of new initiatives to get at the forefront of this revolution. In its recent approach, Google has launched new Generative AI courses, and here are all the details.

What is Generative AI?

Generative AI is a type of artificial intelligence that can create new content, such as images, text, or music. This is in contrast to traditional AI, which is focused on analyzing and understanding existing data.

Google in its blog mentioned “Generative AI is a new type of ML that has made a lot of headlines recently. Research from CIO Dive finds that seven in 10 executives say their companies are investigating or exploring generative AI.

“Now is a great time to become an expert, while we are at the cusp of this technology becoming more widely adopted.”

Nowadays, users can easily access platforms like ChatGPT and Bard to generate new answers to their questions and learn new things.

This is the capability of AI, it can reduce human efforts and might provide real-time information and accurate data.

Generative AI is still in its early stages, but it has the potential to be used in a wide range of applications. For example, it could be used to create realistic synthetic data for training machine learning models or to generate personalized content for users.

Some of the key features of Google Cloud's Generative AI include:

Large Language Models: Google Cloud offers a number of large language models, including BERT, GPT-3, and LaMDA. These models can be used to generate text, translate languages, and answer questions.

Image Generation: Apart from text and answering questions, Google Cloud also offers a number of image generation models, including Imagen and Parti. These models can be used to create realistic images from text descriptions.

Audio Generation: Google Cloud is also working on audio generation models, including WaveNet and Tacotron. These models can be used to create realistic audio from text descriptions.

Although some of these models are not completely available for users, Google is working continuously to bring more AI products to the market.

What is Google's Free Generative AI Courses?

Google has now unveiled a number of free generative AI courses that can help people learn more about this exciting new field. These courses are developed to provide the ability to users to build their own generative AI models.

The eleven free courses on generative AI cover a range of topics, including:

Introduction to Generative AI

Introduction to Large Language Models

Introduction to Responsible AI

Generative AI Fundamentals

Introduction to Image Generation

Encoder-Decoder Architecture

Attention Mechanism

Transfer Models and BERT Model

Create Image Captioning Models

Introduction to Generative AI Studio

And a Quest that is titled- Generative AI Explorer - Vertex AI

Jagranjosh

Source: Google

These courses are available on Google Cloud's Skill Boost platform. Users can access the courses for free and earn a virtual badge upon completion.

By making generative AI more accessible, Google is helping to ensure that everyone has the opportunity to learn about this cutting-edge technology and contribute to its development.

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