You will detect the different bugs to ensure the quality and proper functioning of mobile applications thanks to this 100% online program"

When designing mobile applications, specialists must keep in mind the Testing lifecycle. This alludes to the different phases that make up the planning, design, execution and monitoring of tests during the development of assets. In order to improve the efficiency and quality of these procedures, IT experts take advantage of Machine Learning tools. In this sense, AI improves every activity by speeding up ttesting, automating repetitive tasks and providing additional insights for informed decision making in mobile application development.

To optimize these procedures, TECH has implemented an advanced Postgraduate certificate focused on automated test creation through AI. Developed by an experienced teaching staff, the curriculum will address Test Cases and bug detection in detail. The syllabus will also provide the keys to create the most effective test plans, which will help students to develop the most innovative mobile applications in the telecommunications market. The didactic materials will also provide students with the most modern Machine Learning tools for Web Testing. Moreover, the program will real cases and by solving complex situations in simulated learning environments. In addition, experts will be able to individually plan their schedules and educational timetables.

Thanks to the fact that this Postgraduate certificate is taught in a 100% online mode, computer scientists will have the opportunity to update their knowledge in the field of Testing in AI Applications without the need to make daily trips to an academic center. In addition, they will have at their disposal a wide variety of didactic resources in multimedia supports such as complementary readings or interactive summaries. It should be noted that the university program is based on the Relearningteaching system, of which TECH is a pioneer. This method consists of reiterating the key aspects of the syllabus in a natural and progressive way to ensure that they remain in the student's mind.

You will design innovative and creative projects adapted to the requirements of a growing technological sector"

This Postgraduate certificate in Artificial Intelligence Application Testing contains the most complete and up-to-date program on the market. The most important features include:

• The development of practical cases presented by experts in Artificial Intelligence in programming.
• The graphic, schematic, and practical contents with which they are created, provide scientific and practical information on the disciplines that are essential for professional practice.
• Practical exercises where the self-assessment process can be carried out to improve learning
• Its special emphasis on innovative methodologies
• Theoretical lessons, questions to the expert, debate forums on controversial topics, and individual reflection assignments
• Content that is accessible from any fixed or portable device with an Internet connection

You will become an API Testing specialist and evaluate the functionality, performance and security of Application Programming Interface tests! “

The program’s teaching staff includes professionals from the sector who contribute their work experience to this program, as well as renowned specialists from leading societies and prestigious universities.

The multimedia content, developed with the latest educational technology, will provide the professional with situated and contextual learning, i.e., a simulated environment that will provide immersive education programmed to learn in real situations.

This program is designed around Problem-Based Learning, whereby the professional must try to solve the different professional practice situations that arise during the academic year For this purpose, the students will be assisted by an innovative interactive video system created by renowned and experienced experts.

You will create test plans aimed at establishing sound strategies, verifying that programs are properly executed prior to market launch"

Thanks to the Relearning system used by TECH you will reduce the long hours of study and memorization"

This Postgraduate certificate will guide students through the Testing life cycle, starting from the creation of test cases to the detection of bugs. In this way, the curriculum will analyze in detail various types of tests, among which functionality, compatibility or performance tests stand out. The syllabus will also delve into time-saving automation. The teaching materials will also explore the use of AI-powered QA tools Students will acquire a complete vision that will ensure the efficiency and reliability of software products.

You will create automated tests with Artificial Intelligence to execute procedures in an agile and frequent way"

Module 1. AI for QA Testing

1.1 Testing Life Cycle

1.1.1. Description and Understanding of the Testing Life Cycle in Software Development
1.1.2. Phases of the  Testing Life Cycle and Its Importance for Quality Assurance
1.1.3. Integration of Artificial Intelligence in Different Stages of the Testing Life Cycle
1.1.4. Strategies for Continuous Improvement of the Testing Life Cycle using AI

1.2. Test Cases and Bug Detection

1.2.1. Effective Test Case Design and Writing in the QA Testing Context
1.2.2. Identification of Bugs and Errors during Test Case Execution
1.2.3. Application of Early Bug Detection Techniques using Static Analysis
1.2.4. Use of Artificial intelligence Tools for the Automatic Identification of Bugs in Test Cases

1.3. Types of Testing

1.3.1. Exploration of Different Types of Testing in the QA Domain
1.3.2. Unit, Integration, Functional, and Acceptance Testing: Characteristics and Applications
1.3.3. Strategies for the Selection and Appropriate Combination of Testing Types in AI Projects
1.3.4. Adaptation of Conventional Testing Types to Projects with Artificial Intelligence Components

1.4. Creating a Test Plan

1.4.1. Designing and Structuring a Comprehensive Test Plan
1.4.2. Identifying Requirements and Test Scenarios in AI Projects
1.4.3. Strategies for Manual and Automated Test Planning
1.4.4. Continuous Evaluation and Adjustment of the Test Plan as the Project Develops

1.5. AI Bug Detection and Reporting

1.5.1. Implementation of Automatic Bug Detection Techniques using Machine Learning Algorithms
1.5.2. Use of Artificial Intelligence Tools for Dynamic Code Analysis in Search of Possible Errors
1.5.3. Strategies for Automatic Generation of Detailed Reports on AI-Detected Bugs
1.5.4. Effective Collaboration between Development and QA Teams in the Management of AI-Detected Bugs

1.6. Creation of Automated Testing with AI

1.6.1. Development of Automated Test Scripts for Projects with AI Components
1.6.2. Integration of AI-based Test Automation Tools
1.6.3. Use of Machine Learning Algorithms for Dynamic Generation of Automated Test Cases
1.6.4. Strategies for Efficient Execution and Maintenance of Automated Test Cases in AI Projects

1.7. API Testing

1.7.1. Fundamental Concepts of API Testing and Its Importance in QA
1.7.2. Development of Tests for API Verification in Environments with Artificial Intelligence Components
1.7.3. Strategies for Data and Results Validation in API Testing with AI
1.7.4. Use of Specific Tools for API Testing in Artificial Intelligence Projects

1.8. AI Tools for Web Testing

1.8.1. Exploring Artificial Intelligence Tools for Test Automation in Web Environments
1.8.2. Integration of Element Recognition and Visual Analysis Technologies in Web Testing
1.8.3. Strategies for Automatic Detection of Changes and Performance Problems in Web Applications using AI
1.8.4. Evaluation of Specific Tools for Improving Efficiency in Web Testing with AI

1.9. Mobile Testing  Using AI

1.9.1. Development of Testing Strategies for Mobile Applications with Artificial Intelligence Components
1.9.2. Integration of Specific Testing Tools for AI-based Mobile Platforms
1.9.3. Use of Machine Learning Algorithms for the Detection of Performance Problems in Mobile Apps
1.9.4. Strategies for the Validation of Specific Mobile Application Interfaces and Functions using AI

1.10. QA Tools with AI

1.10.1. Exploration of QA Tools and Platforms that Incorporate Artificial Intelligence Functionalities
1.10.2. Evaluation of Tools for Efficient Test Management and Execution in AI Projects
1.10.3. Use of Machine Learning Algorithms for Test Case Generation and Optimization
1.10.4. Strategies for Effective Selection and Adoption of QA Tools with AI Capabilities

This university program prepares you for the present and future challenges of Mobile Testing. Bet on TECH and experience immediate career advancement!"