Address the development in the best digital university in the world according to Forbes”

Improving productivity in software development with Machine Learning has a significant impact on the quality of IT projects. For example, its systems allow applications to improve over time and adapt to user needs. As a result, professionals implement development processes that are both more efficient and cost-effective. In this way, companies gain competitive advantages by being able to adapt quickly to changing market needs and deliver goods or services immediately.  This allows them to differentiate themselves from their competitors, while launching innovative products to capture the public's attention.

In order to optimize these procedures through AI, TECH is launching an exclusive program aimed at IT professionals. The curriculum will focus on the integration of Machine Learning in database management, allowing students to search for potential bugs in software and create unit tests. The syllabus will also delve into how students can optimize deployment processes on web pages. Furthermore, the teaching materials will delve into the many benefits of cloud computing, including greater scalability of resources in a flexible manner. The program is designed to provide knowledge for 450 hours of study, and all theoretical and practical knowledge is presented through high-quality multimedia content, master classes, lectures, and video techniques that allow for the exchange of learning. 

This program is taught in online format and uses the Relearning methodology based on the reiteration of fundamental concepts throughout the syllabus to facilitate the integration of knowledge in a natural and progressive way. In addition, the professional will be able to access the materials and tools at any time and from anywhere.  In this way, they will be able to combine their professional tasks and their personal lives with a first class program and updating.  

You will implement effective strategies with which you will optimize the deployment of your websites and respond with immediacy to market demands"

This Postgraduate diploma in Multiplatform Application Development using Artificial Intelligence 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 it is conceived scientific and practical information on those 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

Do you want to specialize in Firebase Configuration? Achieve your goals with this innovative program in just 6 months"

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 delve into machine translation between different programming languages, creating applications that work on a variety of platforms"

The Relearning system applied by TECH in its programs reduces the long hours of study so frequent in other teaching methods"

This academic path will cover from the configuration of the development environment to the management of repositories.  The learning materials will highlight the integration of AI elements in Visual Studio Code and code optimization with ChatGPT. At the same time, the syllabus will delve into the practical application of Machine Learning in web projects, promoting highly efficient deployments. In this line, students will work on projects with LAMP and MEVN to gain diversified experience. The program will also guide students in the development of mobile applications, creating spaces with Gothub Copilut and properly configuring Firebase. 

You will optimize codes using ChatGPT and generate automatic documentations for easy understanding”

Module 1. Improving Software Development Productivity with Artificial Intelligence  

1.1. Prepare a Suitable Development Environment
1.2. Essential AI Extensions for Visual Studio Code 
1.3. No-code  Design of User Interfaces with AI Elements 
1.4. Code Optimization using ChatGPT 
1.5. Repository Management with AI 
1.6. Integration of AI in Database Management
1.7. Fault Finding and Creation of Unit Tests with AI
1.8. Pair Programming with GitHub Copilot 
1.9. Automatic Translation between Programming Languages 
1.10. Recommended AI Tools to Improve Productivity 

Module 2. Web Projects with Artificial Intelligence 

2.1. Preparation of the Working Environment for Web Development with AI
2.2. Workspace Creation for AI Projects
2.3. Design Patterns in AI Products
2.4. Frontend Development with AI 
2.5. Database Creation 
2.6. Back-End Development with AI 
2.7. Optimizing Your Web Deployment Process 
2.8. AI in Cloud Computing 
2.9. Creating an AI-enabled Project for LAMP Environments 
2.10. Creating an AI-enabled Project for MEVN Environments

Module 3. Mobile Applications with Artificial Intelligence

3.1. Preparation of Working Environment for Mobile Development with AI    
3.1.1. Configuration of Mobile Development Environments for Projects with Artificial Intelligence
3.1.2. Selection and Preparation of Specific Tools for  Mobile Application Development with AI
3.1.3. Integration of AI Libraries and Frameworks in Mobile Development Environments
3.1.4. Configuration of Emulators and Real Devices for Testing Mobile Applications with AI Components

3.2. Creating a Workspace with GitHub Copilot

3.2.1. Integration of GitHub Copilot in Mobile Development Environments
3.2.2. Effective Use of GitHub Copilot for Code Generation in AI Projects
3.2.3. Strategies for Developer Collaboration when using GitHub Copilot in the Workspace
3.2.4. Best Practices and Limitations in the Use of GitHub Copilot in Mobile Application Development with AI

3.3. Firebase Configuration

3.3.1. Initial Configuration of a Firebase Project for Mobile Development
3.3.2. Firebase Integration in Mobile Applications with Artificial Intelligence Functionalities
3.3.3. Use of Firebase Services as a Database, Authentication and Notifications in AI Projects
3.3.4. Strategies for Real-Time Data and Event Management in Firebase-enabled Mobile Applications

3.4. Concepts of Clean Architecture, DataSources, Repositories    

3.4.1. Fundamental Principles of Clean Architecture in Mobile Development with AI
3.4.2. Implementation of DataSources and Repositories Layers in Clean Architectures    
3.4.3. Design and Structuring of Components in Mobile Projects with a Focus on Clean Architecture
3.4.4. Benefits and Challenges of Implementing Clean Architecture in Mobile Applications with AI

3.5. Authentication Screen Creation    

3.5.1. Design and Development of User Interfaces for Authentication Screens in Mobile Applications with AI
3.5.2. Integration of Authentication Services with Firebase in the Login Screen    
3.5.3. Use of Security and Data Protection Techniques in the Authentication Screen
3.5.4. Personalization and Customization of the User Experience on the Authentication Screen

3.6. Dashboardand Navigation Creation

3.6.1. Dashboard Design and Development with Artificial Intelligence Elements
3.6.2. Implementation of Efficient Navigation Systems in Mobile Applications with AI
3.6.3. Integration of AI Functionalities in the Dashboard to Improve User Experience    

3.7. Creation of Listing Screen

3.7.1. Development of User Interfaces for AI-enabled Mobile Application Listing Displays
3.7.2. Integration of Recommendation and Filtering Algorithms in the Listing Screen
3.7.3. Use of Design Patterns for Effective Data Presentation in the Listing Screen
3.7.4. Strategies for Efficient Real-Time Data Loading in the Listing Screen

3.8. Creating Detail Screen

3.8.1. Design and Development of Detailed User Interfaces for the Presentation of Specific Information
3.8.2. Integration of AI Functionalities to Enrich the Detail Screen
3.8.3. Implementation of Interactions and Animations in the Detail Screen
3.8.4. Strategies for Performance Optimization in Loading and Detail Display in AI-enabled Mobile Applications

3.9. Creating Settings Screen

3.9.1. Development of User Interfaces for Configuration and Settings in AI-enabled Mobile Applications
3.9.2. Integration of Custom Settings Related to AI Components
3.9.3. Implementing Customization Options and Preferences in the Configuration Screen
3.9.4. Strategies for Usability and Clarity in the Presentation of Options in the Settings Screen

3.10. Creating Icons, Splash  and Graphic Resources for Your App with AI    

3.10.1. Designing and Creating Attractive Icons to Represent Your AI Mobile Application
3.10.2. Developing Splash Screens with Impressive Visual Elements
3.10.3. Selection and Adaptation of Graphic Resources to Enhance the Aesthetics of the Mobile Application
3.10.4. Strategies for Consistency and Visual Branding in AI Application Graphics Elements

The teaching materials of this program, elaborated by these specialists, have contents that are completely applicable to your professional experiences”