Manage the adaptation of machine translation algorithms at the world's best digital university according to Forbes"  

Assisted Software Application Development using Machine Learning is an approach aimed at optimizing the process of creating software. The importance of this technology lies in several key benefits it brings to application development. For example, it is able to automate repetitive or tedious tasks in the execution of applications. This frees developers from routine tasks and allows them to focus on more strategic aspects of the project. In addition, AI tools are used to locate and fix bugs faster, which considerably reduces the time required to bring programs to market.

In this context, TECH creates a revolutionary program for Computer Science experts that will offer the keys to improve productivity in Software Development with AI. Designed by experts in the field, the curriculum will delve into the most important extensions for Visual Studio Code, which will allow graduates to customize development environments to improve efficiency. At the same time, the syllabus will analyze in detail the management of repositories, from the automation of technical version control processes to the integration of AI in database management. The program will also provide the most innovative tools for automatic translation for the different programming languages.  

One of the advantages of being part of this unique academic opportunity is based on the convenience and adaptability provided. TECH is a pioneer in the implementation of the Relearning pedagogical methodology, which provides didactic and multimedia content repeatedly to expand and improve the assimilation of concepts. All of this is complemented with case studies refuted by the best experts in the field. It is therefore the perfect opportunity to combine learning with personal life.

You will master most advanced Artificial Intelligence Tools to Improve Productivity”  

This Postgraduate certificate in Assisted Development of Software Applications 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 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'll integrate improved communication and collaboration between developers with GitHub Copilot"

The program’s teaching staff includes professionals from the field who contribute their work experience to this educational 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 perform early detection of vulnerabilities and bugs using Static Analysis"

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

This program will provide computer scientists with a holistic view of the configuration of the software development environment using AI. To achieve this, the curriculum will delve into repository management by combining elements in Visual Studio Code and ChatGPT. This will allow students to perform predictive analysis of changes, to implement improvements in the organization. Likewise, the syllabus will analyze the design of the No-code User Interfaces in order to optimize productivity in the projects. In this sense, graduates will improve interoperability between different languages through automatic translation.

A unique, key and decisive learning experience that will boost your professional development in just 6 weeks"

Module 1. Improving Software Development Productivity with AI         

1.1. Prepare a Suitable Development Environment

1.1.1. Selection of Essential Tools for AI Development
1.1.2. Configuration of the Chosen Tools
1.1.3. Implementation of CI/CD Ppipelines Adapted to AI Projects
1.1.4. Efficient Management of Dependencies and Versions in Development Environments

1.2. Essential AI Extensions for Visual Studio Code

1.2.1. Exploring and Selecting AI Extensions for Visual Studio Code
1.2.2. Integration of Static and Dynamic Analysis Tools in the SDI
1.2.3. Automation of Repetitive Tasks with Specific Extensions
1.2.4. Customization of the Development Environment to Improve Efficiency

1.3. No-code Design of User Interfaces with AI Elements

1.3.1. No-code Design Principles and Their Application to User Interfaces
1.3.2. Incorporation of AI Elements in the Visual Design of Interfaces
1.3.3. Tools and Platforms for No-code Creation of Intelligent Interfaces
1.3.4. Evaluation and Continuous Improvement of No-code Interfaces with AI

1.4. Code Optimization using ChatGPT    

1.4.1. Identifying Duplicate Code
1.4.2. Refactor     
1.4.3. Create Readable Code    
1.4.4. Understanding What Code Does
1.4.5. Improving Variable and Function Names
1.4.6. Automatic Documentation Creation

1.5. Repository Management with AI

1.5.1. Automation of Version Control Processes with AI Techniques
1.5.2. Conflict Detection and Automatic Resolution in Collaborative Environments
1.5.3. Predictive Analysis of Changes and Trends in Code Repositories
1.5.4. Improved Organization and Categorization of Repositories using AI

1.6. Integration of AI in Database Management

1.6.1. Query and Performance Optimization Using AI Techniques
1.6.2. Predictive Analysis of Database Access Patterns
1.6.3. Implementation of Recommender Systems to Optimize Database Structure
1.6.4. Monitoring and Proactive Detection of Potential Problems in Databases

1.7. Fault Finding and Creation of Unit Tests with AI

1.7.1. Automatic Generation of Test Cases Using AI Techniques
1.7.2. Early Detection of Vulnerabilities and Bugs using Static Analysis with AI
1.7.3. Improving Test Coverage by Identifying Critical Areas with AI

1.8. Pair Programming with GitHub Copilot

1.8.1. Integration and Effective Use of GitHub Copilot in Pair Programming Sessions
1.8.2. Integration Improvements in Communication and Collaboration between Developers with GitHub Copilot
1.8.3. Integration Strategies for Making the Most of Code Hints Generated by GitHub Copilot
1.8.4. Integration Case Studies and Best Practices in AI-assisted Pair Programming

1.9. Automatic Translation between Programming Languages

1.9.1. Programming Language Specific Machine Translation Tools and Services
1.9.2. Adapting Machine Translation Algorithms to Development Contexts
1.9.3. Improving Interoperability between Different Languages by Machine Translation
1.9.4. Assessing and Mitigating Potential Challenges and Limitations of Machine Translation

1.10. Recommended AI Tools to Improve Productivity

1.10.1. Comparative Analysis of AI Tools for Software Development
1.10.2. Integration of AI Tools in Workflows
1.10.3. Automation of Routine Tasks with AI Tools
1.10.4. Evaluating and Selecting Tools Based on Context and Project Requirements

Enjoy the most up-to-date educational content available in innovative multimedia formats to optimize your studies"