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AI (Artificial Intelligence)#1
The simulation of human intelligence processes by machines, especially computer systems. Examples include speech recognition and decision-making.
API (Application Programming Interface)#2
A set of rules and tools that allows different software applications to communicate with each other, enabling integration of functionalities.
Data Handling#3
The process of collecting, storing, and managing data effectively for analysis and application in projects.
Personal Assistant#4
An AI application designed to help users manage tasks, schedule events, and provide reminders, enhancing productivity.
User Interface (UI)#5
The space where interactions between humans and machines occur, focusing on the design and layout of an application.
Mock Data#6
Fictitious data created for testing purposes, simulating real data to validate application functionality.
Debugging#7
The process of identifying and fixing errors in software to ensure it operates correctly and efficiently.
Cloud Storage#8
A model of data storage where digital data is stored in logical pools, managed by a cloud storage service provider.
Data Privacy#9
The aspect of data management that deals with the proper handling of sensitive data, ensuring user confidentiality.
Integration Testing#10
A phase in software testing where individual components are combined and tested as a group to identify interface defects.
Unit Testing#11
A software testing method by which individual units of source code are tested to determine if they are fit for use.
User Acceptance Testing (UAT)#12
A type of testing conducted by end-users to validate the functionality and usability of the application before it goes live.
API Call#13
A request made to an API to retrieve or send data, enabling communication between applications.
Data Types#14
The classification of data based on the type of value it holds, such as integers, strings, or booleans.
Feature Testing#15
The process of verifying that specific functionalities of an application work as intended.
Ethical AI#16
The consideration of moral implications and responsibilities in the development and deployment of AI technologies.
Feedback Loop#17
A process where the output of a system is circled back and used as input, improving the system over time.
Data Structure#18
A method of organizing and storing data in a computer so it can be accessed and modified efficiently.
Version Control#19
A system that records changes to files or sets of files over time, allowing for easy tracking and collaboration.
API Documentation#20
A technical document that describes how to effectively use an API, including endpoints, request formats, and response structures.
Task Scheduling#21
The process of planning and organizing tasks to be completed at specific times or under certain conditions.
Application Logic#22
The part of the application that defines how data is created, stored, and changed, influencing user interactions.
Prototype#23
An early sample or model of a product used to test concepts and gather feedback before full-scale production.
Cross-Platform#24
Refers to applications that can run on multiple operating systems or devices without modification.
Performance Testing#25
A type of testing to determine how a system performs in terms of responsiveness and stability under a particular workload.