1.what is microservices?

Microservices is a software architecture ,we can builds applications as a collection of small, independent, loosely coupled services, each focused on a single business function, communicating via lightweight APIs (like REST). Instead of one large "monolith," it breaks down an application, allowing teams to develop, deploy, scale, and update each service independently, leading to faster innovation, better resilience, and quicker delivery of features.

2.what are the Key Characteristics of microservices

Independent & Autonomous: Each service runs in its own process, has its own codebase, and can be deployed without affecting others. Business-Focused: Services are organized around specific business capabilities (e.g., user management, order processing).
Decentralized: Each service manages its own data, and different services can use different technologies (languages, databases) (polyglot).
Lightweight Communication: Services talk to each other using simple APIs or message brokers.
Scalable & Resilient: You can scale specific services that need more resources, and a failure in one service doesn't bring down the entire application.

3.How AI works

Simulating human intelligence by algorithms and data to identify patterns, make predictions, and perform tasks

4.What are the components of AI

Following are the components of AI:

• Data
• Algorithms
• Training
• Prediction
• Iteration

5.What are the 4 types of AI?

4 main types of artificial intelligence:

• Reactive machines. Reactive machines are AI systems with no memory and are task-specific, meaning that an input always delivers the same output.
• Limited memory machines.
• Theory of mind.
• Self-awareness.

6.What are the types of AI Frameworks ?

• Development Frameworks:
The most common, offering building blocks for coding AI models (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers for NLP)


• Agentic Frameworks:
Specialized for building autonomous AI agents that plan, use tools (APIs, web search), and learn (e.g., LangChain, LlamaIndex).


• Governance Frameworks:
Guidelines and practices for ethical, secure, and compliant AI development (e.g., principles for fairness, accountability, transparency).


• Adoption Frameworks:
Roadmaps for organizations to systematically integrate AI into their operations and strategy.


• Legal/Regulatory Frameworks:
Laws and treaties, like the Council of Europe's Framework Convention on AI, to ensure AI aligns with human rights and laws.

7.what are the Jobs and Opportunities in artificial intelligence

• AI Expert
• AI Architect
• AI Agent creator
• AI Product Manager
• AI Marketing Specialist
• Machine learning engineer
• Data Scientist
• AI Research Scientist
• Computer Vision Engineer
• NLP Engineer ..
• AI automation Engineer ..