Cisco Black Belt AI Fundamental

 Q1. What is the primary role of programming languages in AI development?

1. They enable the creation and management of databases that store and organize the data used by AI models.

2. They help write the instructions that tell computers how to learn and process information.

3. They help monitor AI systems by providing the syntax and structures necessary for developing software that tracks performance metrics and system health.

4. They facilitate the networking of various AI systems by providing the code that enables communication and data exchange between disparate systems.

Ans : 2.

Q2. What is the primary advantage of using generative models like GANs and VAEs?

1. They streamline data processing.

2. They reduce the need for data labeling. 

3. They generate new, realistic data instances.

4. They simplify the deployment of AI models.

Ans : 3.

Q3. Why is robust infrastructure important for AI development?

1. It helps ensure that AI applications can be developed without programming languages. 

2. It provides unlimited scalability for AI systems across all types of cloud environments. 

3. It makes AI systems less dependent on machine-learning frameworks.

4. It supports the high computational demands and large data volumes typical in AI workloads.

Ans : 4

Q4. What is a key benefit of effective monitoring in AI systems?

1. It helps ensure that systems operate smoothly and efficiently.

2. It eliminates the need for manual data labeling.

3. It replaces the need for machine-learning frameworks.

4. It reduces the importance of programming languages in AI.

Ans : 1

Q5. attach the following components of the AI tech stack with their descriptions:

Machine-Learning Frameworks

Structures that simplify the development, training, and deployment of ML models.

Vector Databases

Specialized storage solutions that support high-dimensional data used in AI applications.

Monitoring

Process for tracking performance metrics to gain optimal operation of AI systems.

Data Processing and Labeling

Operations that prepare data to enhance the performance of AI models.