Data Analytics Program Quiz 7

Data Analytics Quiz 7

Legal First Name

Legal Last Name

1. Which of the following best describes the relationship between AI and data analytics?

AI replaces data analytics entirely

AI and data analytics are unrelated fields

AI enhances data analytics by automating pattern recognition and decision-making

Data analytics is only useful for structured data, while AI is for unstructured data

2. Which factor contributes to bias in AI models?

Using only real-time data sources for model training

Increasing the model's complexity without adjusting the dataset

Ensuring diverse and balanced training datasets

Collecting data from a limited or skewed sample population

3. What is a key strategy for managing risks in AI implementations?

Using only unsupervised learning models

Ignoring ethical considerations in model deployment

Avoiding AI adoption to minimize errors

Implementing explainable AI (XAI) to improve transparency and accountability

4. Which of the following is a fundamental concept in deep learning?

Statistical hypothesis testing

Neural networks with multiple layers

Decision trees

Relational databases

5. Which of the following is a common application of AI in data analytics?

Using predictive models to forecast customer behavior

Automating the creation of data visualizations

Avoiding the use of cloud computing

Storing data in traditional spreadsheets

6. How does edge computing enhance AI-driven data analytics?

By only working with structured datasets

By eliminating the need for cloud storage

By reducing latency and enabling real-time processing at the data source

By making AI models smaller and less powerful

7. Which AI technique is most commonly used in IoT-based predictive analytics?

Logistic regression

Machine learning models that process sensor data in real time

Recurrent Neural Networks (RNNs)

Convolutional Neural Networks (CNNs)

8. Which risk is associated with AI-powered decision-making in data analytics?

Data analytics becomes obsolete with AI

AI models always make perfect predictions

Overfitting due to excessive model complexity

AI eliminates the need for data preprocessing

9. What is a key challenge when applying AI to real-world data analytics problems?

The quality and quantity of data greatly affect model performance

AI models do not require any form of training

AI does not require ongoing monitoring after deployment

AI is only effective on small datasets

10. Which deep learning architecture is best suited for analyzing sequential data, such as time-series data?

Convolutional Neural Networks (CNNs)

Recurrent Neural Networks (RNNs)

Decision trees

K-means clustering

Breaking News:

Send a message.

careers

Feedbacks

Data Analytics Program Quiz 7

Our Mentorship Programs

QUICK LINKS

NEED HELP?

CALL US DIRECTLY

MAIL US DIRECTLY

🎉 Join our community.