Certificate in Artificial Intelligence (AI) Basics + Data Analytics + Python Programming

Online Examination Detail:
Duration- 60 minutes.
Number of Questions- 30. (Multiple Choice Questions).
Maximum Marks- 100, Passing Marks- 40%.
There is no negative marking.

Candidate Details

NameEmailPhone Number

1 / 30

1. What is exception handling in Python used for?

A. Managing errors and preventing program crashes during runtime

B. Ignoring all user input

C. Increasing program execution speed

D. Converting data types automatically

2 / 30

2. Which data type in Python is used to store multiple items in an ordered, changeable collection?

A. List

B. Tuple

C. Dictionary

D. Set

3 / 30

3. Natural Language Processing (NLP) is an AI technology used for:

A. Understanding, interpreting, and generating human language

B. Processing images and videos

C. Controlling robotic arms

D. Managing database storage

4 / 30

4. AI applications in everyday life include:

A. Virtual assistants, recommendation systems, autonomous vehicles, and smart devices

B. Only academic research

C. Ignoring user data

D. Replacing all human decision-making

5 / 30

5. Decision trees are used for:

A. Classification and regression tasks in machine learning

B. Only clustering datasets

C. Visualizing neural networks exclusively

D. Data cleaning

6 / 30

6. Ethical considerations in AI primarily include:

A. Privacy, fairness, transparency, accountability, and bias prevention

B. Only improving speed and efficiency

C. Ignoring data security

D. Reducing AI adoption

7 / 30

7. A capstone AI project typically involves:

A. Conducting an end-to-end AI project including data collection, analysis, modeling, and reporting

B. Only reading AI textbooks

C. Avoiding coding practice

D. Ignoring project evaluation and presentation

8 / 30

8. In Python, NumPy is mainly used for:

A. Performing efficient numerical computations and handling arrays

B. Managing databases

C. Designing GUIs

D. Web scraping

9 / 30

9. One key difference between AI and human intelligence is:

A. AI can process large datasets quickly, but lacks general reasoning and emotions

B. AI has emotions and consciousness like humans

C. Humans can process data faster than AI

D. AI can only work offline

10 / 30

10. Exploratory Data Analysis (EDA) using Python helps to:

A. Summarize key features of data, detect patterns, and identify anomalies

B. Replace statistical modeling completely

C. Avoid visualization and descriptive statistics

D. Focus only on coding syntax

11 / 30

11. Narrow AI refers to:

A. AI systems designed to perform a specific task or set of tasks

B. AI that can perform any intellectual task a human can

C. AI with consciousness and self-awareness

D. AI that cannot be used in practical applications

12 / 30

12. Scikit-learn in Python is used for:

A. Building and evaluating machine learning models efficiently

B. Web development

C. Creating dashboards only

D. Handling images exclusively

13 / 30

13. Developing a portfolio in AI and Data Analytics helps to:

A. Showcase skills, projects, and experience to potential employers or clients

B. Avoid learning new tools

C. Focus solely on theoretical studies

D. Limit professional growth opportunities

14 / 30

14. Overfitting occurs when:

A. A model learns the training data too well, including noise, and performs poorly on new data

B. A model ignores training data

C. A model generalizes perfectly

D. Data is missing in the dataset

15 / 30

15. Python combined with data analytics is useful for AI tasks because it:

A. Provides libraries for data manipulation, visualization, and machine learning integration

B. Only writes web applications

C. Cannot handle large datasets

D. Replaces human decision-making entirely

16 / 30

16. Exploratory Data Analysis (EDA) is used to:

A. Summarize main characteristics of data and detect patterns or anomalies

B. Only create reports without insights

C. Replace statistical modeling

D. Ignore missing data

17 / 30

17. Matplotlib and Seaborn are used in Python for:

A. Data visualization, such as plotting graphs and charts

B. File handling operations

C. Text-based data input

D. Exception handling

18 / 30

18. Data-driven decision making helps organizations to:

A. Make informed choices based on insights derived from data

B. Rely only on intuition and guesswork

C. Ignore historical trends

D. Limit business growth

19 / 30

19. Tools like Tableau, Power BI, and Excel are primarily used for:

A. Data visualization, analysis, and reporting

B. Data collection only

C. Writing code exclusively

D. Managing emails

20 / 30

20. Which of the following is a correct way to define a variable in Python?

A. age = 25

B. int age = 25;

C. var age := 25

D. age == 25

21 / 30

21. Structured data refers to:

A. Data organized in rows and columns, easily stored in databases

B. Data in videos, images, or audio files

C. Random text data without format

D. Only real-time streaming data

22 / 30

22. Which control structure is used in Python to execute code repeatedly while a condition is true?

A. Loop (e.g., while or for)

B. If-else statement

C. Function definition

D. Exception handling

23 / 30

23. The Pandas library in Python is primarily used for:

A. Data manipulation and analysis using DataFrames and Series

B. Creating 3D graphics

C. Writing web applications

D. Network programming

24 / 30

24. Ethical considerations in AI and data analytics primarily include:

A. Privacy, fairness, transparency, accountability, and bias mitigation

B. Ignoring user consent

C. Only maximizing model accuracy

D. Avoiding regulatory compliance

25 / 30

25. What is the purpose of a Python function?

A. To group code into reusable blocks for modular programming

B. To create variables only

C. To handle file input/output exclusively

D. To delete data from memory

26 / 30

26. Implementing AI solutions in real-life scenarios requires:

A. Applying machine learning models to solve practical business or societal problems

B. Only theoretical knowledge without practical data

C. Ignoring data preprocessing

D. Avoiding evaluation of model performance

27 / 30

27. Handling missing values in a dataset is important because:

A. It ensures accuracy and reliability of analysis results

B. It slows down data processing intentionally

C. It removes all data from the dataset

D. It is unnecessary for large datasets

28 / 30

28. Data cleaning and preprocessing is important because it:

A. Ensures accuracy, consistency, and reliability of data for analysis

B. Slows down the analytics process unnecessarily

C. Removes all valuable information

D. Replaces visualization

29 / 30

29. Supervised learning in Machine Learning involves:

A. Training a model on labeled data to predict outcomes

B. Using data without labels to find patterns

C. Only using reinforcement from games

D. Ignoring input features

30 / 30

30. Clustering is a technique used in:

A. Unsupervised learning to group similar data points together

B. Supervised learning with labeled outputs

C. Reinforcement learning only

D. Data visualization exclusively

Exit

Certificate in Artificial Intelligence (AI) Basics + Data Analytics + Python Programming

Certificate in Artificial Intelligence (AI) Basics + Data Analytics + Python Programming

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