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Data Career Skills Quiz 2

Total questions: 40

Worksheet time: 20mins

Name
Class
Date
1.

Which technical skill is most commonly associated with data analysis in various careers?

a)

Data visualization

b)

Project management

c)

Public speaking

d)

Time management

2.

What one-word term describes the strategic ability to influence stakeholder decisions in the data career space? Please answer in all lowercase.

(a)  

3.

Select all the strategic skills essential across various data-related careers.

a)

Leadership

b)

Critical thinking

c)

Data entry

d)

Negotiation

e)

Spreadsheet proficiency

4.

Select the benefits of AI in various industries.

a)

Enhances productivity

b)

Guarantees data privacy

c)

Improves decision-making accuracy

d)

Always ensures ethical outcomes

e)

Facilitates personalized experiences

5.

What is one significant impact of AI on various industries?

a)

Automation of repetitive tasks

b)

Elimination of all jobs

c)

Creation of biased algorithms

d)

Increased dependence on manual labor

6.

In one word, what is a major limitation of AI related to its decision-making capabilities? Please answer in all lowercase.

a)

bias

b)

ethics

7.

What is the term used to describe a subset of data used to evaluate the performance of a machine learning model? Please answer in all lowercase.

a)

testset

b)

test

8.

Select all the tasks that are typically crucial for AI teams when handling data.

a)

Data cleaning

b)

Feature engineering

c)

Understanding neural network internals

d)

Hyperparameter tuning

e)

Data labeling

9.

Which of the following is essential for effective collaboration with AI teams concerning their approach to data?

a)

Understanding AI data preprocessing techniques

b)

Knowing how to program AI algorithms

c)

Mastering AI hardware configuration

d)

Specializing in AI model deployment

10.

What is the primary role of supervised learning in machine learning?

a)

To classify and make predictions based on labeled data

b)

To discover hidden patterns in data without labels

c)

To improve the efficiency of data processing systems

d)

To generate new data from existing datasets

11.

In supervised learning, what term is used to describe the data that is used to train the model? Please answer in all lowercase.

(a)  

12.

Which of the following are common applications of supervised learning?

a)

Spam email detection

b)

Image recognition

c)

Discovering customer segments

d)

Speech recognition

e)

Predicting stock market trends without historical data

13.

What is the term used to describe the intended skills or knowledge a learner should acquire by the end of an educational program? Please answer in all lowercase.

a)

outcome

b)

outcomes

14.

Select all statements that correctly describe key concepts to be shared in the program to enhance learning outcomes.

a)

Aligns with the program's objectives

b)

Promotes critical thinking

c)

Excludes practical applications

d)

Is irrelevant to the learners' goals

e)

Encourages collaboration

15.

Which of the following is a key aspect to consider when describing the learning outcomes for the program?

a)

Clearly define learning outcomes

b)

Include unrelated topics

c)

Focus solely on theoretical knowledge

d)

Avoid setting any educational goals

16.

What is the term for a brief document summarizing your skills, experience, and education? Please answer in all lowercase.

a)

resume

b)

cv

17.

Which of the following are effective resources to prepare for a job search?

a)

Online job boards

b)

Networking events

c)

Social media platforms

d)

Video games

e)

Peer-reviewed journals

18.

Which of the following resources is most essential to prepare for a job interview?

a)

Researching the company

b)

Practicing sports

c)

Watching movies

d)

Reading novels

19.

What is a common characteristic of successful AI companies when it comes to data management?

a)

They prioritize collecting large volumes of high-quality data.

b)

They focus solely on internal data for model training.

c)

They invest minimally in data cleaning processes.

d)

They do not prioritize data privacy and security.

20.

What is the term for the systematic approach AI companies use to improve their processes and outcomes? Please answer in all lowercase.

a)

optimization

b)

optimisation

21.

Which of the following are key strategies in AI transformation for companies?

a)

Developing a clear AI strategy and roadmap

b)

Investing in AI training and skill development

c)

Relying only on existing IT infrastructure without upgrades

d)

Implementing strong data governance practices

e)

Avoiding external partnerships and collaborations

22.

What is the term for AI-generated videos that make people appear to say or do things they never did? Please answer in all lowercase.

a)

deepfakes

b)

deepfake

23.

Select all potential adverse impacts of deep fakes on society.

a)

Undermining public trust in media

b)

Facilitating criminal activities by impersonating individuals

c)

Creating virtual meeting backgrounds

d)

Improving speech recognition systems

24.

Which of the following is a potential adverse use of deep fakes?

a)

Manipulating videos to spread misinformation

b)

Enhancing video quality for better user experience

c)

Generating realistic avatars for video games

d)

Improving photo editing software

25.

What is the term for the method that modifies input data to exploit weaknesses in AI models? Please answer in all lowercase.

a)

perturbation

b)

perturbations

26.

Which of the following strategies can be used to defend against adversarial attacks on AI systems?

a)

Adversarial training

b)

Regularization techniques

c)

Data augmentation

d)

Ignoring adversarial threats

e)

Reducing model complexity

27.

What is the primary objective of adversarial attacks on AI systems?

a)

Adversarial attacks manipulate input data to deceive AI models.

b)

Adversarial attacks are designed to enhance AI model accuracy.

c)

Adversarial attacks involve directly altering the AI model's code.

28.

What is the term used to describe the audience's essential takeaway from a presentation? Please answer in all lowercase.

a)

message

b)

keypoint

29.

Which of the following should be considered when tailoring key findings for a specific audience?

a)

Cultural context of the audience

b)

Preferred communication style of the audience

c)

Age of the presenter

d)

Timing and length of the presentation

e)

Personal opinions of the presenter

30.

When presenting key findings to an audience, which of the following is the most important element to include?

a)

Clear and concise summary of the findings

b)

Detailed statistical data without context

c)

Background of every research participant

d)

Lengthy explanations of research methodology

31.

What is the term used to describe partnerships between government entities and private companies in AI initiatives? Please answer in all lowercase.

a)

collaboration

b)

partnerships

c)

alliances

32.

Which key element is crucial for effective communication about AI transformation within a company?

a)

Clear understanding of AI concepts

b)

Ignoring stakeholder concerns

c)

Focusing only on technical details

d)

Avoiding collaboration with external partners

33.

Select the key benefits of public-private partnerships in AI transformation.

a)

Access to diverse expertise

b)

Increased innovation

c)

Higher cost without returns

d)

Enhanced resource sharing

e)

Limited to government regulations

34.

Which of the following are components of the PACE workflow in a data science project?

a)

Plan

b)

Act

c)

Explore

d)

Communicate

e)

Execute

35.

What is the purpose of the PACE workflow in a data science project?

a)

To provide a structured approach to problem-solving using data analysis.

b)

To ensure data privacy and security in all data science projects.

c)

To automate all steps of the data science process.

d)

To develop new programming languages for data analysis.

36.

What letter does the PACE workflow begin with? Please answer in all lowercase.

(a)  

37.

Which of the following are common applications of deep learning?

a)

Image Recognition

b)

Demand Prediction

c)

Sorting Algorithms

d)

Weather Forecasting

38.

What is the term for a neural network layer that reduces the spatial size of the representation to decrease the computational load and the number of parameters? Please answer in all lowercase.

a)

pooling

b)

subsampling

39.

Which type of neural network is most commonly used for image recognition tasks?

a)

Convolutional Neural Networks

b)

Recurrent Neural Networks

c)

K-Nearest Neighbors

d)

Decision Trees

40.

Why is data often compared to oil in the context of AI systems?

a)

Data is the new oil

b)

Data is always reliable

c)

Data is insignificant in AI

d)

Data management is straightforward