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WorksheetsGroup 1. Chọn câu (35 câu) - CDR 1.1 - DE
Total questions: 100
Worksheet time: 55mins
Which of the following is a potential effect of AI on job markets?
Job displacement (Mất việc làm)
Increased manual labor (Gia tăng lao động thủ công)
Decreased productivity (Sự suy giảm năng suất)
Reduction in technology reliance (Giảm sự phụ thuộc vào công nghệ)
Which key component is essential for enabling voice recognition in smart speakers?
Natural Language Processing (NLP) (Xử lý ngôn ngữ tự nhiên)
Data Encryption (Mã hóa dữ liệu)
Graphical Processing Unit (GPU) (Đơn vị xử lý đồ họa)
Blockchain Technology (Công nghệ Blockchain)
Which principle of communication is most effective in ensuring clarity during a data project meeting?
Active listening (Lắng nghe chủ động)
Rapid speaking (Nói nhanh)
Using technical jargon (Sử dụng thuật ngữ kỹ thuật)
Monologue presentations (Thuyết trình độc thoại)
Which of the following strategies is most effective for initiating AI projects within a company?
Establishing an AI task force to oversee the initiative
Starting with a pilot project to demonstrate AI capabilities
Immediately integrating AI into all processes without testing
Relying solely on external AI consultants for all AI projects
What is machine learning?
A subset of AI that involves the use of algorithms to allow computers to learn from and make predictions based on data.
A programming language used for web development.
A type of computer hardware component.
A method for storing large amounts of data.
In an AI team, who is primarily responsible for translating business needs into technical requirements and ensuring that the AI solution aligns with business goals?
Product Manager (Quản lý sản phẩm)
Data Scientist (Nhà khoa học dữ liệu)
Software Engineer (Kỹ sư phần mềm)
UX Designer (Nhà thiết kế UX)
What role in an AI team is responsible for maintaining the integrity of datasets and ensuring data quality?
Data Engineer (Kỹ sư dữ liệu)
Data Scientist (Nhà khoa học dữ liệu)
Data Analist (Nhà phân tích dữ liệu)
Product Manager (Quản lý sản phẩm)
Which of the following is a key step in applying the AI Transformation Playbook to guide a company in becoming proficient in AI?
Identifying and prioritizing AI opportunities within the company
Focusing solely on increasing the company's social media presence
Developing a new line of consumer products
Reducing the number of employees to cut costs
One significant opportunity that AI presents for developing economies is:
Enhancing access to education and healthcare
Increasing pollution levels
Reducing technological innovation
Limiting job creation
Which of the following scenarios is considered a failure of machine learning due to overfitting?
A model performs well on training data but poorly on new, unseen data.
A model has low bias and high variance.
A model uses a simple linear regression for a non-linear problem.
A model predicts the test data with the same accuracy as the training data.
What is the term for the error due to the bias that occurs when a model is too simple, such as assuming linearity when the data is more complex?
underfitting (Chưa khớp)
overfitting (Quá khớp)
High variance (Độ lệch cao)
Gradient vanishing (Sự tiêu biến của Gradient)
In the PACE workflow, what is the primary focus during the Planning stage?
Defining the project scope and objectives
Collecting and analyzing data
Deploying the final model
Evaluating the performance of the model
In the PACE workflow, what is the term for the stage focused on gathering information and insights from data?
Analysis (Phân tích)
Crawling (Cào dữ liệu)
Processing (Xử lý)
In one word, what is essential for ensuring that all team members are aligned and understand their roles in a project?
Clarity (Sự rõ ràng)
Chaos (Hỗn loạn)
Silence (Sự im lặng)
Confusion (Sự nhầm lẫn)
What is one key way that effective communication drives the PACE workflow?
Establishes clear project goals
Creates more work for team members
Reduces the need for meetings
Eliminates task redundancy
What is the term used to describe the principle of doing no harm when working with data?
nonmaleficence (Nguyên tắc không gây tổn hại đến cá nhân, cộng đồng)
negligence (sự cẩu thả)
exploitation (sự khai thác)
bias (sự thiên vị)
Which technical skill is most commonly associated with data analysis in various careers?
Data visualization (Trực quan hóa dữ liệu)
Project management (Quản lý dự án)
Public speaking (Nói trước công chúng)
Time management (Quản lý thời gian)
What one-word term describes the strategic ability to influence stakeholder decisions in the data career space?
Persuasion (Thuyết phục)
Coding (Lập trình)
Storage (Lưu trữ)
Analysis (Phân tích)
In supervised learning, what term is used to describe the data that is used to train the model?
Training (Huấn luyện)
Testing (kiểm thử)
Tuning (điều chỉnh)
Preparing (chuẩn bị)
Which of the following resources is most essential to prepare for a job interview?
Researching the company
Practicing sports
Watching movies
Reading novels
What is the primary objective of adversarial attacks on AI systems?
Adversarial attacks manipulate input data to deceive AI models.
Adversarial attacks are designed to enhance AI model accuracy.
Adversarial attacks involve directly altering the AI model's code.
Adversarial attacks always require human intervention to succeed.
When presenting key findings to an audience, which of the following is the most important element to include?
Clear and concise summary of the findings (Tóm tắt rõ ràng và ngắn gọn các phát hiện)
Detailed statistical data without context (Dữ liệu thống kê chi tiết mà không có ngữ cảnh)
Which key element is crucial for effective communication about AI transformation within a company?
Clear understanding of AI concepts
Ignoring stakeholder concerns
Focusing only on technical details
Avoiding collaboration with external partners
What is the purpose of the PACE workflow in a data science project?
To provide a structured approach to problem-solving using data analysis.
To ensure data privacy and security in all data science projects.
To automate all steps of the data science process.
To develop new programming languages for data analysis.
What letter does the PACE workflow begin with?
P
A
C
E
Which type of neural network is most commonly used for image recognition tasks?
Convolutional Neural Networks (Mạng nơ-ron tích chập)
Recurrent Neural Networks (Mạng nơ-ron hồi tiếp)
K-Nearest Neighbors (K-điểm gần nhất)
Decision Trees (Cây quyết định)
28. Data is often compared to oil in the context of AI systems because:
it is a valuable resource that powers AI systems, much like oil powers engines.
it is a liquid substance used in computers.
it is a pollutant that needs to be cleaned up.
it is only useful for transportation industries.
Data is the new oil (Dữ liệu là dầu mỏ mới) Which of the following statements is true?
Data is always reliable (Dữ liệu luôn đáng tin cậy)
Data is insignificant in AI (Dữ liệu không quan trọng trong AI)
Data management is straightforward (Quản lý dữ liệu là đơn giản)
Data is the new oil (Dữ liệu là dầu mỏ mới)
What is a significant ethical consideration when developing AI systems for real-world applications?
Ensuring transparency in AI decision-making processes.
Maximizing AI's profit-making abilities.
Focusing solely on technical performance of AI.
Prioritizing AI's speed over accuracy.
Which of the following is a realistic application of natural language processing (NLP)?
Generating automated language translations for books
Performing complex mathematical operations quickly
Designing computer hardware components
Creating virtual reality environments
What is the one-word term for AI technologies that simulate human conversation?
chatbots
databases
sensors
Image recognition
Which of the following is a key responsibility of a data professional?
Designing and maintaining databases
Performing heart surgeries
Developing marketing strategies
Teaching language courses
Which of the following is a key ethical consideration when implementing AI systems?
Ensuring transparency in AI decision-making processes
Maximizing AI's profit-making abilities
Focusing solely on technical performance of AI
Prioritizing AI's speed over accuracy
What is Artificial General Intelligence (AGI)?
A type of AI focused on performing specific tasks.
A form of AI that has the ability to understand and learn any intellectual task that a human can.
An AI system that operates without human intervention.
A computer program designed to simulate human conversation.
What is a primary responsibility for data stewardship in the context of data analytics professionals?
Identify data privacy regulations that apply to analytics.
Minimize ethical concerns to enhance data collection.
Prioritize data monetization over ethical considerations.
Ignore user consent if the data is anonymized.
Select the main drivers of business value that can be enhanced through AI automation.
Improved accuracy in data analysis
Increased time for market research
Reduction of customer interaction through chatbots
What is the primary goal businesses aim to achieve by automating tasks?
Partner (Đối tác)
Productivity (Năng suất)
Mobility (Lưu động)
Customer (Khách hàng)
Which solutions are proposed to counteract job displacement due to AI?
Do not need to do anything
Lifelong learning programs
Increased taxation on AI companies
Do not need to care about AI
Select the processes involved in developing AI products like smart speakers.
Data Collection (Thu thập dữ liệu)
Software development (Phát triển phần mềm)
UI Design (Thiết kế giao diện người dùng)
Requirement analysis (Phân tích yêu cầu)
In one word, what is a major limitation of AI related to its decision-making capabilities?
Bias (Thiên lệch)
Data (Dữ liệu)
Model (Mô hình)
Software (Phần mềm)
What is the term for the systematic approach AI companies use to improve their processes and outcomes?
Optimization (Tối ưu hóa)
Evaluation (Đánh giá)
Minimization (Tối thiểu hóa)
Maximization (Tối đa hóa)
What is the term for AI-generated videos that make people appear to say or do things they never did?
Deepfake
Fake News
Misinformation
Synthetic Media
Select all potential adverse impacts of deepfakes on society.
Increase public trust in media
Facilitating criminal activities by impersonating individuals
Creating virtual meeting backgrounds
Improving speech recognition systems
Which of the following are common applications of deep learning?
Image Recognition (Nhận dạng hình ảnh)
Software Development (Phát triển phần mềm)
Sorting Algorithms (Thuật toán phân loại)
Weather Forecasting (Dự báo thời tiết)
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?
Pooling (Pooling)
Sampling (Lấy mẫu)
Activation (Kích hoạt)
Convolution (Tích chập)
What is the term for the process of cleaning and organizing raw data for analysis?
Preprocessing (Tiền xử lý)
Crawling (Cào dữ liệu)
Visualization (Trực quan hóa)
Modeling (Mô hình hóa)
What is the term for the ability of AI systems to make decisions without human intervention?
Autonomy (Tự chủ)
Governance (Quản lý)
Dependence (Phụ thuộc)
What is the term for extracting meaningful insights from large sets of raw data?
Analysis (Phân tích)
Remove (Xoá)
Storage (Lưu trữ)
Encryption (Mã hóa)
What is the term for the ethical principle that AI should not cause harm to humans?
Nonmaleficence (không gây hại)
Productivity (Năng suất)
Efficiency (hiệu quả)
Profitability (lợi nhuận)
What is the term for the practice of ensuring data is accurate, consistent, and reliable for its intended use?
Data Lake (Kho dữ liệu)
Data Integrity (Toàn vẹn dữ liệu)
Data Volume (Khối lượng dữ liệu)
Data Security (Bảo mật dữ liệu)
Select the practice that reflect data stewardship priorities in analytics.
Implementing encryption techniques to protect data.
Regularly deleting data access logs.
Sorting Algorithms
Assuming data from trusted sources needs no validation.
In the context of AI and machine learning projects, what is the term for adjusting model parameters to improve performance?
Tuning (Điều chỉnh)
Evaluation (Đánh giá)
Initialization (Khởi tạo)
Validation (Xác thực)
What is the key AI component used in self-driving cars to perceive the environment and objects?
Mirror (Lidar)
radar (Radar)
Sonar (sóng siêu âm)
GPS (định vị GPS)
In the context of data project communication, what is the term for a visual representation of data?
Chart (biểu đồ)
Graph (đồ thị)
Table (bảng)
Report (báo cáo)
What is the term for a small-scale project used to test and demonstrate the potential of AI within a company?
Pilot (dự án thử nghiệm)
Prototype (nguyên mẫu)
Demo (bản thử nghiệm)
Mockup (mô hình giả lập)
Select all strategies that are effective for developing AI projects within a company.
Forming AI learning groups to share knowledge
Starting with complex projects to challenge the team
Encouraging cross-departmental collaboration on AI initiatives
Investing heavily in AI technology before having a clear application plan
What is the term used for a computer system modeled on the human brain, consisting of layers of interconnected nodes?
Neural network
Artificial neural network
What is the term used to describe a small-scale AI project used to test the viability and impact of AI solutions before full-scale deployment?
Pilot (dự án thử nghiệm)
Prototype (nguyên mẫu)
Simulation (mô phỏng)
Draft (bản nháp)
What single word describes the type of leadership crucial for integrating AI in developing economies?
Visionary
Innovative
Collaborative
Authoritative
What are significant impacts of AI on various industries?
Automation of repetitive tasks
Enhance Productivity
Creation of biased algorithms
Increased dependence on manual labor
Which of the following is a key step in the workflow of AI, machine learning, and data science projects?
Data Visualization (Trực quan hóa dữ liệu)
Model Training (Huấn luyện mô hình)
Data Backup (Sao lưu dữ liệu)
Resource Allocation (Phân bổ tài nguyên)
When evaluating an AI project, which factor is essential to consider when deciding between building the solution in-house or buying an existing solution?
Cost and resource availability
Project deadline flexibility
Team size
Office location
What is the term for assessing the potential impacts of AI on ethical and societal norms?
Ethics (Đạo đức)
Effective (Hiệu quả)
Efficiency (Hiệu quả)
Performance (Hiệu suất)
What is the primary industry that employs data professionals for data analysis and management?
Technology (công nghệ)
F&B (Đồ ăn & nước uống)
Agriculture (nông nghiệp)
Entertainment (giải trí)
Which of the following types of organizations most commonly employ data professionals?
Technology companies (Các công ty công nghệ)
Grocery stores (Cửa hàng tạp hóa)
Cafes (Quán cà phê)
Construction firms (Công ty xây dựng)
Name a machine learning library that starts with 's'.
Scikit-learn (Scikit-learn)
Pytorch (Pytorch)
Pandas (pandas)
Tensorflow (tensorflow)
Which of the following is a popular open-source library used for deep learning projects?
(a)
What is a common pitfall in AI projects that can severely impact the timeline and budget?
Inadequate data quality
Overestimating algorithm complexity
Using open-source tools
Hiring a diverse team
What term is used to describe the challenge of having too much data to process effectively in AI projects?
Overload (Quá tải)
Data insufficient (Không đủ)
Underfitting (Chưa khớp)
Encryption (Mã hóa)
What is the acronym for the field of study focused on giving computers the ability to understand text and spoken words in a manner similar to humans?
NLP (Xử lý ngôn ngữ tự nhiên)
ML (Học máy)
AI (Trí tuệ nhân tạo)
CNN (Mạng nơ-ron tích chập)
Which AI technique is primarily used in computer vision for image recognition tasks?
Convolutional Neural Networks (Mạng nơ-ron tích chập)
Recurrent Neural Networks (Mạng nơ-ron hồi tiếp)
Decision Trees (Cây quyết định)
K-Means Clustering (Phân cụm K-Means)
How do data science and machine learning impact various job functions? (Khoa học dữ liệu và học máy ảnh hưởng đến các chức năng công việc như thế nào?)
What one-word term describes the process of using algorithms to parse data, learn from it, and make a determination or prediction?
Modeling
Cleaning
Storing
Visualizing
What is a common source of bias in AI systems?
Training data that lacks diversity
Using too many data points
Implementing complex algorithms
High computational power
What is the term used to describe the unfair treatment of individuals based on their association with certain groups within AI systems?
Discrimination
accuracy
efficiency
transparency
What is the primary goal during the planning stage of a data science project?
Define the scope and objectives of the project
Develop the final deliverables
Implement the data collection process
Conduct the final review and assessment
What is the term commonly used to describe the extraction of hidden insights from large volumes of data?
Data analysis
Data mining
Data visualization
Data warehousing
What is one of the primary roles of a Data Analyst within an organization?
Data Analysts interpret trends and patterns in data to support business decisions.
Data Analysts primarily handle the installation of hardware and software systems.
Data Analysts are responsible for maintaining server infrastructure.
Data Analysts design marketing strategies for enterprises.
What is the primary objective of adversarial attacks on AI systems?
Adversarial attacks manipulate input data to deceive AI models.
Adversarial attacks are designed to enhance AI model accuracy.
Adversarial attacks involve directly altering the AI model's code.
Adversarial attacks always require human intervention to succeed.
What is the primary challenge when working with unstructured data in AI projects?
Lack of labeled data
High cost of storage
Difficulty in data analysis
Complexity in data preprocessing
What is the primary goal of using deep learning techniques in AI?
To improve accuracy by using large neural networks
To reduce computational cost
To simplify data preprocessing
To increase interpretability of models
Which of the following tasks are typically performed during the model evaluation stage in an AI project?
Testing the model on validation data (Kiểm tra mô hình trên dữ liệu xác thực)
Selecting the appropriate model for deployment (Chọn mô hình phù hợp để triển khai)
Adjusting hyperparameters (Điều chỉnh siêu tham số)
Collecting additional training data (Thu thập dữ liệu huấn luyện bổ sung)
Which of the following describes a neural network’s ability to improve its performance as more data is provided during training?
Supervised learning (Học có giám sát)
Reinforcement learning (Học tăng cường)
Deep learning (Học sâu)
Unsupervised learning (Học không giám sát)
What is the key difference between supervised and unsupervised learning in machine learning?
unlabeled
labeled
binary
continuous
Which of the following is a key benefit of using ensemble methods in machine learning?
Which of the following methods is commonly used for dimensionality reduction in machine learning?
Principal component analysis (Phân tích thành phần chính)
Singular value decomposition (Phân rã giá trị đặc biệt)
K-means clustering (Phân cụm K-means)
Support vector machines (Máy vector hỗ trợ)
Which of the following are key applications of reinforcement learning?
Game playing (Chơi game)
Robotics (Robot học)
Image classification (Phân loại hình ảnh)
Natural language processing (Xử lý ngôn ngữ tự nhiên)
Which of these is the best definition of “Generative AI”?
AI that can produce high quality content, such as text, images, and audio.
Any web-based application that generates text.
A form of web search.
Artificial intelligence systems that can map from an input A to an output B.
Which of these is the most accurate description of an LLM?
It generates text by repeatedly predicting the next word.
It generates text by repeatedly predicting words in random order.
It generates text by finding a writing partner to work with you.
It generates text by using supervised learning to carry out web search.
AI is called a general purpose technology because:
it can be applied across various industries and domains
it is only used in robotics
it is limited to scientific research
it is specific to entertainment applications
What is a token in the context of a large language model (LLM)?
Word or part of a word in either the input prompt or LLM output.
A physical device or digital code to authenticate a user's identity.
The part of the LLM output that has primarily symbolic rather than substantive value (as in, “the court issued a token fine”, or “the LLM generated a token output”).
A unit of cryptocurrency (like bitcoin or other “crypto tokens”) that you can use to pay for LLM services.
A friend writes the following prompt to a web-based LLM: “Write a description of our new dog food product.” Which of these are reasonable suggestions for how to improve this prompt?
Give the LLM more context about what’s interesting or unique about the product to help it craft a better description.
Give it guidance on the purpose of the description (is it to go in an internal company memo, a website, a press release?) to help it use the right tone.
Specify the desired length of the description.
All other answers.
93. Monitoring the performance of a customer service chatbot after deployment is important because:
It helps identify issues and improve the system.
It guarantees the chatbot will never make mistakes.
It eliminates the need for human customer service agents.
It ensures the chatbot can answer every possible question.
You want to build an application to answer questions based on information found in your emails. Which of the following is the most appropriate technique?
RAG, where the LLM is provided additional context based on retrieving emails relevant to your question.
Fine-tuning an LLM on your emails, whereby we take a pre-trained LLM and further train it on your emails.
Prompting (without RAG), where we iteratively refine the prompt until the LLM gets the answers right.
Pretraining an LLM on your emails.
You’re preparing a presentation about technology, and ask an LLM to help you find an inspirational quote. It comes up with this: "And that’s what a computer is to me. What a computer is to me is it’s the most remarkable tool that we’ve ever come up with, and it’s the equivalent of a bicycle for our minds." -Steve Jobs. What should you do next?
Use the quote in your presentation, as it is inspirational and relevant.
Ignore the quote because it is not related to technology.
Replace the quote with a generic statement about computers.
Remove the quote because it is not from a famous person.
In the context of building a restaurant review sentiment classifier, which of the following statements about prompt-based development is correct?
Prompt-based development is generally much faster than supervised learning.
Prompt-based development requires that you collect hundreds or thousands of labeled examples.
Prompt-based development requires that you collect hundreds or thousands of unlabeled examples (meaning reviews without a label B to say if it is positive or negative sentiment).
If you want to classify reviews as positive, neutral, or negative (3 possible outputs) there is no way to write a prompt to do so: An LLM can generate only 2 outputs.
You are working on using an LLM to summarize research reports. Suppose an average report contains roughly 6,000 words. Approximately how many tokens would it take an LLM to process 6,000 input words?
8,000 tokens (about 6000 * 1.333)
4,500 tokens (6000 * 3/4)
6,000 tokens (6.000 token)
14,000 tokens (about 6000 * 1.333 + the original 6000 words)
The idea of using an LLM as a reasoning engine refers to:
Employing a large language model to perform logical inference and problem-solving tasks.
Using a language model solely for generating text without reasoning.
Applying a language model for image recognition tasks.
Utilizing a language model for data storage purposes.
By making trusted sources of information available to an LLM via RAG, we can reduce the risk of hallucination?
True, because RAG allows the LLM to reason through accurate information retrieved from a trusted source to arrive at the correct answer.
True, because the LLM is now restricted to outputting paragraphs of text exactly as written in the provided document, which we trust.
An ecommerce company is building a software application to route emails to the right department. It wants to do so with a small, 1 billion parameter model, and needs high accuracy. Which of these is an appropriate technique?
Fine-tune a 1 billion parameter model on around 1,000 examples of emails and the appropriate department.
Pretrain a 1 billion parameter model on around 1 billion examples of emails and the appropriate department.
Pretrain a 1 billion parameter model on around 1,000 examples of emails and the appropriate department.
Fine-tune a 1 billion parameter model on around 1 billion examples of emails and the appropriate department.
