Statistical Data – Class 10 Artificial Intelligence NCERT Book Solutions
Session 4.1: No code AI tool for Statistical Data – Book Solutions
I. Multiple Choice Questions:
Que 1. Orange data mining is an example of
a) Custom coding
b) Low code
c) No code
d) None of these.
Answer: c) No code
Que 2. Select Which is not the feature of No code approach.
a) visual
b) Highly expensive
c) code free
d) drag and drop
Answer: b) Highly expensive
Que 3. _______ assembly relies on developers to write and deploy code.
a) High code
b) Low code
c) No code
d) None of these
Answer: a) High code
Que 4. Flexibility is often limited in _________.
a) High code
b) High code and Low code
c) No code
d) High code and No code.
Answer: c) No code
Que 5. The organisation is heavily dependent on developer resources. This statement is true for
a) High code approach
b) Low code approach
c) No code approach
d) All of the above.
Answer: a) High code approach
Answer the following questions briefly:
Que 1. Name any two cloud based No-code AI tools?
Answer: : Azure Machine Learning and Google Cloud AutoML
Que 2. How accessible are no-code AI tools for non-technical users?
Answer: No-Code AI tools are highly accessible to non-technical users as they do not require any programming knowledge and offer user-friendly visual interfaces with drag-and-drop features.
Que 3. What types of tasks can be accomplished with no-code AI tools?
Answer: Tasks such as data visualization, building machine learning models, making predictions, automating workflows, and training models with images or sounds can be accomplished using No-Code AI tools.
Que 4. Can no-code AI tools be used for advanced projects? Justify.
Answer: Yes, No-Code AI tools can be used for advanced projects such as personalized recommendations, genetic data analysis, and predictive analytics because they offer powerful features and pre-trained models that can handle complex data.
Que 5. Do no-code AI tools require prior programming knowledge? Justify.
Answer: No, No-Code AI tools do not require prior programming knowledge because they are designed for users with no coding background. They use drag-and-drop components and intuitive interfaces to make AI development easy for everyone.
Answer the following questions in detail:
Que 1. What are the benefits of using No-code AI tools?
Answer: The key benefits of using No-Code AI tools include:
- Accessibility: They allow individuals without coding skills to build AI applications and solutions.
- Speed: These tools help create models much faster than traditional coding methods.
- Cost-Effective: Companies save money by not hiring highly paid developers.
- Ease of Use: Their drag-and-drop interface makes the learning curve minimal.
- Encourages Innovation: Even business users or students can build custom solutions for real-world problems.
Que 2. What are the challenges faced in using the No-code AI tools?
Answer: The challenges include:
- Lack of Flexibility: Limited customization due to fixed components.
- Automation Bias: Users may over-trust automated decisions even when they’re wrong.
- Security Concerns: These tools may not offer robust security features, especially for applications handling sensitive data.
- Limited Scope: They may not be suitable for highly complex or enterprise-level AI applications.
Que 3. Differentiate low code and No-code AI tools with examples.
Answer:
| Low-Code AI Tools | No-Code AI Tools |
| Some coding knowledge needed. | No coding required |
| Moderate customization possible. | Limited customization |
| Easier than traditional coding. | Easiest to use with drag-and-drop features |
| Semi-technical users | Non-technical users |
| Example: Power Apps, AppGyver | Example: Teachable Machine, Lobe AI, Orange |
Que 4. As the CEO of a small e-commerce startup, you’re eager to leverage artificial intelligence to enhance your platform’s user experience and drive sales. However, your team lacks the technical expertise to develop and deploy AI-powered solutions. What would be your recommendations for the CEO?
Answer: As the CEO, I would recommend:
- Using No-Code AI tools like Google Cloud AutoML, Teachable Machine, or Lobe AI to develop recommendation engines or customer segmentation models.
- These tools can help improve user experience, targeted marketing, and personalized product suggestions without hiring AI developers.
- Encourage staff to learn the basics of No-Code AI tools through tutorials.
- Start with simple projects (like product recommendation based on customer behavior) and scale up as needed.
Que 5. Samarth attended a seminar on Artificial Intelligence and has now been asked to write a report on his learnings from the seminar. Being a non-technical person, he understood that the AI enabled machine uses data of different formats in many of the daily based applications but failed to sync it with the right terminologies and express the details. Help Samarth define Artificial Intelligence, list the three domains of AI and the data that is used in these domains.
Answer: Definition of AI: Artificial Intelligence (AI) is a technology that enables machines to perform tasks that typically require human intelligence. It uses data to make decisions, learn from patterns, and improve over time.
Three Main Domains of AI:
- Data Science – Uses structured and numerical data for analysis, prediction, and automation.
- Computer Vision – Uses image and video data to recognize objects, people, and scenes.
- Natural Language Processing (NLP) – Uses text and audio data to understand, interpret, and generate human language.
Session 4.2: Statistical Data: Use Case Walkthrough
I. Multiple Choice Questions:
Que 1. What type of tool is Orange?
a) Open-source
b) Closed-source
c) Paid software
d) Hardware
Answer: a) Open-source
Que 2. Which of the following tasks can be performed using Orange?
a) Classification
b) Regression
c) Clustering
d) All of the above
Answer: d) All of the above
Que 3. What type of data can be imported into Orange?
a) CSV
b) Excel
c) SQL databases
d) All of the above
Answer: d) All of the above
Que 4. What does the Data Table widget in Orange primarily facilitate?
a) Loading and viewing datasets
b) Performing clustering analysis
c) Running machine learning algorithms
d) Evaluating
Answer: a) Loading and viewing datasets
Que 5. Which component in Orange enables users to evaluate the performance of machine learning models?
a) Test & Score
b) Data Table
c) Data Projection
d) Data Exploration
Answer: a) Test & Score
Reflection Time (Answer the following questions):
Que 1. Define No-Code and Low-Code AI.
Answer: No-Code AI means creating AI projects without writing any programming code. We use drag-and-drop tools and ready-made features.
Low-Code AI means creating AI projects with very little coding. Some parts are drag-and-drop, but a small amount of code is used to add extra features.
Que 2. Identify the differences between Code and No-Code AI concerning Statistical Data.
Answer: Code vs No-Code AI
- In Code-based AI, we write programs to calculate statistics like mean, median, graphs, etc.
- In No-Code AI, the tool automatically calculates and shows statistical results using buttons and drag-and-drop blocks.
- Code requires programming knowledge, while No-Code tools can be used without coding skills.
Que 3. Relate AI project stages to the stages of No-Code AI projects.
Answer: The stages are almost the same:
- Problem Understanding → Import Data in No-Code Tool
- Data Collection → Upload Dataset
- Data Processing → Clean and arrange data using tool options
- Modeling → Use drag-and-drop blocks to build a model
- Evaluation → See accuracy and results shown by the tool
- Deployment → Share or export project output
So, No-Code AI follows the same steps, but everything is done without coding.
Que 4. Orange Data Mining is a machine learning tool for data analysis where we can perform operations through simple drag-and-drop steps.
Answer: Yes, this statement is true.
Orange Data Mining allows users to:
- drag-and-drop widgets
- connect blocks
- analyze data
- build ML models easily
It is a No-Code data science tool.
Que 5. Descriptive statistics – Mean, Median, Mode – help us to describe the data and its underlying characteristics.
Answer: Yes, this statement is true.
Mean, Median and Mode help us to:
- understand data values
- find central patterns
- summarize large data sets
They describe the nature of the data.
Que 6. Write the names of five No-Code tools for AI projects.
Answer: Five No-Code AI tools are:
- Orange Data Mining
- Teachable Machine
- Lobe AI
- Google AutoML
- Microsoft PowerApps AI Builder
By Anjeev Kr Singh – Computer Science Educator
Published on : January 6, 2026 | Updated on : January 6, 2026
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