Sahu Testing Expert

AI, Machine Learning, and GenAI – What’s the Difference?

Before diving into exploratory data analysis (EDA), it’s important to understand the broader AI landscape and where Machine Learning (ML) and Generative AI (GenAI) fit into financial risk modeling. Here is a brief run-down:

What is Artificial Intelligence (AI)?

AI refers to any system that can perform tasks requiring human intelligence, such as recognizing patterns, making decisions, or processing language. It is a broad category that includes both traditional rule-based systems and Machine Learning (ML) models that improve based on data.


What is Machine Learning (ML)?

Machine learning is a subset of AI that learns from historical data to predict future outcomes. In financial services, ML models are used for credit scoring, fraud detection, and risk assessment.

Example: A logistic regression model trained on customer repayment history to predict the likelihood of delinquency.

What is Generative AI (GenAI)?

GenAI is a specialized form of AI that can create new content, such as text, images, or structured code, based on training data. Unlike ML, which is designed for structured predictions, GenAI assists with automation, summarization, and data exploration—making it a valuable tool in EDA.

Example: Using GenAI to generate a summary of credit risk trends instead of manually coding an exploratory analysis.

You won’t be building an ML model from scratch, but you will:

📊 Explore patterns in financial data that inform risk assessment.
⚙️ Use GenAI tools to summarize insights and guide predictive modeling.
🌍 Understand how AI-driven predictions influence real-world decisions

State the difference between mobile device testing and mobile application testing

Mobile Device Testing:

Mobile device testing is typically conducted to ensure the quality of the mobile device itself. The process involves testing hardware and software. These tests are generally being conducted to verify the mobile device itself and to test features such as Call, SMS, Memory, Camera, Media Player, inbuilt browsers, etc.

Mobile Application Testing:

Applications must undergo this whole testing process to survive in today's market. Performance, security, and user interface, and other aspects of the application are also scrutinized (tested) in order to ensure the best possible quality for end-users. This type of testing includes functional, performance, usability, security, load, and other types. Then, you can find out if the targeted application is of high quality, if it is compatible with the device, if it has the right hardware, software, and network connections, etc.

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Test cases for Netflix, the popular streaming service, can be comprehensive and cover various aspects of the application to ensure its functionality, usability, and performance.

Below, I'll provide a set of test cases that cover different areas of Netflix:

User Authentication:
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Verify that users can successfully create a new account.

Verify that users can log in with valid credentials.

Verify that users receive appropriate error messages for invalid login attempts.

Verify that users can reset their passwords.

Browsing Content:
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Verify that users can browse the library by different genres (e.g., action, comedy, drama).

Verify that users can search for specific movies or TV shows.

Verify that the content is categorized correctly.

Playing Content:
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Verify that users can start playback of a movie or TV show.

Verify that playback controls (play, pause, forward, rewind) work as expected.

Verify that video quality adjusts based on the user's internet connection.

Verify that users can switch between different audio and subtitle options.

Verify that content resumes from where the user left off (if applicable).

User Profile:
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Verify that users can create and edit their profiles.

Verify that users can set parental controls.

Verify that user preferences (e.g., language, autoplay settings) are saved and applied.

Account Management:
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Verify that users can update their account information (email, password, payment method).

Verify that users can cancel their subscription.

Verify that users receive appropriate notifications (e.g., payment confirmation, subscription renewal).

Cross-Device Compatibility:
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Verify that the application works seamlessly on various devices (smartphones, tablets, smart TVs, web browsers).

Verify that users can start watching on one device and continue on another.

Performance and Load Testing:
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Simulate high user traffic to ensure the system handles load efficiently without crashing or slowing down significantly.

Test the application's performance on devices with varying processing power and network conditions.

Security Testing:
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Verify that sensitive user information (such as payment details) is securely transmitted and stored.

Test for potential vulnerabilities (SQL injection, XSS) to ensure user data is protected.

Accessibility Testing:
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Verify that the application is usable for users with disabilities (screen readers, keyboard navigation, color contrast).

Localization Testing:
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Verify that the application works well in different languages and regions.

Test the accuracy of subtitles and dubbing for non-English content.