Bert Labs Interview Questions, Process, and Tips

Severity refers to the impact of a defect, while priority indicates the urgency of fixing it.

• Severity is categorized based on the impact on the system (e.g., critical, major, minor).

• Priority is determined by the urgency to fix the defect (e.g., high, medium, low).

• Example of severity: A system crash is high severity, while a typo is low severity.

• Example of priority: A critical bug affecting many users may be high priori

Regression testing ensures that new code changes do not adversely affect existing functionalities.

• Verifies that previously developed and tested software still performs after changes.

• Can be automated or manual; automation is preferred for efficiency.

• Example: After fixing a bug in a login feature, regression testing checks if the login still works and if other features are unaffected.

• Often performed after updates, bug fi

Throughout my education, I faced challenges like balancing studies with personal responsibilities and adapting to different learning environments.

• Time Management: Juggling coursework with part-time jobs made it difficult to maintain focus on studies.

• Adaptability: Transitioning from high school to college required adjusting to a more independent learning style.

• Resource Availability: Limited access to study materials and...read more

Data science offers a new challenge and opportunity to apply analytical skills from my engineering background.

• Data science allows me to utilize my analytical skills in a new and challenging field.

• I can apply my knowledge of statistics and programming to extract insights from data.

• Data science offers opportunities to work on diverse projects and industries.

• My background in electrical engineering provides a strong founda...read more

Convolutional neural networks (CNNs) are deep learning models specifically designed for processing structured grid data, such as images.

• CNNs use convolutional layers to extract features from input data

• They are commonly used in image recognition tasks, such as object detection and facial recognition

• CNNs are composed of multiple layers, including convolutional, pooling, and fully connected layers

• They are trained using ba