Viva prep · Real questions · Student experiences Enroll in Bootcamp
165 proctors 5262 questions

Lazy IITians Project Mentorship

Prepare in structure for the Project Mentorship.

View Bootcamp Detail
L1_118 MLP Level 1 Aug 5, 2026
  1. 1
    What feature engineering techniques did you use?
  2. 2
    Which correlation method did you use?
  3. 3
    Why did you use StandardScaler (or your chosen scaler)?
  4. 4
    Difference between RandomSearchCV and GridSearchCV.
  5. 5
    How many combinations does RandomizedSearchCV try based on n_iter and cv?
  6. 6
    Why did you choose RandomizedSearchCV?
  7. 7
    What is the baseline model?
  8. 8
    If a node has 7 samples, will it split? Explain using min_samples_split and min_samples_leaf.
  9. 9
    If two features have 0 correlation, can they still be collinear?
  10. 10
    Explain Bagging vs Boosting.
  11. 11
    What is a Weak Learner?
  12. 12
    What preprocessing steps did you perform?
  13. 13
    Why didn't you use Accuracy as the evaluation metric?
  14. 14
    Formula of F1 Score.
  15. 15
    Does F1 Score give equal weight to Precision and Recall?
  16. 16
    Why did you use F1 Macro instead of other averaging methods?
  17. 17
    Which of your models are parametric and which are non-parametric?
  18. 18
    Why is Logistic Regression called "Regression" although it performs classification?
  19. 19
    Why did you use MLPClassifier?
  20. 20
    Explain your pipeline structure.
  21. 21
    Explain your hyperparameter tuning approach.
  22. 22
    Explain your model parameters.
  23. 23
    Why did you choose the models you used?
  24. 24
    How did you compare your models?
  25. 25
    What conclusions did you draw from model comparison?
  26. 26
    Explain your EDA graphs and the insights obtained.
  27. 27
    Explain the confidence interval/shaded region in a regression plot.
  28. 28
    Why is the correlation between OperationalHoursMeter and TargetValue nearly zero?
  29. 29
    What does errors="coerce" do while converting datetime?
  30. 30
    Did you use Pipelines or ColumnTransformer? Why?
  31. 31
    Did you use any user-defined functions?
  32. 32
    What is the output type after preprocessing (type(X_train))?
  33. 33
    What does fit_transform() return?
  34. 34
    How can you convert transformer output to a Pandas DataFrame (set_output(transform="pandas"))?
  35. 35
    What are the parameters of LightGBM?
  36. 36
    Explain Ridge and Lasso Regression.
  37. 37
    Which algorithms can perform feature selection?
  38. 38
    What does a Pair Plot show?
  39. 39
    Difference between Histogram and Bar Plot.
  40. 40
    What does Early Stopping mean?
  41. 41
    If the best score occurs at iteration 100, when does training stop with early stopping?
  42. 42
    What does TF-IDF do?
  43. 43
    How did you select the ensemble weights?
  44. 44
    Explain your train-test split and what changes if the split ratio changes.
  45. 45
    Load the Iris dataset and: Display the feature matrix. Separate features and target. Print feature matrix shape. Print target variable. Print feature names. Print data without the target column.
  46. 46
    Load the Breast Cancer dataset and: Print target names. Count missing values.
  47. 47
    Load the California Housing dataset and fit HistGradientBoostingRegressor.
  48. 48
    Load the Wine dataset and print feature names.
  49. 49
    Load the Diabetes dataset and print the feature matrix.
  50. 50
    Load any toy dataset from scikit-learn and display its contents.
  51. 51
    Import a dummy dataset.
  52. 52
    Create a bar chart manually using model names and scores.
  53. 53
    Plot a graph comparing training scores of models.
  54. 54
    Plot the target value graph (including after log transformation if asked).
  55. 55
    Write simple Lasso Regression code.
  56. 56
    Explain your complete notebook.
  57. 57
    Explain EDA.
  58. 58
    Explain preprocessing.
  59. 59
    Explain feature engineering.
  60. 60
    Explain model selection.
  61. 61
    Explain hyperparameter tuning.
  62. 62
    Explain pipeline/ColumnTransformer.
  63. 63
    Explain model comparison.
  64. 64
    Explain graphs and visualizations.
  65. 65
    Explain assumptions and interpretations.
  66. 66
    Explain notebook improvements and limitations.
Level2_79 DBMS Level 1 Aug 3, 2026
  1. 1
    Show your ID card.
  2. 2
    Download and run the project.
  3. 3
    Show your GitHub repository and collaborator.
  4. 4
    Demonstrate the complete application.
  5. 5
    Explain the complete authentication flow end-to-end.
  6. 6
    Demonstrate all Celery tasks (scheduled and user-triggered).
  7. 7
    Show where caching is implemented in the project.
  8. 8
    What are Vue Lifecycle Hooks?
  9. 9
    What is an asynchronous function?
  10. 10
    Explain v-bind.
  11. 11
    Difference between v-if and v-show.
  12. 12
    Create a button in the frontend that calls a backend API and displays the returned message.
  13. 13
    Modify the API/frontend so that the displayed message changes.
Proctor801 MAD2 Level 1 Aug 3, 2026
  1. 1
    Download the project and start all servers.
  2. 2
    Give a complete demonstration of the application (no interruptions during the demo).
  3. 3
    Open any online JavaScript editor.
  4. 4
    Given a JSON array of users, write JavaScript code to filter users whose score is greater than a specified value (e.g., score > 15). The JSON data will be provided by the examiner. Run and debug the code if needed.
  5. 5
    Be comfortable with core JavaScript, especially: Arrays Objects filter() map() Arrow functions Basic debugging
  6. 6
    The examiner is patient and allows time to think, code, and debug.
  7. 7
    Confidence while solving the problem matters.
  8. 8
    Most of the emphasis is on JavaScript coding rather than theoretical questions.
level1_107 MAD2 Level 1 Aug 3, 2026
  1. 1
    Write and explain a Login API route.
  2. 2
    Create a Vue component from scratch.
  3. 3
    Write and explain a Celery task (live coding).
  4. 4
    What is backref? How is it different from back_populates?
  5. 5
    Explain the Vue Lifecycle Hooks.
  6. 6
    Prepare all basic Vue, Flask, SQLAlchemy, and Celery concepts, as the examiner may ask follow-up theory questions based on your code.
level1_5 MAD2 Level 1 Aug 3, 2026
  1. 1
    Give an overview/demonstration of the complete application.
  2. 2
    Difference between v-if and v-show.
  3. 3
    What is caching? How have you implemented it in your project?
  4. 4
    What is crontab?
  5. 5
    Difference between v-bind and v-model.
  6. 6
    What are Vue directives?
  7. 7
    Move the navigation bar to the bottom of the page.
  8. 8
    Modify the admin dashboard so that only cancelled appointments are displayed.
  9. 9
    Write a query/code to fetch only approved students.
Level2_137 MAD2 Level 1 Aug 3, 2026
  1. 1
    Show your ID Card.
  2. 2
    Show your GitHub repository.
  3. 3
    Demonstrate the complete application.
  4. 4
    What is a Promise in JavaScript?
  5. 5
    Difference between Session-based Authentication and JWT Authentication.
  6. 6
    Why did you use Session-based Authentication?
  7. 7
    Difference between Local Storage and Session Storage.
  8. 8
    How do you clear Local Storage?
  9. 9
    Explain Vue Lifecycle Hooks.
  10. 10
    Write a JavaScript function that prints your name.
  11. 11
    Write a backend route that returns the names of all users.
  12. 12
    Show me around your room.
Appdev_level1_viva5 MAD2 Level 1 Aug 3, 2026
  1. 1
    Show Student ID.
  2. 2
    Show GitHub repository and collaborator.
  3. 3
    Download the project from the portal.
  4. 4
    Run the frontend, backend, Celery worker, Redis, and Celery Beat.
  5. 5
    Demonstrate the complete application without skipping any features.
  6. 6
    Show Celery tasks (daily reminders/monthly reports).
  7. 7
    Trigger a scheduled Celery task by changing the schedule to the current time.
  8. 8
    Demonstrate only the implemented backend jobs (if export/email features are missing, explain accordingly).
  9. 9
    What is caching (Redis caching)?
  10. 10
    Why do we use caching?
  11. 11
    What is Celery?
  12. 12
    What is Celery Beat?
  13. 13
    What are asynchronous (async) tasks?
  14. 14
    What are Vue directives?
  15. 15
    Difference between v-if and v-show.
  16. 16
    What is v-model?
  17. 17
    Difference between v-model and v-bind.
  18. 18
    What is binding in Vue?
  19. 19
    What are Props?
  20. 20
    Show only booked appointments on the admin dashboard.
  21. 21
    Show only cancelled bookings.
  22. 22
    Show only confirmed/paid bookings.
  23. 23
    Show only unassigned treks/doctors using filtering.
  24. 24
    Limit the doctor list to display only 2 doctors.
  25. 25
    Move the Navbar to the bottom of the page.
  26. 26
    Move the Footer to the top/Navbar position (swap Navbar and Footer).
  27. 27
    Move the Search Bar to the right side of the page.
  28. 28
    Add a CSS hover effect to an element.
appdev_level1_viva10 MAD2 Level 1 Aug 3, 2026
  1. 1
    Explain the complete project and all functionalities.
  2. 2
    Demonstrate all core features and workflows mentioned in the project milestones.
  3. 3
    Difference between PUT, PATCH, and POST.
  4. 4
    Show how you display a list of students using a loop (e.g., Jinja for loop over a list of student objects).
  5. 5
    Write a Jinja template snippet in Notepad (examiner may randomly ask for syntax such as passing arguments, rendering variables, template expressions, etc.).
Most Asked Topics

No tags yet.

View all →
Top Proctors
Created for educational purposes only. Questions are based on students' personal experiences and may not reflect actual exam content.