AI Screening Questionnaire for SCNS

Participant Registration

Full Name *

Email Address *

Mobile Number *

Designation *

Company

Before You Begin

Please read the instructions carefully

Questions

~10

Minutes

Topic

Free

No Score

Important Notes

This is a screening questionnaire, not a test — there are no right or wrong answers.
Answer honestly to help us tailor the AI programme to your skill level.
Questions marked * are required. Some allow multiple selections.
Click Submit Questionnaire at the end to save your responses.

Your responses are confidential and will only be used to personalise the AI training programme.

AI Screening Questionnaire

Answer all questions, then submit at the bottom

How would you rate your Python programming skills? *

A)0 – No experience

B)1 – Basic syntax (variables, loops)

C)2 – Functions and basic data structures

D)3 – Libraries (NumPy, Pandas)

E)4 – Data processing & scripting projects

F)5 – Advanced (ML pipelines, APIs, optimization)

Which of the following have you done in Python? (Select all that apply)

Select all that apply

A)Written scripts using loops and conditions

B)Used Pandas for data analysis

C)Visualized data using Matplotlib/Seaborn

D)Built or trained a machine learning model

E)Worked with APIs or deployed code

F)None of the above

How familiar are you with data cleaning and preprocessing techniques? *

A)Not familiar

B)Basic (removing duplicates, handling missing values)

C)Intermediate (feature encoding, scaling)

D)Advanced (pipelines, feature engineering, transformations)

Which best describes your experience with Exploratory Data Analysis (EDA)? *

A)No experience

B)Basic statistics (mean, median, charts)

C)Identifying patterns/trends using visualization

D)Performing correlation analysis and feature insights

E)Full EDA workflow (insights + reporting)

Which statement best describes your understanding of machine learning? *

A)No prior knowledge

B)Basic concepts (supervised vs unsupervised)

C)Familiar with algorithms (regression, classification)

D)Trained models using libraries (Scikit-learn, etc.)

E)Designed and evaluated ML pipelines

Which best describes your understanding of the bias–variance tradeoff? *

A)Never heard of it

B)Heard of it but unclear

C)Basic understanding

D)Can explain with examples

E)Can apply it in model tuning

Which metrics are you familiar with? (Select all that apply)

Select all that apply

A)Accuracy

B)Precision / Recall

C)F1 Score

D)ROC-AUC

E)Confusion Matrix

F)None of the above

In a classification problem, when would you prioritize recall over precision? *

A)I don't know

B)Rarely

C)When false negatives are costly

D)When false positives are costly

E)Always prioritize recall

Which areas have you worked with or studied? (Select all that apply)

Select all that apply

A)Natural Language Processing (text classification, sentiment analysis)

B)Computer Vision (image classification, object detection)

C)Time Series / Forecasting

D)Deep Learning (TensorFlow, PyTorch)

E)None of the above

What is your primary goal for joining this AI program? *

A)General awareness of AI

B)Career transition into AI/Data Science

C)Enhance current technical role

D)Research / academic purposes

E)Build real-world AI applications