WBCHSE Applied AI study guide
WBCHSE Applied AI · Work through your exam, one topic at a time.
Applied Artificial Intelligence is a vocational subject at the Higher Secondary level under the West Bengal Council of Higher Secondary Education. It is written for Class XI and XII students who want a school-level credential that pairs AI literacy with practical computing skill, rather than a purely theoretical science-stream course. The WBCHSE Applied AI study guide has 10 sections and about 3,824 words.
01Introduction to Artificial Intelligence
Domain 1 - Introduction to Artificial Intelligence. This domain tests whether you can define AI precisely, separate it from machine learning and deep learning, and classify real systems by capability and by technique rather than by marketing language.
427 words, about 2 min02AI Ethics and Societal Impact
Domain 2 - AI Ethics and Societal Impact. The exam tests whether you can name specific ethical principles, apply them to a concrete system, and distinguish legal compliance from ethical acceptability.
385 words, about 2 min03Computational Thinking and Python Programming Fundamentals
Domain 3 - Computational Thinking and Python Programming Fundamentals. This domain tests decomposition and abstraction as much as syntax: can you read a short program, trace its state line by line, and predict the exact output?
365 words, about 2 min04Data Handling
Domain 4 - Data Handling. This domain tests whether you can take a messy dataset and produce a clean, correctly split table suitable for a model, and justify every cleaning decision you make.
408 words, about 2 min05Data Literacy and Visualisation
Domain 5 - Data Literacy and Visualisation. This domain tests whether you can read a chart critically, choose the right chart for a variable type, and compute and interpret basic summary statistics.
408 words, about 2 min06Introduction to Machine Learning Concepts and Workflow
Domain 6 - Introduction to Machine Learning Concepts and Workflow. This domain tests the full pipeline from problem framing to evaluation, plus accurate use of supervised, unsupervised and reinforcement learning vocabulary.
362 words, about 2 min07Natural Language Processing and Computer Vision Applications
Domain 7 - Natural Language Processing and Computer Vision Applications. This domain tests whether you know the standard preprocessing pipeline in each field and can match a stated task to the correct model type.
361 words, about 2 min08AI Application Domains
Domain 8 - AI Application Domains. This domain tests whether you can map a real problem to an appropriate AI technique and justify the match, sector by sector, using data type and label availability as the deciding evidence.
365 words, about 2 min09Tools and Emerging Technologies
Domain 9 - Tools and Emerging Technologies. This domain tests whether you know what each tool in the AI stack actually does, and can assemble a sensible toolchain for a stated task.
364 words, about 2 min10Practical Skills, Project Work and Employability / Entrepreneurship
Domain 10 - Practical Skills, Project Work and Employability / Entrepreneurship. This domain tests laboratory discipline, honest project reporting, and realistic career and business framing rather than ambition statements.
379 words, about 2 min