Punjab PSEB SS Computer Application study plan

Define and correctly classify computer hardware, software, and firmware components, writing a one-line justification for each item

Convert between binary, decimal, octal, and hexadecimal by hand and verify each conversion with a second method

Explain the fetch-decode-execute cycle in your own words and label each stage on a hand-drawn diagram

Differentiate primary and secondary memory types and state one realistic use case for each

Distinguish system software from application software and place 15 named examples into the correct category

Describe the functions of an operating system and match each function to a concrete user-visible behaviour

Trace how a source program becomes executable, naming the role of compiler, interpreter, assembler, and linker

Identify common file extensions and map each to the software category that handles it

Explain networking fundamentals including LAN, WAN, topology, IP addressing, and the role of protocols

Describe the layered idea behind the internet and state what each common protocol (HTTP, FTP, SMTP, DNS) is used for

Define artificial intelligence and separate it from rule-based automation with two concrete contrasting examples

List the main subfields of AI (machine learning, NLP, computer vision, robotics) and give one everyday application of each

Distinguish supervised, unsupervised, and reinforcement learning and assign 9 given scenarios to the right type

Explain training data, features, labels, and model evaluation in plain language without jargon shortcuts

Describe how a simple classifier is trained and tested, including why data is split into training and test sets

Identify ethical risks of AI such as bias, privacy loss, and job displacement with one mitigation for each

Explain how neural networks learn, covering neurons, weights, activation functions, and backpropagation at a conceptual level

Differentiate classical machine learning from deep learning and justify when each is preferable

Describe natural language processing tasks including tokenisation, sentiment analysis, and chatbots

Outline how computer vision works from pixels to features to classification

Compare generative AI, large language models, and traditional predictive models on inputs, outputs, and typical use cases

Explain prompting concepts: instruction clarity, context, examples, and iterative refinement

Identify limitations of AI systems including hallucination, data dependency, and lack of common sense

Describe AI applications in Indian contexts such as agriculture advisory, healthcare screening, and language translation

Map the vocational group syllabus topics to the core CS concepts already studied and flag any gaps

Practise vocational skill areas such as office productivity tools, data entry accuracy, and basic troubleshooting procedures

Explain workplace safety, digital hygiene, and responsible use of IT resources in a vocational setting

Describe the steps of a basic IT support workflow from problem report to resolution and documentation

Complete two full-length timed mock tests under exam conditions and record section-wise scores

Review every wrong answer and write the underlying rule or fact that was missed

Re-drill the two weakest areas identified by mock scores until accuracy exceeds 80%

Recite key definitions from all four domains from memory in a rapid self-quiz