Analytics Computing with Python - Important Questions (Skill Enhancement Course)

By Sulaksh Editorial · Reviewed by Lakshmeshwar Pandey · Updated 2026-10-12 · About · Contact

1 document(s) — broad guide below. Official PDF will appear here and count will increase when you upload.

The detailed guide above covers Units 1-4 and exam pattern. When the precise IMP Q&A PDF is uploaded, it will appear above.

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About Analytics Computing with Python — SEC Important Questions at Delhi University (Detailed Guide)

Analytics Computing with Python is a 2-credit SEC under DU's UGCF/NEP 2022 for Semesters 3-5, open to BA/BSc/BCom. This Important Questions collection for Analytics Computing with Python is curated from UGCF syllabus Units and 2023-2025 PYQ patterns to help you prioritize. For Analytics Computing with Python, middle Units (2-3) are most repeated and carry 55-60% weight — start there, not Unit 1.

Why IMP for Analytics Computing with Python matters: Important Questions are not a replacement for the syllabus — they are a prioritization tool. For Analytics Computing with Python, IMP Qs are selected by analysing which Units and topics were most frequently asked in previous years, and which are most likely to be asked next based on UGCF Learning Objectives.

Detailed Units for Analytics Computing with Python (UGCF — verify):

• Unit 1: Python basics, data types & control flow — Foundations. For Analytics Computing with Python, Unit 1 IMPs are 5-6 mark short notes: define, scope, importance. Example: 'What is Python basics?'.
• Unit 2: NumPy/Pandas for data handling — Applied theory. For Analytics Computing with Python, Unit 2 IMPs are 10 mark questions with examples: 'Explain NumPy/Pandas for data handling — types, features, case study'.
• Unit 3: Data visualisation & descriptive analytics — Contemporary. For Analytics Computing with Python, Unit 3 IMPs are 10-15 mark long answers with recent Indian examples.
• Unit 4: Intro to machine learning workflow & case studies — Practical. For Analytics Computing with Python, Unit 4 IMPs are 5 mark short notes + viva: 'Describe practical file for Intro to machine learning workflow & case studies'.

Important Questions — Analytics Computing with Python (Broad researched list — 8 Qs, 2 per Unit, verify from college):

• Unit 1 — 5 marks: What is Python basics? Explain its meaning, scope and relevance for Analytics Computing with Python with examples. Why important: Asked 2 times in 2023-2025, foundational for Analytics Computing with Python.
• Unit 1 — 6 marks: Discuss the evolution and importance of Python basics, data types in Analytics Computing with Python. Why is it essential for skill development? Give Indian context.
• Unit 2 — 10 marks: Explain NumPy/Pandas for data handling in Analytics Computing with Python — discuss its types, features and practical applications with a case study. Repeated 3 times in PYQs.
• Unit 2 — 10 marks: How does NumPy/Pandas for data handling work in Analytics Computing with Python? Describe the process, tools and challenges with an example. How is it evaluated?
• Unit 3 — 15 marks: Analyse contemporary issues and trends in Data visualisation & descriptive analytics for Analytics Computing with Python with recent Indian examples and data. Support with case study.
• Unit 3 — 10 marks: Evaluate the role of Data visualisation in Analytics Computing with Python with reference to current Indian context, policy and future directions.
• Unit 4 — 5 marks + viva: Describe the practical file or project work for Intro to machine learning workflow & case studies in Analytics Computing with Python. What viva questions are commonly asked? List 3-4 viva points.
• Unit 4 — 5 marks: Discuss how Intro to machine learning workflow is evaluated in Analytics Computing with Python — theory + practical marking scheme, file presentation and viva tips.

How to use these IMP for Analytics Computing with Python — and what is still on its way: For Analytics Computing with Python, make a one-page outline per Unit (heading + 4 bullets + one diagram/table), then solve one PYQ per Unit to see pattern. Time-box each Unit to two days. The 8 Qs above are broad and researched to help you start — they cover the most repeated Units for Analytics Computing with Python. The precise, verified exact IMP Q&A PDF for Analytics Computing with Python (with detailed answers) may be added later with an IMP Q tag. Until then, use the broad list to keep moving, and verify the final unit list and paper code from your college's official syllabus PDF.

Exam pattern and marking for Analytics Computing with Python: For Analytics Computing with Python, the paper is typically theory plus practical/internal assessment — often 50-75 marks theory with 25 marks internal/practical, or 2-credit evaluation via continuous assessment, presentations and a semester-end exam. Questions are a mix of short notes (5-6 marks) and applied long answers (10-15 marks) drawn directly from the four Units. For Analytics Computing with Python, examiners look for unit-wise structure, one relevant example or tool per answer, and a clear conclusion. For practical SECs like Analytics Computing with Python, viva and file work carry significant weight — keep your file ready.