BCA 212T Introduction to Data Science Notes cover all four units of this Semester 4 paper in an 80-page printed book: 50 solved two-mark questions, 25 ten-mark practice questions and 35 Python programs with output, for the BCA batch admitted 2024-25 onwards.
Written by Prateek Talwar, Founder, Unnati Educations · Reviewed by Ritik Rawat, B.Tech, Senior Full Stack Developer · Checked against BCA Scheme and Syllabus 2024-25 (01 Aug 2025) · Updated 13 October 2026 · Editorial policy
Scheme: BCA 2024-25 | Applies to: batch admitted 2024-25 onwards | Verified against: BCA Scheme and Syllabus, 01 Aug 2025
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BCA 212T Introduction to Data Science at a glance: GGSIPU BCA Sem 4 credits, units and exam pattern
One of four Semester 4 electives, BCA 212T is taken with the BCA 212P lab. It sits with the other GGSIPU BCA Semester 4 papers.
| Code and title | BCA 212T · Introduction to Data Science |
|---|---|
| Course and semester | BCA, Semester 4 |
| Category and credits | PCE (Programme Core Elective), 4 credits, L-T-C 4-0-4 |
| Marks | 100: 40 internal + 60 end-term |
| Applies to | Batch admitted 2024-25 onwards |
| End-term pattern | Q1: 10 compulsory two-mark questions; then 1 of 2 ten-mark questions per unit (20 + 40 = 60 marks) |
| Units | 4, 11 teaching hours each |
| Paired lab | BCA 212P Data Science Lab: 2 credits, 100 marks (40 + 60) |
Grading, results and re-appear rules for BCA 212T follow Ordinance 11 on examinations (ipu.ac.in).
BCA 212T Introduction to Data Science Notes unit-wise: 50 solved two-mark questions and 35 Python programs across 4 units
Notes for every other paper of the course sit under GGSIPU BCA notes.
BCA 212T Unit 1: Introduction to Data Science and Data Pre-processing
Unit 1 covers the evolution of data science, team roles, the seven project stages, data security, data collection and the five pre-processing tasks.
Pages 4 to 23 · 13 sections · 7 solved numericals · 12 two-mark, 7 ten-mark questions
| Method | Working | Result |
|---|---|---|
| Min-max to [0, 1] | (73,600 − 12,000) ÷ (98,000 − 12,000) | 0.716 |
| Z-score (mean 54,000, SD 16,000) | (73,600 − 54,000) ÷ 16,000 | 1.225 |
| Decimal scaling (range −986 to 917) | −986 ÷ 10³ | −0.986 |
Quick look: one income value normalised three ways (from page 17)
- Method
- Min-max to [0, 1]
- Working
- (73,600 − 12,000) ÷ (98,000 − 12,000)
- Result
- 0.716
- Method
- Z-score (mean 54,000, SD 16,000)
- Working
- (73,600 − 54,000) ÷ 16,000
- Result
- 1.225
- Method
- Decimal scaling (range −986 to 917)
- Working
- −986 ÷ 10³
- Result
- −0.986
BCA 212T Unit 2: Python for Data Science (NumPy, Pandas and Statistics)
Unit 2 moves from NumPy arrays to Pandas Series, DataFrames, groupby and pivot tables, then works nine marks through mean, variance, IQR, box plot, skewness and kurtosis, ending with linear regression.
Pages 24 to 46 · 16 sections · 25 Python programs with output · 13 two-mark, 8 ten-mark questions
Quick look: groupby() totals sales by region (from page 35)
sales = pd.DataFrame({
'Region': ['North', 'South', 'North', 'East', 'South', 'East'],
'Sales': [200, 150, 300, 250, 400, 100]})
print(sales.groupby('Region')['Sales'].sum())Output: East 350, North 500, South 550.
BCA 212T Unit 3: Bayesian Statistics and Inferential Statistics
Unit 3 covers probability, the Poisson, exponential and normal distributions and the Central Limit Theorem, then correlation, regression, sampling, the Z, t, chi-square and F distributions, and hypothesis testing.
Pages 47 to 64 · 10 sections · 12 solved numericals, 3 SciPy checks · 13 two-mark, 8 ten-mark questions
Quick look: a Z-test on packet weights (from page 60)
- Claim 500 g; sample of 36 has mean 495 g, σ = 12 g. H₀: μ = 500, H₁: μ ≠ 500.
- Standard error = 12 ÷ √36 = 2.
- Z = (495 − 500) ÷ 2 = −2.5.
- |Z| = 2.5 > 1.96 at 5%, so H₀ is rejected.
BCA 212T Unit 4: Case Studies on Patterns, Demand Forecasting and Clinical Data
Unit 4 runs three case studies: a Delhi retail chain's 24 months of sales, a power-bank demand forecast done five ways, and a 20-patient blood-pressure trial.
Pages 65 to 79 · 20 sections · 3 case studies, 7 Python programs · 12 two-mark, 2 ten-mark questions
| Method (months 4 to 12) | MAE | MAPE | RMSE |
|---|---|---|---|
| 3-month moving average | 13.33 | 8.15% | 14.21 |
| Exponential smoothing (α = 0.3) | 19.18 | 11.58% | 20.01 |
| Linear trend | 4.41 | 2.66% | 4.82 |
Quick look: which forecast fits the power-bank demand best (from page 74)
- Method (months 4 to 12)
- 3-month moving average
- MAE
- 13.33
- MAPE
- 8.15%
- RMSE
- 14.21
- Method (months 4 to 12)
- Exponential smoothing (α = 0.3)
- MAE
- 19.18
- MAPE
- 11.58%
- RMSE
- 20.01
- Method (months 4 to 12)
- Linear trend
- MAE
- 4.41
- MAPE
- 2.66%
- RMSE
- 4.82
BCA 212T exam corner: 50 two-mark solved questions and 25 ten-mark practice questions by unit
Two-mark answers are solved in full; ten-mark questions are for practice.
| Unit | 2 Marks (solved) | 10 Marks (practice) | Programs and numericals |
|---|---|---|---|
| Unit 1 | 12 | 7 | 7 numericals |
| Unit 2 | 13 | 8 | 25 programs |
| Unit 3 | 13 | 8 | 12 numericals, 3 programs |
| Unit 4 | 12 | 2 | 3 case studies, 7 programs |
BCA 212T exam corner per unit (labels as printed: 2 Marks, 10 Marks)
- Unit
- Unit 1
- 2 Marks (solved)
- 12
- 10 Marks (practice)
- 7
- Programs and numericals
- 7 numericals
- Unit
- Unit 2
- 2 Marks (solved)
- 13
- 10 Marks (practice)
- 8
- Programs and numericals
- 25 programs
- Unit
- Unit 3
- 2 Marks (solved)
- 13
- 10 Marks (practice)
- 8
- Programs and numericals
- 12 numericals, 3 programs
- Unit
- Unit 4
- 2 Marks (solved)
- 12
- 10 Marks (practice)
- 2
- Programs and numericals
- 3 case studies, 7 programs
- Unit 1 (2 Marks): What is the entity identification problem? Pointer: one entity, two names (cust_id, customer_no).
- Unit 2 (2 Marks): Differentiate
locandiloc. Pointer: label (stop included) vs position (stop excluded). - Unit 3 (2 Marks): When is a t-test used instead of a Z-test? Pointer: σ unknown, n below 30.
- Unit 4 (10 Marks): Calculate support, confidence and lift for Bread → Milk. Pointer: 0.625, 0.833, 1.11.
The BCA 212T notes solve 50 two-mark questions across 4 units, list 25 ten-mark practice questions, and include 35 Python programs with output.
These are exam-style questions, not year-tagged. More practice sits in the BCA 212T important questions.
Bayes' theorem and the medical-test problem: excerpt from page 49 of the BCA 212T notes
Excerpt from page 49
Conditional probability
Conditional probability is the chance that event A happens when we already know that event B has happened. It is written P(A | B) = P(A ∩ B) ÷ P(B), and it is defined only when P(B) is greater than zero.
Example: in a class, 60% of students study Maths and 24% study both Maths and Statistics. The probability that a Maths student also studies Statistics is 0.24 ÷ 0.60 = 0.40.
Bayes' theorem
Bayes' theorem, from Rev. Thomas Bayes in the 18th century, tells us how to update the probability of a hypothesis when new evidence arrives. It is the foundation of Bayesian statistics.
P(A | B) = P(B | A) × P(A) ÷ P(B). When events A1, A2, ..., An form a partition of the sample space, P(Ai | B) = P(B | Ai) P(Ai) ÷ Σ P(B | Aj) P(Aj).
| Term | Name | Meaning |
|---|---|---|
| P(A) | Prior probability | Belief before seeing the evidence |
| P(B | A) | Likelihood | How likely the evidence is if A is true |
| P(B) | Evidence (marginal) | Total probability of the evidence |
| P(A | B) | Posterior probability | Updated belief after seeing the evidence |
The four parts of Bayes' theorem (page 49)
- Term
- P(A)
- Name
- Prior probability
- Meaning
- Belief before seeing the evidence
- Term
- P(B | A)
- Name
- Likelihood
- Meaning
- How likely the evidence is if A is true
- Term
- P(B)
- Name
- Evidence (marginal)
- Meaning
- Total probability of the evidence
- Term
- P(A | B)
- Name
- Posterior probability
- Meaning
- Updated belief after seeing the evidence
Read it as a chain: the prior, multiplied by the likelihood of the new evidence, gives the posterior, which is the updated belief.
Solved example: the medical test
A disease affects 1% of people. A test detects it correctly in 99% of sick people, but it also gives a false positive for 5% of healthy people. A person tests positive. What is the probability that he actually has the disease?
Given: P(D) = 0.01, P(D′) = 0.99, P(+ | D) = 0.99 and P(+ | D′) = 0.05.
Total probability of a positive result: P(+) = P(+ | D) · P(D) + P(+ | D′) · P(D′) = 0.99 × 0.01 + 0.05 × 0.99 = 0.0099 + 0.0495 = 0.0594.
Posterior: P(D | +) = 0.0099 ÷ 0.0594 = 0.1667, which is about 16.7%. Even after a positive result, the chance of disease is only about one in six, because so few people had the disease in the first place.
Do the BCA 212T notes cover the full GGSIPU syllabus?
Yes. Every topic in Units I to IV of the official BCA 212T syllabus has a matching section in the notes.
| Official unit | Official topics | Where in the notes | Status |
|---|---|---|---|
| Unit I | Evolution, Roles, Stages, Applications, Data security; Collection Strategies, Cleaning, Integration, transformation, Reduction, Discretization | Parts A and B, pages 5 to 20 | Covered |
| Unit II | Why Python, libraries; NumPy ndarray, Data Types, Arithmetic, Slicing; Series, Data Frames, statistical functions, group by, Sorting, Deleting, Renaming, Pivoting | Parts A to C, pages 25 to 37 | Covered |
| Unit II | Bias, Variance, Mean, Median, standard Deviation, Range, IQR, Skewness, Kurtosis, Box plots, Pivot Table, Linear Regression | Part D, pages 37 to 42 | Covered |
| Unit III | Probability theory; Poisson, exponential and Normal Distribution; Central Limit Theorem; Correlation, Regression, Sampling, Sampling distributions (Z, t, Chi-Square, F), Hypothesis Testing | Parts A and B, pages 48 to 61 | Covered |
| Unit IV | Checking different patterns in data, Forecasting demand, investigating clinical data | Case studies 1 to 3, pages 67 to 78 | Covered |
BCA 212T official topics mapped to pages in the notes
- Official unit
- Unit I
- Official topics
- Evolution, Roles, Stages, Applications, Data security; Collection Strategies, Cleaning, Integration, transformation, Reduction, Discretization
- Where in the notes
- Parts A and B, pages 5 to 20
- Status
- Covered
- Official unit
- Unit II
- Official topics
- Why Python, libraries; NumPy ndarray, Data Types, Arithmetic, Slicing; Series, Data Frames, statistical functions, group by, Sorting, Deleting, Renaming, Pivoting
- Where in the notes
- Parts A to C, pages 25 to 37
- Status
- Covered
- Official unit
- Unit II
- Official topics
- Bias, Variance, Mean, Median, standard Deviation, Range, IQR, Skewness, Kurtosis, Box plots, Pivot Table, Linear Regression
- Where in the notes
- Part D, pages 37 to 42
- Status
- Covered
- Official unit
- Unit III
- Official topics
- Probability theory; Poisson, exponential and Normal Distribution; Central Limit Theorem; Correlation, Regression, Sampling, Sampling distributions (Z, t, Chi-Square, F), Hypothesis Testing
- Where in the notes
- Parts A and B, pages 48 to 61
- Status
- Covered
- Official unit
- Unit IV
- Official topics
- Checking different patterns in data, Forecasting demand, investigating clinical data
- Where in the notes
- Case studies 1 to 3, pages 67 to 78
- Status
- Covered
Official source: BCA Scheme and Syllabus, batch admitted 2024-25 onwards.
Every course in GGSIPU notes is mapped to its official PDF the way BCA 212T is here.
Who writes and checks the BCA 212T Data Science notes?
- Prateek Talwar, author: Founder, Unnati Educations; Associate Company Secretary (ACS), ICSI, membership no. 58704, since 15 May 2019; B.Com, University of Delhi (School of Open Learning), 2012. Author profile
- Ritik Rawat, subject reviewer: B.Tech; Senior Full Stack Developer, Unnati Educations. Reviewer profile
These GGSIPU BCA Sem 4 Introduction to Data Science notes follow the 2024-25 scheme; the 2026-27 edition has 29 figures and 42 numbered tables. Last updated 13 October 2026 under our editorial policy.
The same team prepares GGSIPU important questions for every course, BCA 212T included.
BCA 212T and the BCA 212P Data Science lab (20 practicals), plus other GGSIPU BCA Sem 4 papers
Paired lab: BCA 212P Data Science lab notes. Its official list has 20 practicals, of which 15 must be implemented.
Most lean on Unit 2: pages 31 to 37 (Series, DataFrames) feed practicals 1 to 11 and 16 to 20; pages 37 to 41 (descriptive statistics) feed 12 to 15. Practicals 6 (cumsum(), cumprod()) and 8 (mean absolute deviation) are not in the theory notes.
Other Semester 4 papers: BCA 202T Operating Systems, BCA 204T Software Testing, BCA 232 and BCA 234 (NUES); other PCE choices BCA 216T, 218T and 220T; GE-2 options BCA 222T, 224T and 226T.
How to write BCA 212T answers: two-mark definitions, Python output answers and ten-mark statistics numericals
Question 1 carries ten two-mark answers with at least two from each unit, so no BCA 212T unit can be skipped. The notes answer each in two or three lines: a one-sentence definition, then one example or formula. "Noisy data" gets a definition plus age = 250; "IQR" gets Q3 − Q1 plus why it beats the range.
For Python output questions, page 30 stresses two rules: indexing starts at 0, and a slice's stop value is not included. A NumPy slice is also a view, so changing it changes the original array, and loc includes the stop label while iloc does not.
For numericals, page 18 sets the order: formula, substitution, final answer. Hypothesis tests on page 59 add three steps: state H₀ and H₁, compare the calculated value with the table value, and write the conclusion in plain words.
Worked example (page 55): Spearman's rank correlation
Two judges mark five students: A = 85, 60, 73, 40, 90 and B = 93, 75, 65, 50, 80. Ranks (highest = 1) are 2, 4, 3, 5, 1 and 1, 3, 4, 5, 2, so d = 1, 1, −1, 0, −1 and Σd² = 4.
Formula: ρ = 1 − 6Σd² ÷ n(n² − 1). Substitute: 1 − (6 × 4) ÷ (5 × 24) = 1 − 24 ÷ 120. Answer: ρ = 0.8, high positive agreement between the judges.
Unit 4 case-study answers should not stop at numbers. Page 66 asks you to close with the decision the numbers support, such as raising stock from September because October and November sales run about 50% above the monthly average.
Before the exam, revise the quick revision table at the end of each unit, because it lists every formula in one place. Practise this layout on GGSIPU BCA important questions and on the BCA 212T exam corner above.
BCA 212T Data Science notes FAQs
Is BCA 212T a compulsory paper in BCA Semester 4?
No. BCA 212T is one of four Programme Core Elective (PCE) theory papers in Semester 4, alongside BCA 216T, BCA 218T and BCA 220T. Each comes with its matching lab, so choosing Introduction to Data Science means also taking BCA 212P Data Science Lab. Which electives actually run depends on your institute, so check with your college.
What is the passing mark for BCA 212T?
BCA 212T is marked out of 100: 40 internal and 60 end-term. The BCA scheme of examination does not print a separate pass percentage for this paper, so we do not quote one. End-term minimums, aggregate rules and re-appear rules come from IPU's Ordinance 11 on examinations, so check it on ipu.ac.in or with your examination cell.
Which BCA 212T unit has the most Python programs?
Unit 2 has the most: 25 of the 35 Python programs with output in these notes sit in it, across NumPy arrays, Pandas Series and DataFrames, groupby, pivot tables and descriptive statistics. Unit 4 has 7 inside its case studies, Unit 3 has 3 SciPy checks, and Unit 1 relies on numericals such as binning and normalisation.
Do the BCA 212T notes follow the 2024-25 BCA scheme?
Yes. The notes were checked against the BCA scheme and syllabus for students admitted in 2024-25 onwards, whose second-year syllabus was approved on 01 August 2025. All four official units are covered, including the three case studies in Unit IV. A batch on an older scheme should check its own syllabus first, as topics may differ.
How is BCA 212T different from the BCA 212P lab?
BCA 212T is the theory paper: 4 credits, 60 end-term marks and 40 internal marks, covering data science concepts, statistics and case studies. BCA 212P is the practical paper: 2 credits and 4 practical hours a week, where you implement at least 15 Pandas programs from a list of 20. The lab has its own notes.
Get the full BCA 212T Introduction to Data Science Notes on WhatsApp
These Introduction to Data Science notes in English come as an 80-page printed book and are not sold as a PDF. All 35 programs and 19 numericals are inside.
| Unit | Pages | Page count |
|---|---|---|
| Unit 1 | 4 to 23 | 20 |
| Unit 2 | 24 to 46 | 23 |
| Unit 3 | 47 to 64 | 18 |
| Unit 4 | 65 to 79 | 15 |
| Cover, contents, back cover | 1 to 3, 80 | 4 |
Pages in the BCA 212T notes book, unit by unit
- Unit
- Unit 1
- Pages
- 4 to 23
- Page count
- 20
- Unit
- Unit 2
- Pages
- 24 to 46
- Page count
- 23
- Unit
- Unit 3
- Pages
- 47 to 64
- Page count
- 18
- Unit
- Unit 4
- Pages
- 65 to 79
- Page count
- 15
- Unit
- Cover, contents, back cover
- Pages
- 1 to 3, 80
- Page count
- 4
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Unnati Educations is an independent education provider based in Vikaspuri, Delhi. We are not affiliated with, authorised by, or endorsed by Guru Gobind Singh Indraprastha University (GGSIPU). 'GGSIPU' and 'IPU' are used only to describe the syllabus our notes follow. For official information, visit ipu.ac.in.
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