Name: Kalyani Data Science and Analytics Using Python Data Analytics - I As per NEP Syllabus M.Sc. 1st Sem PU
Brand: Disha Publication
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Kalyani Data Science and Analytics Using Python Data Analytics - I As per NEP Syllabus M.Sc. 1st Sem PU

by Madhurima

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Type : book
Weight : GM
ISBN :
Publisher : Kalyani Publishers
Seller : Amit Singh
Authors : Nisha Gupta Shanky Kansal

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Q1

Is this book aligned with the NEP syllabus for M.Sc. 1st Semester?

A1

Yes, it strictly follows the NEP syllabus for M.Sc. 1st Semester (PU).
Q2

Does this book cover Python programming for data science?

A2

Yes, it includes Python basics, operators, control flow, NumPy, and Pandas.
Q3

Are there practical examples for data cleaning and transformation?

A3

Absolutely, it covers real-world data cleaning, preprocessing, and transformation techniques.
Q4

Is this book suitable for beginners with no coding experience?

A4

Yes, it is designed for beginners with step-by-step explanations.
Q5

Which Python libraries are covered in this book?

A5

It includes NumPy, Pandas, and data manipulation techniques.
Q6

Can B.Tech/B.Sc. students use this book?

A6

Yes, it is useful for any student or professional learning data science.
Q7

Does it explain hierarchical indexing and pivot tables?

A7

Yes, Chapter 9 covers these advanced topics.
Q8

Does it include real-world applications of data science?

A8

Yes, Chapter 2 discusses industry applications.
Q9

Is NumPy explained with practical examples?

A9

Yes, Chapter 7 covers NumPy arrays and operations.
Q10

Does it teach data visualization techniques?

A10

While the focus is on data analytics, basic visualization is included in Pandas.

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Have Doubts Regarding This Product ? Ask Your Question

Q1

Is this book aligned with the NEP syllabus for M.Sc. 1st Semester?

A1

Yes, it strictly follows the NEP syllabus for M.Sc. 1st Semester (PU).
Q2

Does this book cover Python programming for data science?

A2

Yes, it includes Python basics, operators, control flow, NumPy, and Pandas.
Q3

Are there practical examples for data cleaning and transformation?

A3

Absolutely, it covers real-world data cleaning, preprocessing, and transformation techniques.
Q4

Is this book suitable for beginners with no coding experience?

A4

Yes, it is designed for beginners with step-by-step explanations.
Q5

Which Python libraries are covered in this book?

A5

It includes NumPy, Pandas, and data manipulation techniques.
Q6

Can B.Tech/B.Sc. students use this book?

A6

Yes, it is useful for any student or professional learning data science.
Q7

Does it explain hierarchical indexing and pivot tables?

A7

Yes, Chapter 9 covers these advanced topics.
Q8

Does it include real-world applications of data science?

A8

Yes, Chapter 2 discusses industry applications.
Q9

Is NumPy explained with practical examples?

A9

Yes, Chapter 7 covers NumPy arrays and operations.
Q10

Does it teach data visualization techniques?

A10

While the focus is on data analytics, basic visualization is included in Pandas.

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