Tuesday, 29 July 2025

ANU UG/Degree B.Sc Foundation of Data Science Material all 5 Units PDF

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 ANU UG/Degree B.Sc Foundation of  Data Science Material all 5 Units PDF are now available for downloading. Here you get all ANU B.Sc 5th Semester Material along with lab manuals.  For latest updates on exams, results, time tables, materials, previous year papers book mark this webiste.



Why ANU UPDATES MATERIALS so important?

  1. Free of cost
  2. Prepared by most experienced and well qualified faculty.
  3. 100% error free content.
  4. Screenshots for each and every example when required.

UNIT-I (Introduction to Data Science)
  • Need for Data Science 
  • What is Data Science 
  • Evolution of Data Science, 
  • Data Science Process 
  • Business Intelligence and Data Science 
  • Prerequisites for a Data Scientist 
  • Tools and Skills required. 
  • Applications of Data Science in various fields 
  • Data Security Issues.
  • Data Collection Strategies
  • Data Pre-Processing Overview
  • Data Cleaning
  • Data Integration and Transformation
  • Data Reduction
  • Data Discretization
  • Data Munging, Filtering


Descriptive Statistics – Mean, Standard Deviation, Skewness and Kurtosis; Box Plots – Pivot Table – Heat Map – Correlation Statistics –ANOVA.

No-SQL: Document Databases, Wide-column Databases and Graphical Databases.

Download UNIT-II Material Here

Download UNIT-II Material Here SET-II

UNIT-III

Python for Data Science –Python Libraries, Python integrated Development Environments (IDE) for Data Science, 

NumPy Basics: Arrays and Vectorized Computation- The NumPy ndarray-Creating ndarrays- Data Types for ndarrays- Arithmetic with NumPy Arrays- Basic Indexing and Slicing - Boolean Indexing-Transposing Arrays and Swapping Axes.

Universal Functions: Fast Element-Wise Array Functions- Mathematical and Statistical Methods-Sorting- Unique and Other Set Logic.

Download UNIT-III Material Here

Download UNIT-III Material Here SET-II

UNIT-IV Introduction to pandas Data Structures Series, Data Frame and Essential Functionality:

 Dropping Entries- Indexing, Selection, and Filtering- Function Application and Mapping- Sorting and Ranking.
Summarizing and Computing Descriptive Statistics- Unique Values, Value Counts, and Membership. Reading and Writing Data in Text Format.

Download UNIT-IV Material Here

Download UNIT-IV Material Here SET-II

UNIT-V Data Cleaning and Preparation

Handling Missing Data - Data Transformation: Removing Duplicates, Transforming Data Using a Function or Mapping, Replacing Values, Detecting and Filtering Outliers-
Plotting with pandas: Line Plots, Bar Plots, Histograms and Density Plots, Scatter or Point Plots.





Download Data sets from here






Text Book(s)
  1. Y. Daniel Liang, “Introduction to Programming using Python”, Pearson, 2012.
  2. Wes McKinney, “Python for Data Analysis: Data Wrangling with Pandas, NumPy,and IPython”, O’Reilly, 2nd Edition, 2018.
Reference Books
  1. Sanjeev Wagh, Manisha Bhende, Anuradha Thakare, ‘Fundamentals of Data Science, CRC Press, 1st Edition, 2022
  2. Jake VanderPlas, “Python Data Science Handbook: Essential Tools for Working with Data”, O’Reilly, 2017

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