Course curriculum

  • 1

    Introduction to Python Programming for Data Analytics

    • 1. Motivation for Learning Python Programming Language

    • 2. Anaconda Installation

    • 3. Introduction to Anaconda and Jupyter Notebook Environment

    • 4. Introduction to Jupyter Notebook Interface

    • 5. Introduction to Python Programming Language

    • Programming Series : 1. Syntax of a Programming Language

    • 2. Newline Character

    • 3. Elements, Keywords and Identifiers

    • 4. Comments and Statements

    • 5. Variable Assignments

    • 6. Data Type I in Python Programming

    • 7. Data Type II in Python Programming

    • 8. Type Conversion of a Data Type

    • 9. Output Formatting and Input Function

    • 10. Operators in Python Programming

    • 11. IF Statements

    • 12. While loop Statements

    • 13. For loop Statements

    • 14. Break and Continue Statement

    • 15. Lists-I

    • 16. Lists-II

    • 17. Tuples

    • 18. Sets

    • 19. Dictionary

    • 20. Strings

    • 21. Functions

    • 22. Function Arguments and parameters

    • 23. Built-in Functions

    • 24. Recursive Function

    • 25. Lambda Function

    • 26. Modules,Package and Libraries

    • 27. File I/O Operations

    • 28. Working with Python Directory and Files

    • 29. Exception Handling with Python

    • 30. Comprehension in Python

    • Capstone Project : Project 1 - Reading and Converting Twitter Metadata into Information

    • Project 2 - Text Analysis of Twitter data

    • Project 3 - Creating New dictionary from Twitter data

    • Project 4 - Data Cleaning and Counting of Twitter data

    • Project 5 - Creating Function definition to check a value within Twitter data
  • 2

    Handling Data Arrays using Numpy Module

    • 1. Numpy Introduction

    • 2. Numpy Array Creation

    • 3. Numpy Arange Reshape functions

    • 4. Creating different types of Array using Numpy

    • 5. Accessing Array Values

    • 6. Numpy Operations

    • 7. Fancy Indexing and Sorting Arrays

    • 8. Array Products and Concatenation

    • 9. Broadcasting
  • 3

    Advanced Data Analysis using Pandas Module

    • 1. Pandas Introduction

    • 2. Pandas Series

    • 3. Pandas DataFrames

    • 4. Handling missing data

    • 5. Conditional Selection and Reindexing of a DataFrame

    • 6. Data Input and Data Output

    • 7. Data Processing

    • 8. Grouping & Aggregation and Pivot Table

    • 9. Concatenating DataFrames and Inserting new rows

    • 10. Concatenation and Merging Logic

    • 11. Merging and Joining DataFrames

    • 12. Cartesian Product Between DataFrames

    • 13. Handling Duplicates in a DataFrame

    • 14. Handling Strings in a DataFrame
  • 4

    Handling DateTime Series in a DataFrame

    • 1. DateTime -DateTime Creation

    • 2. DateTime pandas Functions

    • 3. Reading Dates with Informats

    • 4. DateRange and DateOffset
  • 5

    Data Visualization using Matplotlib Module

    • 1. Introduction to Matplotlib

    • 2. Line Chart Plot

    • 3. Plotting a Bar Charts

    • 4. Histogram and Scatter Plot

    • 5. Stack Plot and Pie Plot

    • 6. Plotting Subplots
  • 6

    Probability and Statistics

    • 1. Introduction to Statistics

    • 2. Introduction to Inferential Statistics

    • 3. Measures of Central Tendencies

    • 4. Measures of Dispersion

    • 5. Introduction to Probability

    • 6. Types of Probability functions

    • 7. Probability Density Function

    • 8. Cumulative Distribution Function

    • 9. Skewness and Kurtosis

    • 10. Boxplot

    • 11. Kernel Density Estimation plot

    • 12. Covariance

    • 13. Correlation and Causation

    • 14. Introduction to Linear Regression
  • 7

    Exploratory Data Analysis using Seaborn Module

    • 1. Exploratory Data Analysis using Classroom Dataset

    • 2. Exploratory Data Analysis using IMD Rainfall Dataset

    • 3. Exploratory Data Analysis of Real Estate Dataset

    • 4. Exploratory Data Analysis using IPL player performance Dataset
  • 8

    Capstone Projects

    • Capstone Project -1

    • Capstone Project -2

    • Capstone Project -3

    • Capstone Project Assignment -4

    • Capstone Project Assignment -5

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