PYTHON
Data science with python syllabus
1st week
Basics of Python(Duration 6 hours)
Python Introduction
Introduction
Data structures in python
What is Python
Why Python
Installation
Jupyter notebook
Basics of python
Lists
Tuples
Dictionaries
Sets
Control structures in python
If-Elif-Else
Loops
Comprehension
Functions
Map, Filter and Reduce
Functions
Arrays
Selection by position and labels(ILoc,Loc)
Graded questions
2nd week
Data science with Python
Introduction to Numpy
Introduction
Numpy basics
Creating Numpy arrays
Structure and content of arrays
Subset, slice, index and iterate through arrays
Multidimensional arrays
Computation times in numpy and standard python lists
Operations on numpy arrays
Basic operations
Operations on arrays
Basic linear algebra operations
Introduction to pandas
Introduction
Pandas basics
Indexing and selecting data
Merge and append
Grouping and summarizing data frames
Lambda function & pivot tables
Getting and cleaning data
Introduction
Reading Delimited and Relational Databases
Reading Data from websites
Getting Data from APIs
Reading Data from PDF files
Cleaning Datasets
Graded questions
3rd week
Assignment
4th week
Case study
5th week
Data Visualization
Visualization Purpose and Intro
Visualization examples
Understanding chart type
Plots for Data Distribution
Introduction
Components of a plot
Subplots
Functionalities of plots
Univariate distributions
Univariate distributions-rug plots
Bivariate distributions
Bivariate distributions plotting pairwise relationships
Time Series and Discrete Data Plotting
Plotting distributions across categories
Plotting aggregate values across categories
Time series data
Graded questions
6th week
EDA
Data Sourcing
Introduction to EDA
Public and private data
Exercise with private and public data
Data Cleansing Methods-Imputation
Fixing rows and columns
Handling missing values
Standardizing values
Invalid values
Filtering data
imputation
Univariate and Segmented Univariate Analysis
Unordered categorical variable analysis
Ordered categorical variable analysis
Basis of segmentation
Way of segmentation
Comparison of other metrics
Bivariate Analysis
Bivariate analysis on continuous variables
Correlation
Bivariate analysis on categorical variables
Derived Metrics
Introduction to derived metrics
Type driven metrics
Business driven metrics
Data driven metrics
Graded questions
7th week
Assignment