Python Data Science

Course Overview

Course Curriculum

Week 1:

Introduction to Python
Variables, Operators and Expressions
Control Flow
Functions

Week 2:

Week 3:

Week 4: OOPS

Week 5: Statistics

Introduction to Statistics
Different types of Statistics
Population vs Sample
Mean, Median and Mode
Variance, Standard Deviation
Sample Variance why n-1
Standard Deviation
Variables
Random Variables
Percentiles & quartiles
5 number summary
Histograms
Gaussian – Normal distribution
Standard Normal distribution
Application Of Z Score

Week 6: Data Visualization

Week 7: Exploratory Data Analysis

Week 8: Machine Learning Module-1

Week 9: Machine Learning Module-2

Ridge Regression
Lasso Regression
Logistics regression
Difference between Linear Regression and Logistic Regression
Performance matrix
Confusion matrix
Precision, Recall, ROC, AUC Curve
F-beta Score

Week 10: Machine Learning Module-3

Week 11: Machine Learning Module-4

Week 12: Unsupervised Machine Learning

Python Data Science

Course Overview

Course Curriculum

Week 1:

Introduction to Python

Variables, Operators and Expressions

Control Flow

Functions

Week 2:

Data Structures

Week 3:

Modules and Libraries

7-File I/O

Error Handling

Week 4: OOPS

Object-Oriented Programming

Week 5: Statistics

Introduction to Statistics

Different types of Statistics

Population vs Sample

Mean, Median and Mode

Variance, Standard Deviation

Sample Variance why n-1

Standard Deviation

Variables

Random Variables

Percentiles & quartiles

5 number summary

Histograms

Gaussian – Normal distribution

Standard Normal distribution

Application Of Z Score

Week 6: Data Visualization

Numpy

Pandas

Seaborn

Matplotlib

Week 7: Exploratory Data Analysis

Feature Engineering and Selection

Perform EDA with automated library

Week 8: Machine Learning Module-1

Introduction of machine learning

Difference between Supervised, Unsupervised & Semi-supervised

Algorithms

Linear Regression

Logistics regression

Overfitting & Underfitting

Week 9: Machine Learning Module-2

Ridge Regression

Lasso Regression

Logistics regression

Difference between Linear Regression and Logistic Regression

Performance matrix

Confusion matrix

Precision, Recall, ROC, AUC Curve

F-beta Score

Week 10: Machine Learning Module-3

Decision Tree

Random Forest

SVM(Support vector machine)

K Nearest Neighbor

Week 11: Machine Learning Module-4

Ada boosting

Gradient boosting

XGBoosting

Week 12: Unsupervised Machine Learning

K-Means

Hierarchical clustering

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