# Regression & Forecasting for Data Scientists using Python

- Offered byCoursera

## Regression & Forecasting for Data Scientists using Python at Coursera Overview

Duration | 12 hours |

Start from | Start Now |

Total fee | Free |

Mode of learning | Online |

Official Website | Explore Free Course |

Credential | Certificate |

## Regression & Forecasting for Data Scientists using Python at Coursera Highlights

- Earn a certificate of completion
- Add to your LinkedIn profile
- 21 quizzes

## Regression & Forecasting for Data Scientists using Python at Coursera Course details

- What you'll learn
- Develop expertise in time series analysis, forecasting, and linear regression
- Analyze techniques for exploratory data analysis, trend identification
- Understand various time-series models and implement them using Python
- Prepare and preprocess data for accurate linear regression modeling
- Build and interpret linear regression models for informed decision-making

- This course provides comprehensive training in regression analysis and forecasting techniques for data science, emphasizing Python programming. You will master time-series analysis, forecasting, linear regression, and data preprocessing, enabling you to make data-driven decisions across industries

## Regression & Forecasting for Data Scientists using Python at Coursera Curriculum

**Time-Series Analysis and Forecasting**

Introduction to Regression & Forecasting for Data Scientists using Python

Introduction to Time-Series Basics

Time-Series Forecasting Use Cases and steps

Forecasting Model Creation

Time-Series Basic Notations

Installing Anaconda and Jupyter Notebook

Data Loading in Python Part 1

Data Loading in Python Part 2

Data Loading in Python Part 3

Feature Engineering in Python Part 1

Feature Engineering in Python Part 2

Visualization in Python Part 1

Visualization in Python Part 2

Visualization in Python Part 3

Time-Series Power Transformation

Moving Average

Exponential Smoothing

Conclusion to Time - Series Analysis and Forecasting

Course Introduction

Course Syllabus

Python for Data Analysis

Feature Engineering Techniques for Time-Series Data

Time Series Transformation Techniques

Practice Quiz: Time - Series Basics

Practice Quiz: Time-Series Data Loading and Feature Engineering

Practice Quiz: Time-Series Visualization

Practice Quiz: Time - Series Transformation

Graded Quiz: Time-Series Analysis and Forecasting

Time-Series Analysis and Forecasting

Ungraded Lab: Time Series Analysis and Forecasting

**Time-Series Models**

Introduction to Time-Series Models

Test Train Split in Python Part 1

Test Train Split in Python Part 2

Walk Forward Validation

Naïve (Persistence) Model in Python Part 1

Naïve (Persistence) Model in Python Part 2

Auto-regression basics

Auto-regression model creation Part 1

Auto-regression model creation Part 2

With Validation in Python

Moving average model basics

Moving average model in python Part 1

Moving average model in python Part 2

ACF and PACF

ARIMA Model Basics

ARIMA Model in Python Part 1

ARIMA Model in Python Part 2

ARIMA Model validation in python

SARIMA Model

SARIMA Model in Python Part 1

SARIMA Model in Python Part 2

Conclusion to Time-Series Models

Evaluating Time Series Forecasting Models

Choosing the Right Forecasting Method

Understanding ACF and PACF Plots

Practice Quiz: Naïve (Persistence) Model

Practice Quiz: Auto Regression Model

Practice Quiz: Moving Average Model

Practice Quiz: ARIMA Model

Practice Quiz: Time-Series Models

Graded Quiz: Time-Series Models

Time-Series Models

Ungraded Labs: Time Series Models

**Linear Regression - Data Preprocessing**

Introduction to Linear Regression - Data Preprocessing

The dataset and data dictionary Part 1

The dataset and data dictionary Part 2

Importing data in Python

Univariant analysis and EDD in Python Part 1

Univariant analysis and EDD in Python Part 2

Outlier treatment in Python

Missing value imputation in python

Seasonality in data

Bi-Variant Analysis and Variable Transformation Part 1

Bi-Variant Analysis and Variable Transformation Part 2

Handling quantitative data

Dummy variable creation in python

Correlation analysis

Correlation analysis in python

Conclusion to Linear Regression - Data Preprocessing

Handling Outliers in Time Series Data

Bivariate Analysis

Lagged Correlation: Analyzing Time-Series Dependencies

Practice Quiz: EDD and Outlier

Practice Quiz: Missing Values

Practice Quiz: Bi-variant Analysis

Practice Quiz: Correlation Analysis

Graded Assessment: Linear Regression - Data Preprocessing

Linear Regression - Data Preprocessing

Ungraded Labs: Linear Progression Data Preprocessing

**Linear Regression - Model Creation**

Introduction to Linear Regression - Model Creation

OLS method

Accessing Accuracy of Predicted Coefficients Part 1

Accessing Accuracy of Predicted Coefficients Part 2

RSE and R - Square

Simple Linear Regression in Python Part 1

Simple Linear Regression in Python Part 2

Multiple-Linear Regression

Multiple-linear regression Part 1

Multiple-linear regression Part 2

F-Statistics

Results of Categorical Variables

Test-train Split in python

Conclusion to Linear Regression - Model Creation

Conclusion to Regression & Forecasting for Data Scientists using Python

Understanding OLS Method

Applied Linear Statistical Models

Understanding Test-Train

Practice Quiz: Basics Equation

Practice Quiz: Simple Linear Regression

Practice Quiz: Multiple-linear regression

Practice Quiz: Test-Train

Graded Quiz: Linear Regression - Model Creation

Linear Regression - Model Creation

Ungraded Labs: Linear Regression - Model Creation

## Regression & Forecasting for Data Scientists using Python at Coursera Admission Process

## Important Dates

## Other courses offered by Coursera

### Student Forum

**Anything you would want to ask experts?**