Udemy – Time Series Analysis in Python 2020 2020-1

Description

Time Series Analysis in Python is the name of a series of video tutorials on business and time data analysis. In fact, in this course you will become a financial analyst by learning your practical skills. Students in this course will also be well acquainted with the analysis of complex time series. This course is also presented in a way that students can understand the educational content in the best possible way and easily. Having categorized exercises along with a wealth of resources will also help you more.

Students in this course will work with various Python libraries such as StatsModels, matplotlib, NumPy, yfinance, ARCH, pmdarima and more. You will also be taught the most commonly used skills in this course. You can take yourself to a very high level of data analysis by watching the tutorials in this course and solving the exercises provided. This training course is designed and published for beginners in programming and people interested in finance.

Items that are taught in this course

Understand the difference between time series data and cross-sectional data

Learn the basic skills of time series data

Understand and learn how to use time data in real projects

Learn Python programming skills to analyze data

Learn how to work with a variety of Python libraries in a practical way

Learn how to interpret and analyze the data obtained

Time Series Analysis in Python

English language

Duration: 7 hours and 20 minutes

Number of courses: 95

Instructor: 365 Careers

File format: mp4

Time Series Analysis in Python

Course content 95 lectures 07:20:44

Introduction 1 lecture 04:54

Setting Up the Environment 8 lectures 18:40

Introduction to Time Series in Python 7 lectures 23:27

Creating a Time Series Object in Python 7 lectures 28:47

Working with Time Series in Python 8 lectures 38:42

Picking the Correct Model 1 lecture 02:32

Modeling Autoregression: The AR Model 12 lectures 53:57

Adjusting to Shocks: The MA Model 7 lectures 34:06

Past Values and Past Errors: The ARMA Model 8 lectures 41:52

Modeling Non-Stationary Data: The ARIMA Model 9 lectures 45:30

Measuring Volatility: The ARCH Model 7 lectures 33:42

An ARMA Equivalent of the ARCH: The GARCH Model 5 lectures 13:39

Auto ARIMA 6 lectures 27:35

Forecasting 8 lectures 45:34

Business Case 1 lecture 27:47

Prerequisite for Time Series Analysis in Python

No prior experience with time-series is required.

You’ll need to install Anaconda. We will show you how to do that step by step.

Some general understanding of coding languages is preferred, but not required.

Installation

After Extract, watch with your favorite Player.

English subtitle

Quality: 720p