• 4.6/5

  • Intermediate

What is Time Series Analysis?

‘Time’ is the most important factor which ensures success in a business. It’s difficult to keep up with the pace of time.  But, technology has developed some powerful methods using which we can ‘see things’ ahead of time!

Nope, not the time machine, we are talking about the methods of prediction & forecasting. As the name ‘time series forecasting’ suggests, it involves working on time (years, days, hours, minutes) based data, to derive hidden insights to make informed decision making.

What will you learn from Time Series Forecasting using Python Course?

This course is designed for people who want to solve problems related to Time Series Forecasting. By the end of the course, you will learn to apply the following necessary skills and techniques required to solve Time Series problems:

  • ARIMA Model

  • Tuning Parameters for ARIMA

  • Handling Seasonality using ARIMA

  • Moving Average

  • Machine Learning for Time Series forecasting

  • Exponential Smoothing Methods

  • Framework to evaluate Time Series Models

Course curriculum

  • 1
    Introduction to Time Series
    • Introduction to the Course
    • Introduction to Time Series
    • Components of a Time Series
    • AI&ML Blackbelt Plus Program (Sponsored)
  • 2
    Understanding Problem Statements and Data Sets
    • Problem Statement
    • Table of Contents
    • Hypothesis Generation
    • Getting the system ready and loading data
    • Dataset Structure and Content
  • 3
    Exploration and Preprocessing
    • Feature Extraction
    • Exploratory Analysis
    • Exercise 1
  • 4
    Modelling Techniques and Evaluation
    • Splitting the data into training and validation part
    • Modeling Techniques
    • Holt's Linear trend model on daily time series
    • Holt Winter's model on daily time series
    • Introduction to ARIMA model
    • Parameter tuning for ARIMA model
    • SARIMAX model on daily time series
    • Exercise 2
    • Important Links
    • Your Feedback

FAQs

  • Who should take this course?

    This course is meant for people looking to explore Time Series Forecasting in Python.

  • Do I need to install any software before starting the course?

    You will need to download and install python.

  • What is the refund policy?

    The course is free of charge.

  • Do I need to take the modules in a specific order?

    We would highly recommend taking the course in the order in which it has been designed to gain the maximum knowledge from it.

  • Do I get certificate upon completion of the course?

    This is a free course and therefore there is no certificate involved.

  • What is the fee for this course?

    The course is free of charge.

  • How long I can access the course?

    You will have access to the course for a duration of 6 months.

  • Is there any placement support

    This is an introductory course and this does not include any placement support. Once you have worked on a few data science projects and hackathons, you can always apply to jobs on Analytics Vidhya portal