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~ Time Series Analysis and Forecasting using Python

FREE 
29.99

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Time Series Analysis and Forecasting using Python
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Time Series Analysis and Forecasting using Python

Requirements

  • Students will need to install Python and Anaconda software but we have a separate lecture to help you install the sameStudents will need to install Python and Anaconda software but we have a separate lecture to help you install the same

Description

You’re looking for a complete course on Time Series Forecasting to drive business decisions involving production schedules, inventory management, manpower planning, and many other parts of the business., right?

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You’ve found the right Time Series Forecasting and Time Series Analysis course using Python Time Series techniques. This course teaches you everything you need to know about different time series forecasting and time series analysis models and how to implement these models in Python time series.

After completing this course you will be able to:

  • Implement time series forecasting and time series analysis models such as AutoRegression, Moving Average, ARIMA, SARIMA etc.
  • Implement multivariate time series forecasting models based on Linear regression and Neural Networks.
  • Confidently practice, discuss and understand different time series forecasting, time series analysis models and Python time series techniques used by organizations

How will this course help you?

Verifiable Certificate of Completion is presented to all students who undertake this Time Series Forecasting course on time series analysis and Python time series applications.

If you are a business manager or an executive, or a student who wants to learn and apply forecasting models in real world problems of business, this course will give you a solid base by teaching you the most popular forecasting models and how to implement it. You will also learn time series forecasting models, time series analysis and Python time series techniques.

Why should you choose this course?

We believe in teaching by example. This course is no exception. Every Section’s primary focus is to teach you the concepts through how-to examples. Each section has the following components:

  • Theoretical concepts and use cases of different forecasting models, time series forecasting and time series analysis
  • Step-by-step instructions on implement time series forecasting models in Python
  • Downloadable Code files containing data and solutions used in each lecture on time series forecasting, time series analysis and Python time series techniques
  • Class notes and assignments to revise and practice the concepts on time series forecasting, time series analysis and Python time series techniques

The practical classes where we create the model for each of these strategies is something which differentiates this course from any other available online course on time series forecasting, time series analysis and Python time series techniques.

.What makes us qualified to teach you?

  • The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using Analytics and we have used our experience to include the practical aspects of Marketing and data analytics in this course. They also have an in-depth knowledge on time series forecasting, time series analysis and Python time series techniques.

 

  • Section 7 – Theoretical Concepts

This part will give you a solid understanding of concepts involved in Neural Networks.

In this section you will learn about the single cells or Perceptrons and how Perceptrons are stacked to create a network architecture. Once architecture is set, we understand the Gradient descent algorithm to find the minima of a function and learn how this is used to optimize our network model.

  • Section 8 – Creating Regression and Classification ANN model in Python

In this part you will learn how to create ANN models in Python.

We will start this section by creating an ANN model using Sequential API to solve a classification problem. We learn how to define network architecture, configure the model and train the model. Then we evaluate the performance of our trained model and use it to predict on new data. We also solve a regression problem in which we try to predict house prices in a location. We will also cover how to create complex ANN architectures using functional API. Lastly we learn how to save and restore models.

I am pretty confident that the course will give you the necessary knowledge and skills related to time series forecasting, time series analysis and Python time series techniques to immediately see practical benefits in your work place.

Go ahead and click the enroll button, and I’ll see you in lesson 1 of this course on time series forecasting, time series analysis and Python time series techniques!

Cheers

Start-Tech Academy

Who this course is for:

  • People pursuing a career in data science
  • Working Professionals beginning their Machine Learning journey
  • Statisticians needing more practical experience
  • Anyone curious to master Time Series Analysis using Python in short span of time


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Time Series Analysis and Forecasting using Python

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FREE 
29.99

 ~ 
Time Series Analysis and Forecasting using Python
FREE 29.99
~ Time Series Analysis and Forecasting using Python

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