Simple Python Time Series Analysis Crash Course

Learn how to snag the most in demand role in the tech field today!

This course will teach you everything you need to know to use Python for forecasting time series data to predict new future data points.

What you’ll learn

  • Use Statsmodels to Analyze Time Series Data.
  • How to Work with Time Series Data with Pandas.
  • Use Facebook’s Prophet Library for forecasting.
  • Data Manipulation.
  • Data Visualization.

Course Content

  • Course Overview –> 1 lecture • 3min.
  • Mammoth Interactive Courses Introduction –> 3 lectures • 15min.
  • What is Machine Learning (Prerequisite) –> 2 lectures • 16min.
  • Build Time Series Analysis Models –> 6 lectures • 31min.
  • Bonus Section – Don’t Miss This –> 1 lecture • 1min.

Simple Python Time Series Analysis Crash Course

Requirements

  • No necessary experience needed.

This course will teach you everything you need to know to use Python for forecasting time series data to predict new future data points.

We’ll start off with the basics by teaching you how to work with and manipulate data using the NumPy and Pandas libraries with Python. Then we’ll dive deeper into working with Pandas by learning about visualizations with the Pandas library and how to work with time stamped data with Pandas and Python.

Then we’ll begin to learn about the statsmodels library and its powerful built in Time Series Analysis Tools.

Afterwards we’ll get to the heart of the course, covering general forecasting models. We’ll talk about creating AutoCorrelation and Partial AutoCorrelation charts and using them in conjunction with powerful ARIMA based models, including Seasonal ARIMA models and SARIMAX to include Exogenous data points.

Afterwards we’ll learn about state of the art Deep Learning techniques with Recurrent Neural Networks that use deep learning to forecast future data points.

This course even covers Facebook’s Prophet library, a simple to use, yet powerful Python library developed to forecast into the future with time series data.

 

If there is some time dependency, then you know it – the answer is time series analysis.

This course will teach you the practical skills that would allow you to land a job as a quantitative finance analyst, a data analyst or a data scientist.

In no time, you will acquire the fundamental skills that will enable you to perform complicated time series analysis directly applicable in practice. We have created a time series course that is not only timeless but also:

· Easy to understand

· Comprehensive

· Practical

· To the point

· Packed with plenty of exercises and resources

But we know that may not be enough.

We take the most prominent tools and implement them through Python – the most popular programming language right now. With that in mind…

Machine Learning and artificial intelligence (AI) is everywhere; if you want to know how companies like Google, Amazon, and even Udemy extract meaning and insights from massive data sets, this data science course will give you the fundamentals you need. Data Scientists enjoy one of the top-paying jobs, with an average salary of $120,000 according to Glassdoor and Indeed. That’s just the average! And it’s not just about money – it’s interesting work too!

 

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