Time series Analysis in Python

The primary goal of this course is to get started on Times Series Analysis with no prior experience. You will have the opportunity to walk through hands-on Time series in Python. Time series are one of the most common data types encountered in daily life. Time series can be encountered in Financial prices, home energy usage, weather, and all examples of data that can be collected at regular intervals.

In this course, we will go from the very early concept such as Skiwness, to advanced topics on Time Series Analysis Using Python programming language..

  • Understand Normality test analysis.
  • With complete access to course materials and activities.
  • Get familiar with probability theory and statistics tools like Skewness
  • Time Series helps retrieving financial data.
  • Use Pandas dataframes to plot with matplotlib.
  • Use Additive Model for analyzing and predicting periodic data.

What is the target audience?

The course is designed for complete beginners to be able to follow it. This can be is intimidating for beginners, but you will see it is quite detailed for all levels of Data Scientists. There are a lot of tutorials, documentation and advice already out but how do you start and proceed with learning ?

We are here to help!

Starting Course

1
Learn Data Science at PyCademy
3min

In this two-day workshop, we will help you get started learning how to program in Python 3, one of the most popular languages for quick scripts, production software, and doing data science

Normality test analysis

1
Skewness
2
Anderson-Darling Test
3
Kolmogorov-Smirnov
4
D’Agostino’s K^2 Test
5
Shapiro-Wilk

Normality Transformation

1
Log Transformation
2
Square Root Transformation
3
Reciprocal Transformation
4
Cube Root Transformation
5
Box-Cox transform

Stationary Test & Making a Time Series Stationary

1
KPSS (Kwiatkowski-Phillips-Schmidt-Shin) Test

ACF & PACF

1
What is ACF
2
What is PACF
Faq Content 1
Faq Content 2

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Enrolled: 37 students
Duration: 12 hours
Lectures: 14
Video: 9 hours
Level: Advanced

Archive

Working hours

Monday 9:30 am - 6.00 pm
Tuesday 9:30 am - 6.00 pm
Wednesday 9:30 am - 6.00 pm
Thursday 9:30 am - 6.00 pm
Friday 9:30 am - 5.00 pm
Saturday Closed
Sunday Closed