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- 82% Python for Time Series Data Analysis

Python for Time Series Data Analysis

$19.99Track price

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9.0/10 (Our Score)
Product is rated as #64 in category Python

Welcome to the best online resource for learning how to use the Python programming Language for Time Series Analysis!

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. Including learning about Error–Trend–Seasonality decomposition and basic Holt–Winters methods.

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.

Instructor Details

Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science and programming. He has publications and patents in various fields such as microfluidics, materials science, and data science technologies. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming the ability to analyze data, as well as present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Data Inc. and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, The New York Times, Credit Suisse, and many more. Feel free to contact him on LinkedIn for more information on in-person training sessions or group training sessions in Las Vegas, NV.

Specification: Python for Time Series Data Analysis

Duration

15.5 hours

Year

2020

Level

Intermediate

Certificate

Yes

Quizzes

Yes

25 reviews for Python for Time Series Data Analysis

4.7 out of 5
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  1. Yichun Tsai

    So far so good

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  2. Kashish Bhutani

    great

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  3. Ismael Mart nez Delgado

    Jose explains and teach very well and all the notebooks are completed with futher reading links and information, increasing the quality of each lesson. With any doubt it is a very recommendable course.

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  4. harish kumar

    So far so good

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  5. Ralf Truth

    hjtgfjytfd

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  6. Chinmaya Acharya

    Detailed , handholding by Jose… no other tutor is like him. Only if real world complex datasets can be used to demonstrate complex problem, it can be more useful.

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  7. Fiqih Rosady

    nice

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  8. Haritha Gayathri Kurada

    Great course for beginners of time series analysis but would have been even more helpful if there is at least one multivariate problem in ARMA/ARIMA as this course entirely focuses on uni variate data.

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  9. Mohammed Shammeer

    very good…

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  10. Oleg Kovalev

    pretty concise and reach course with good examples

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  11. Charles Jacob Tan

    Very good course. Everything was easy to understand and straightforward until I reached RNN’s where I began to get lost. Maybe start the Deep Learning Section with easier examples (doesn’t have to be related to time series) so we get a better understanding of how it works.

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  12. Parker Erikson

    Jose is the best. If you need to learn about something and Jose happens to have a course on the topic, consider yourself lucky.

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  13. Mario Cortez

    It’s soon yet to tell if the course has met my expectations. But so far it seems that I’m gonna learn a lot, so I’m looking foward to it.

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  14. Kartikeya Chitranshi

    The explanation was damn good.

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  15. Arindam Bhowal

    It was good

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  16. Asparuh Emilov

    I really like the way you explain every detail making sure that is really clear to the student what is actually doing. It is always exciting to learn from you. Thank you Jose!

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  17. Roxy Xu

    I hope that this lecture can contains more materials for practice examples for rookies like me

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  18. Mihai Maldaianu

    Excellent course, very well explained and goes through most aspects of TSA. The forecasting section is particularly detailed, going through all variations of ARIMA models. Section on RNN is also a great addition, with plenty of examples.

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  19. Drive Lean

    very clear!

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  20. Oliver

    Las clases y los apuntes son excelentes!

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  21. Yolla Haifah

    Great course ! Jose knows what he’s doing pretty well. Thank you !!! maybe there are times when I load the code and it won’t work but whoever just new started this course don’t worry! . learn to find till it works and u gonna feels really cool about it ! XD . about to take your My sql course later soon hehe

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  22. Lusi Yang

    Jose is a good instructor. He covers pretty much all the topics I need for work. 🙂

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  23. Roberto Bonilla Ibarra

    Muy bien preparado el material

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  24. Geoffrey

    Great for a beginner

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  25. Mehmet Ketenci

    The reason I disappointed is detailed examples are insufficient and some are wrong examples lead students to wrong direction.He is taking training data to fit and then he took entire data to evaluate how model was good. Of course score will increase. I sensed deception. That is my opinion.

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    Python for Time Series Data Analysis

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