Live Time series

Course Feature
  • Cost
    Free
  • Provider
    Youtube
  • Certificate
    Paid Certification
  • Language
    English
  • Start Date
    On-Demand
  • Learners
    No Information
  • Duration
    5.00
  • Instructor
    Krish Naik
Next Course
2.5
0 Ratings
This three-day live session will provide an overview of time series analysis, including exploratory data analysis, stock analysis, and various forecasting models such as ETS, EWMA, ARIMA, SARIMAX, and Fbprophet. Participants will gain an understanding of the fundamentals of time series analysis and how to apply them to real-world problems.
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Course Overview

❗The content presented here is sourced directly from Youtube platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [February 21st, 2023]

What does this course tell?
(Please note that the following overview content is from the original platform)


Announcing Time Series Live Session With Syllabus And Prerequisites.
Live Day 1- Exploratory Data Analysis And Stock Analysis With Time series Data.
Live Day 2- TimeSeries,ETS,EWMA,ARIMA,SARIMAX, Fbprophet Session.
Live Day 3- ARIMA,SARIMAX, Fbprophet Session.


We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
1. You can learn the basics of time series analysis, such as exploratory data analysis and stock analysis.

2. You can gain a deeper understanding of time series models, such as ETS, EWMA, ARIMA, SARIMAX, and Fbprophet.

3. You can learn how to apply these models to analyze time series data and make predictions.

4. You can gain practical experience in using these models to solve real-world problems.

5. You can gain the skills and knowledge necessary to become a successful time series analyst.

[Applications]
After completing this course, participants can apply their knowledge to analyze time series data and develop forecasting models. They can use the techniques learned in the course to explore and analyze stock data and develop forecasting models using ETS, EWMA, ARIMA, SARIMAX, and Fbprophet. Participants can also use the techniques to develop forecasting models for other types of time series data.

[Career Paths]
1. Data Scientist: Data Scientists use their knowledge of mathematics, statistics, and computer science to analyze large datasets and uncover trends and patterns. They use this information to develop predictive models and algorithms that can be used to make decisions and solve problems. Data Scientists are in high demand as businesses increasingly rely on data-driven decision making.

2. Financial Analyst: Financial Analysts use their knowledge of economics, finance, and accounting to analyze financial data and make recommendations to their clients. They use their expertise to assess the performance of investments, identify potential risks, and develop strategies to maximize returns. Financial Analysts are in high demand as businesses look to maximize their profits and minimize their losses.

3. Business Intelligence Analyst: Business Intelligence Analysts use their knowledge of data analysis and business processes to develop insights and strategies that can be used to improve business performance. They use their expertise to analyze data from multiple sources, identify trends, and develop strategies to optimize operations. Business Intelligence Analysts are in high demand as businesses look to gain a competitive edge in the market.

4. Time Series Analyst: Time Series Analysts use their knowledge of mathematics, statistics, and computer science to analyze time series data and uncover trends and patterns. They use this information to develop predictive models and algorithms that can be used to make decisions and solve problems. Time Series Analysts are in high demand as businesses increasingly rely on data-driven decision making.

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