Certified Time Series Analytics Expert
$200.00
Get certified in the most applied skill in the industry for time-series data analysis and forecasting.
- Get certified for your knowledge
- Work on projects and get experience certificate
Description
This certification-oriented course on Time Series Analytics will provide an in-depth understanding of time series data and its applications in various domains such as finance, economics, marketing, and engineering. Attendees will learn about different types of time series models, including ARIMA, SARIMA, and ARMA, and gain hands-on experience in data preparation, forecasting, and model selection.
The course will cover topics such as trend analysis, seasonal patterns, and time series decomposition. attendees will also learn about advanced topics such as state space models and machine learning techniques for time series analysis. By the end of the course, attendees will be equipped with the skills to analyze and forecast time series data, and communicate their findings effectively.
Program Outcome
- Get job ready with complete understanding of time series data and its characteristics, including trends, seasonality, and cyclicality. attendees will be able to apply techniques such as data decomposition and differencing to prepare time series data for analysis.
- Developing skills to select and apply appropriate time series models, such as ARIMA, SARIMA, and exponential smoothing, to make forecasts and predictions. attendees will learn how to evaluate model performance and make adjustments to improve accuracy.
- Gaining experience with advanced topics in time series analysis, such as state space models and machine learning techniques. Attendees will learn how to use these methods to model and forecast complex time series data, and develop an understanding of the limitations and challenges associated with these techniques. By the end of the course, attendees will have a strong foundation in time series analytics and be able to apply these skills in various domains.
Prerequisite
- Intermediate level knowledge of statistics
- Basic knowledge of machine learning
- Intermediate-level knowledge of python programming
- Understanding of mathematical concepts
Time Series Analytics Course Contents
- Introduction to Time Series Analytics
- Overview of time series data and its characteristics
- Applications of time series analysis in various domains
- Time series data visualization and exploration
- Time Series Modeling Basics
- Stationarity and non-stationarity
- Autocorrelation and partial autocorrelation
- AR, MA, and ARMA models
- Advanced Time Series Models
- Seasonal patterns and seasonal ARIMA models (SARIMA)
- Exponential smoothing models
- Holt-Winters method for seasonal data
- Time Series Decomposition and Forecasting
- Decomposition of time series data into trend, seasonal, and residual components
- Trend analysis and forecasting using linear regression
- Time series forecasting using ARIMA, SARIMA, and exponential smoothing models
- Machine Learning Techniques for Time Series Analysis
- Overview of machine learning techniques for time series analysis
- Feature engineering for time series data
- Time series classification and regression using machine learning algorithms
- Time Series Analysis in Practice
- Time series data preprocessing and cleaning
- Model selection and validation techniques
- Case studies and examples of time series analysis in various domains
- Capstone Project
A complete project that covers the skills earned during the course with guidance from industry mentors and support from learner success managers throughout.
FAQs
- Who can attend this course?
This course is suitable for beginners as well as professionals working in analytics domains.
- What is the mode of delivery?
This course has different modes of delivery. It can be taken in person from a center over the weeks, or it can be taken online as well based on your own convenience.
- Will there be an instructor also in this course?
Yes, an instructor will be there for in-person delivery and online (instructor-led) delivery.
- What are the prerequisites to attend this course?
Basic understanding of statistics, machine learning, python, and mathematics is required to attend this course.
- How difficult is this course to learn?
The course has beginner-level difficulty.
- What job roles can i take if i attend this course?
Data scientists, Data Analyst, and other Analytics based roles can be explored after taking this course.
- Who can get the certificate?
All attendees who complete all sections of the course along with the capstone project will get the certificate.
- How the completeness of each section is measured in the course?
There are MCQ-based short tests given after each section to assess the understanding of a learner in each section. Finally, the capstone project is evaluated manually by the instructors.
Reviews
There are no reviews yet.