LinkedIn – Time Series Modeling in Excel, R, and Power BI 2023-3

Time Series Modeling in Excel, R, and Power BI. This course teaches you how to use time series models to make accurate predictions using Excel, R, and Power BI. In the dynamic world of data science, time series models play a key role. Helen Wall, the instructor of this course, teaches you how to implement ARIMA (Autoregressive Integrated Moving Average) models in these tools. You will be introduced to the basic concepts of time series decomposition, autoregressive coefficients, autocorrelation, moving averages, stationarity, and random movements, and you will learn how to make predictions with Power BI. By the end of the course, you will be able to analyze data to make effective business decisions.

What you will learn

• Complete understanding of time series models: You will learn the concept of time series models and their importance in data analysis.
• Time Series Decomposition: You will learn how to decompose a time series into different components (trend, seasonal, and residual) to make more accurate forecasts.
• Working with dates and times in data: You will learn how to work with different date and time formats and create date/time indexes in time series.
• Filtering and Handling Incomplete Data: You will learn how to filter data and remove or handle missing values (NA) in time series.
• Aggregating and grouping time series data: You will learn about different methods of aggregating and grouping time series data for various analyses.
• Autoregression and Moving Average: You will understand the concepts of autoregression and moving average and learn how to apply them in modeling.
• Autocorrelation and Partial Autocorrelation: You will learn about the concepts of autocorrelation and partial autocorrelation and their importance in pattern recognition.
• The concept of stationarity: You will learn the importance of stationarity in time series and how to examine and achieve it.
• ARIMA Modeling: You will be introduced to ARIMA modeling and learn how to use it to forecast time series.
• Time Series Modeling in Power BI: Learn how to use Power BI to model and forecast time series.
• Predicting Future Trends: You will gain the skills necessary to predict future trends and make data-driven decisions.

This course is suitable for people who:

• Data scientists and analysts: People who want to expand their skills in time series modeling and forecasting.
• Business professionals: Managers and professionals who need to make data-driven decisions and predict business trends.
• Students: Students in computer science, statistics, economics, and other related fields who are looking to learn the practical applications of time series.
• Anyone who works with data: People who regularly work with time-based data and are looking for tools for forecasting and analysis.

Time Series Modeling in Excel, R, and Power BI Course Details

• Publisher: LinkedIn
• Instructor: Helen Wall
• Training level: Advanced
• Training duration: 2 hours

Course topics

Course images

Sample course video

Download link

Download file – 386 MB

File(s) password: www.downloadly.ir

File size

386 MB