Postgraduate certificate Time Series and Forecast for Data Analysis

In the 21st century, technology has allowed the generation of large amounts of data, a source of incalculable business value, which requires the use of innovative techniques to process and analyze them. For this reason, this program has been designed to allow the professional to deeply analyze time series and their different models. These, together with the forecast, will help you to make the best sales, profit and loss forecasts for your company. Therefore, this program will allow you to bring your company closer to success thanks to the data that you will be able to collect from the tools obtained.

University certificate

duration

6 weeks

Modality

Online

Schedule

At your own pace

Exams

Online

start date

Credits

6 ECTS

financing up to

3 months

Price(first year)

See price

The world's largest school of business”

Syllabus

The Postgraduate certificate in Time Series and Forecast for Data Analysis is the ideal opportunity to learn about the models that allow the analysis of stochastic phenomena. Thanks to the partnership with an excellent group of experts, TECH has devised a program that meets all the requirements and demands of a booming sector. In this way, the student will be able to better understand the most commonly used models to predict the behavior of a time series, improving the economic performance of his company.

You will lead your company to success thanks to the data analysis techniques that you will acquire in the development of this Postgraduate certificate"

Syllabus

It is essential in this new era to have professionals who are capable of exploring and extracting knowledge that adds value and supports the decisions they make in any professional field. In this sense, analyzing stochastic phenomena has become the main objective of time series models. In this Postgraduate certificate, special emphasis will be given to those models that represent greater versatility and adaptation for the analysis of these systems.

Therefore, during the development of this program, it will be possible to delve into the theoretical foundations on the spectral analysis of univariate time series, as well as the fundamental aspects related to inference based on the eriodogram and its interpretation.

All the knowledge contained in this program is supported by the experience of an excellent teaching staff that, in a dynamic and practical way, will present several examples applicable to the student's daily work.

For these reasons, this Postgraduate certificate is perfect for those professionals who wish to add value to their companies, based on the deep, detailed and accurate analysis of data.

This Postgraduate certificate takes place over 6 weeks and it consists of 1 module:

Module 1. Time Series and Forecast for Data Analysis

Where, When and How is it Taught?

TECH offers the possibility of developing this Postgraduate certificate in Time Series and Forecast for Data Analysis completely online. During the 6 weeks that the specialization program lasts, the student will be able to access all the contents of this program at any time, which will allow them to manage their own study time.

Module 1. Time Series and Forecast for Data Analysis

1.1. Time Series

1.1.1. Objectives
1.1.2. Application

1.2. Components of a time series

1.2.1. Trend component - Seasonal
1.2.2. Cycle
1.2.3. Waste

1.3. Types of time series

1.3.1. Stationary time series
1.3.2. Stationary time series
1.3.3. Box-Cox Transformation

1.4. Basic Forecasting Methods

1.4.1. Media
1.4.2. Naïve
1.4.3. Seasonal Naïve
1.4.4. Method Comparison

1.5. Waste Analysis

1.5.1. Autocorrelation
1.5.2. ACF of Waste
1.5.3. Correlation Test

1.6. Predictive Methods of Time Series

1.6.1. ARIMA
1.6.2. RMA
1.6.3. Exponential Smoothing

1.7. Measures of forecast accuracy

1.7.1. MAE
1.7.2. MSE
1.7.3. RMSE
1.7.4. MAPE

1.8. Forecasting Stages

1.8.1. Model identification
1.8.2. Estimate
1.8.3. Verification-Prediction

1.9. Manipulation and Analysis of Time Series with R

1.9.1. Data Preparation
1.9.2. Identification of Patterns
1.9.3. Model Analysis
1.9.4. Prediction

1.10. Combined Graphical Analysis with R

1.10.1. Application of graphical analysis combined with R

If your company needs a change, here is the answer: consolidate your career in time series analysis and add value to your business decisions"

Teaching Objectives

The main objective of this Postgraduate certificate is to strengthen the student's knowledge in the field of time series. In this way, TECH guarantees that students will develop their professional goals in a competitive environment. Throughout the 150 hours of learning that make up this program, students will be able to better understand the concepts of univariate models, dynamic regression and niche construction methodology. This way, after completing the program, the professional will be able to make global decisions with an innovative perspective and an international vision.

Apply the best dynamic regression models, as well as the methodology of building such models from observed series and direct your objectives to be the best professional in your work environment"

TECH makes the goals of their students their own goals too.
Working together to achieve them.

The Postgraduate certificate in Time Series and Forecast for Data Analysis enables the student to:

Develop advanced knowledge of time series
Identify the pattern and characteristics of time series
Predict the behavior of a time series, based on the knowledge of the models studied
Develop specialized knowledge of time series
Develop the formulation and basic properties of univariate time series models
Apply the fundamentals of real time series modeling and forecasting methodology
Analyze univariate models including outliers
Apply dynamic regression models, as well as the methodology for the construction of such models from observed series
Establish the theoretical foundations of spectral analysis of univariate time series, as well as the fundamental aspects related to inference based on the eriodogram and its interpretation
Estimate the probability and trend in time series for a given time horizon

Postgraduate Certificate in Time Series and Forecast for Data Analysis.

Time series is a tool for data analysis that is used to analyze the evolution of a data set over time. This involves the study of the regularity and trends of a data set, as well as its projection into the future.

The objective of time series is to identify patterns and trends, such as the increase or decrease in sales or production in a company over the years. These patterns can be analyzed by statistical techniques and mathematical models, in order to make forecasts about future trends.

One of the most widely used models for time series analysis is the ARIMA (Autoregressive Integrated Moving Average) model. This model uses historical information to predict future values in a time series. The ARIMA model can be used to analyze different types of data, such as sales, production, prices, stocks, among others.

Time series analysis is also fundamental in business management as it allows for making projections and predictions important for strategic decision making. For example, knowing in which months there is usually greater demand for a product helps the company to plan its production and inventory management.

The forecasting technique is based on the analysis of time series to predict future events. For example, time series analysis can be used to predict the future growth of a company, the evolution of the market in the future, customer behavior, among others.

Time series and forecasting are essential for data analysis in business. These techniques use mathematical and statistical models to analyze the temporal evolution of data and make relevant forecasts for decision making in companies.

Students learn techniques to predict the future behavior of a variable, including techniques such as exponential smoothing, linear regression modeling and trend forecasting.