Trending September 2023 # Time Series Course (11 Courses Bundle, Online Certification) # Suggested October 2023 # Top 13 Popular |

Trending September 2023 # Time Series Course (11 Courses Bundle, Online Certification) # Suggested October 2023 # Top 13 Popular

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The central idea behind providing this training program on time series is to make people profession with the use of prediction and forecasting techniques that are one of the most demanded skills of the industries. With the help of this training program what would be able to understand the core concepts and different technologies that are required for understanding the time series analysis that is used commonly used for forecasting and prediction of unforeseen events and analysis. The training also helps in bridging the gap between the industry demand and the skills that people hold.

the training program of time series analysis is a bundle of many different tools and technologies that are going to be covered and taught at this training program. The curriculum is developed by keeping in mind different requirements of the industries as well as the individuals who are looking forward to learning something new and demanding too in nature. survival skills that individuals will learn in this training program are statistical tools, Microsoft Excel, machine learning, python, data analysis, forecasting tools and techniques, basics of the R language, and many other skills that are very much demanded in nature. With the knowledge of these skills when would be able to secure a job in the industry as a data analyst, business analyst, predictive analyst, machine learning analyst, consultant, and a pool of other opportunities that are open for the individual once they will complete this training program successfully.

Course Highlights

Many skills are going to be covered under this training program. Some of the core skills that one will learn through this program are as follows:

Under the module of statistical tools in Microsoft Excel when will learn about introduction to the statistical tools in Microsoft Excel, references, descriptive statistics, Central tendencies, mean, mode, and median the discovered of the three different parts.

Descriptive statistics that cover dispersion and standard deviation, data analysis tools, data analysis with the use of Central tendencies, correlation and regression, histograms in bar charts using data analysis, moving averages using data analysis, etc.

Under the module of machine learning which emphasis on statistical essentials one will learn about introduction to machine learning with the use of python, introduction to analytics with the use of machine learning, big data in machine learning, imaging trends in machine learning, data mining, supervisor unsupervised learning, basics of statistical sampling, sampling methods machine learning, technical terminology, the error of observation and nonobservation, systematic sampling, cluster sampling, different types of data, qualitative data and visualization, basics of statistics probability, relative frequency probability, joint probability, conditional probability, the concept of independence, basics of statistics random variables, probability distribution, cumulative probability distribution, basics of statistics distribution, geometric distribution, normal distribution, Matrix algebra, transpose of a matrix, properties of the matrix, mathematical expressions and computation, hypothesis testing, types of errors, critical value approach, p-value approach, confidence interval, types of hypothesis testing, normal and no normal distribution, normality test, t-test, a test of independence, regression, covariance, etc.

Under the module of statistics for data science using python, a participant would learn about introduction to data science, calculator mode, calculating dispersion means, basic techniques, testing methods, differences in NumPy packages, exclusive events, statistics for data science, analysis of test statistics, the output of the variables, best fit to the, etc.

Under this module of forecasting, a participant would learn about different forecasting tools and techniques that are used with the use of our language, predictive analysis, predictive analysis using SPSS, etc.

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