Business Analytics with MS Excel
Business Analytics with MS Excel Certification training is designed to boost your Data analytics career with the new powerful Microsoft Excel skills. The course drives you with the basic concepts of data analysis and statistics, that helps in promoting data-driven decision making. This will make you skilled in Power BI, enabling to visually represent better and present, your data analysis findings. This Business Analytics with MS Excel Training will equip you with all the concepts and skills required for a strong career in Data analytics.
Below are the learning objectives of Business Analytics with MS Excel Certification:
- On Successful completion of the Business Analytics with Excel Certification course, the participants will get:
- Understanding of basic statistical concepts and types of data.
- Understanding of data sampling techniques.
- Understanding of frequency distributions and measures of central tendency, dispersion and shape.
- Knowledge of the one-way analysis of variance and correlation.
- Knowledge of linear regression and linear programming.
- Knowledge on Optimizing business situations that involve whole numbers, such as employees to deploy.
- Knowledge on Optimizing business decisions that take multiple input variables to predict between two possible outputs.
- Understanding of Model decisions under a variety of future uncertain states, depending on the decision maker’s proneness or aversion to risks.
- Compute the regression model for time series data that has correlation within itself.
- Optimize business situations where two variables do not move in a linear fashion.
- Test hypothesis for experiments involving different treatments.
- Model continuous outcomes that depend on more than one input variable.
- Group data points dynamically based on the similarities among the members of each group.
- Master a data mining concept i.e. is combining the data from different sources, cleansing the data and preparing the data for analytics.
- Understand how to use statistical techniques in real time scenario.
- Complete understanding of predictive modeling concepts.
- Learn how to build a complex statistical model, how to test it and how to deploy it.