Business Analytics in Malaysia

Inferential Statistics is the study to evaluate results for a population using a subset of data. The assumptions made for business problems are analyzed using Inferential Statistics. Learn various Hypothesis Tests to solve business problems. Using a simple mathematical formula, the equation of a line, you can predict an outcome. Understand the art of improvising the results of Prediction Models.

Line Assumptions are the prerequisite and post requisites for developing a Regression Model. As part of this module learn to deal with conditions that may arise while developing a Prediction Model. Understand the different regression techniques, like Logistic Regression and Poisson Regression, etc., used for discrete data.

Descriptive Analytics analyses historical data and can explain scenarios that happened in the past. The information generated from this preliminary analysis is subjected to Data Mining techniques to obtain the desired results. Understand the different mathematical approaches for Descriptive and Predictive Analysis as part of this Data Mining module.

Learn to predict categorical data using Classifier Techniques. In the industry, the classification techniques are predominantly used to solve prediction problems. You will learn these popular techniques and the math behind these algorithms. Learn to analyze the unstructured text data by extracting features from the data. Apply probability-based classification techniques to predict outcomes using text data.

Deep Learning techniques are based on Black Box techniques. As part of this module, you will learn the most commonly used Deep Learning Algorithms. Learn how to deal with unstructured data, the art of developing a Neural Network and the different types of Neural Networks. Support Vector Machine is a kernel-based technique to classify the non-linear data in multidimensional spaces. Understand how time-series data is different from the regular data, learn to interpret the effects of time on the data. You will learn methods used to perform forecasting on time series data.

Reporting is an essential stage of Data Analytics. You will learn the most famous business intelligence tool Tableau and its capabilities. Learn the Data Visualization rules and differentiate a good visualization from a bad visualization.

Learn to tell stories on data using graphs and plots. Learn how Tableau can be used to tell patterns and anomalies in the data. Learn the features like parameters, filters, Quick Table calculations, sets, etc., to segregate the data.

Learn how to use Calculated Fields in Tableau to customize and create new attributes. Tableau Maps feature which is a unique feature will automatically help to define stories using world maps. You will learn to add customized maps and background images for creating customized visual information. Learn to use dashboards and stories using multiple worksheets in sequence and create a story on business data.