Designed with Inputs from Top Industry Professionals
Industry professionals from top tech companies guide our industry-aligned curriculum. Our curriculum is continually refreshed with the latest on big data technologies so that you never fall behind.
Introduction to Data Science and R programming
Data Science is an interdisciplinary field which is growing rapidly in response to the exponential amount of data to be captured and analyzed to solve the business requirement.In this module, you will understand both the basic concepts and advanced concepts of Data Analyst. In this session you will learn the basic overview of Data Science, Applications of Data Science evolution and scope of business analytics. Learn R, data manipulation and data visualizations in R.
Statistics and Data Exploration
Data Exploration in Statistics is an approach to analyze the data sets to summarize the characters with the visual methods. Get trained in Statistics Exploration in Statistics by understanding the various types and applications of Statistics. Master the art of making informed decisions by enhancing the key Statistical skills.
Random Variable and Normal Distribution and Hypothesis Testing
The statistical distribution is a data listing or function which shows all the possible data intervals. Get trained in Statistical and Mathematical skills to gain an edge over your peers by expertizing in the Normal Distribution and Hypothesis Testing.
Correlation and Regression
Correlation and Regression is implemented in finding the differences between the two variables. In this module, you will learn the various key concepts such as strength of linear association, applying correlation, least squares or regression line, regression line model. You will also master in advanced concepts such as multiple regression, regression diagnostics and detection of collinearity.
Model Creation and Selection
The Model Creation and Selection is a specific task of creating and selecting a statistical model. The most critical things such as interpretability, accuracy, simplicity, speed and scalability must be considered carefully before selecting the model. In this module, you will expertise in model fitting, diagnostics plot, model comparison, variable selection, cross variables and relative importance of Box-Cox transformations.
Logistic Regression is the appropriate predictive analysis Master Binary Response Regression and linear regression models are the results of proposed model. You will understand and work on the concepts such as linear probability model, logistic function, logistics regression and its interpretation, odds ratio, goodness of fit measures and confusion matrix.
Data Analytics and Visualization Tools
Big Data and the related technology wave are sweeping across all the industries. In this course, you will be mastering the following tools:
- The Data Analytic Tool, Excel allow users to analyze, manipulate data in an intuitive way.
- The Data Visualization tool, Tableau Desktop help users to present data to the right people at the right time to get an effective insights.