This course includes a structured approach of handling the data related projects for maximizing the success rate. Learn about insights on how data is assisting organizations to make informed data-driven decisions. Data is treated as the new oil for all the industries and sectors which keep organizations ahead in the competition. Learn the application of Big Data Analytics in real-time, you will understand the need for analytics with a use case. Also, learn about the best project management methodology for Data Mining - CRISP-DM at a high level.

• Learners will understand about Project management methodology - CRISP-DM, in handling Data Science projects or Artificial Intelligence projects end to end.

• Learn about all the 6 stages including Business Understanding, Data Understanding, Data Preparation, Data Modeling, Model Evaluation and finally Model Deployment.

• Learn about Data Collection, Data Cleansing, Data Preparation, Data Munging, Data Wrapping, etc.

• Learn about the preliminary steps taken to churn the data, known as exploratory data analysis. In this module, you also are introduced to statistical calculations which are used to derive information from data. We will begin to understand how to perform a descriptive analysis.

• Learn about continuous probability distribution. Understand the properties of a continuous random variable and its distribution under normal conditions. To identify the properties of a continuous random variable, statisticians have defined a variable as a standard, learning the properties of the standard variable and its distribution. You will learn to check if a continuous random variable is following normal distribution using a normal Q-Q plot.

• Learn the science behind the estimation of value for a population using sample data.