Description
Recent updatesJan 2023: EDA libraries (Klib, Sweetviz) that complete all the EDA activities with a few lines of code have been addedJan 2022: Conditional Scatter plots have been addedNov 2021: An exhaustive exercise covering all the possibilities of EDA has been added. Testimonials about the courseI found this course interesting and useful. Mr. Govind has tried to cover all important concepts in an effective manner. This course can be considered as an entry-level course for all machine learning enthusiasts. Thank you for sharing your knowledge with us. Dr. Raj Gaurav M. He is very clear. It's a perfect course for people doing ML based on data analysis. Dasika Sri Bhuvana V. This course gives you a good advice about how to understand your data, before start using it. Avoids that you create a bad model, just because the data wasn't cleaned. Ricardo VWelcome to the program on data analysis and exploratory data analysis! This program covers both basic as well as advanced data analysis concepts, analysis approaches, the associated programming, assignments and case studies: How to understand the relationship between variablesHow to identify the critical factor in dataDescriptive Statistics, Shape of distribution, Law of large numbersTime Series ForecastingRegression and ClassificationFull suite of Exploratory Data Analysis techniques including how to handle outliers, transform data, manage imbalanced datasetEDA libraries like Klib, SweetvizBuild a web application for exploratory data analysis using StreamlitProgramming Language UsedAll the analysis techniques are covered using python programming language. Python's popularity and ease of use makes it the perfect choice for data analysis and machine learning purposes. For the benefit of those who are new to python, we have added material related to python towards the end of the course. Course DeliveryThis course is designed by an AI and tech veteran and comes to you straight from the oven!
