This course introduces basic concepts of data science, data exploration, preparation in Python and then prepares you to participate in exciting machine learning competitions on Analytics Vidhya.
Introduction to Python for Data AnalysisFree
This chapter will get you started with Python for Data Analysis. We will cover the reasons to learn Data Science using Python, provide an overview of the Python ecosystem and get you to write your first code in Python!
Python Libraries and data structuresFree
In this chapter, we will introduce some of the most common data structures in Python to you and take you through some of the libraries we commonly use in data analysis.
Exploratory analysis in Python using PandasFree
We start with the first step of data analysis - the exploratory data analysis.
Data Munging in Python using PandasFree
Pandas is at the heart of data analysis in Python. This chapter gets you started with Data Munging in Python using Pandas
Building a Predictive model in PythonFree
We build our predictive models and make submissions to the AV DataHack platform in this section.First Step of Model Building50 xpLabel categories of Gender to number100 xpSelecting the right algorithm50 xpHave you performed data preprocessing step?50 xpLogistic Regression Introduction100 xpBuild your first logistic regression model100 xpPrediction and submission to DataHack100 xpDecision Tree Introduction100 xpTrain model and do prediction using Decision Tree100 xpRandom Forest Introduction100 xpTrain model and do prediction using Random Forest100 xpSelecting important variables for model building50 xp
Expert advice to improve model performanceFree
This chapter will help to understand the approach of data science experts, "How they do approach a challenge?", "How to select a right algorithm?", "How to combine outputs of multiple algorithms?" and "How to select the right value of model parameter also known as parameter tuning?".How to approach a challenge?50 xpFeature Engineering50 xpFeature Selection50 xpHow to select the right value of model parameter?50 xpUse ensemble methods to combine output of more than one models?50 xpCross validtion helps to improve your score on out of sample data set50 xpiPython / Jupyter notebook for Predictive Modeling50 xpThank You & Further studies50 xp