DETAILED CURRICULUM : MODULES
Introduction to Python Programming
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Overview of Python
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History of Python
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Python Basics – variables, identifiers, indentation
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Data Structures in Python (list, string, sets, tuples, dictionary)
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Statements in Python (conditional, iterative, jump)
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OOPS concepts
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Exception Handling
Regular Expression
Introduction to various packages and related functions
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Numpy, Pandas and Matplotlib
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Pandas Module
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Series
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Data Frames
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Numpy Module
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Numpy arrays
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Numpy operations
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Matplotlib module
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Plotting information
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Bar Charts and Histogram
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Box and Whisker Plots
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Heatmap
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Scatter Plots
Data Wrangling using Python
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NumPy – Arrays
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Data Operations (Selection , Append , Concat , Joins)
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Univariate Analysis
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Multivariate Analysis
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Handling Missing Values
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Handling Outliers
Introduction to Machine Learning with Python
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What is Machine Learning?
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Introduction to Machine Learning
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Types of Machine Learning
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Basic Probability required for Machine Learning
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Linear Algebra required for Machine Learning
Supervised Learning - Regression
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Simple Linear Regression
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Multiple Linear Regression
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Assumptions of Linear Regression
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Polynomial Regression
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R2 and RMSE
Supervised Learning – Classification
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Logistic Regression
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Decision Trees
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Random Forests
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SVM
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Naïve Bayes
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Confusion Matrix