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Course Description:

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Data science is a "concept to unify statistics, data analysis, informatics, and their related methods" in order to "understand and analyze actual phenomena" with data.
Machine learning (ML) is the study of computer algorithms that improve automatically through experience and by the use of data.

Introduction to Data Science

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• What is Data Science?
• Need of Data Science
• Applications of Data Science
• Libraries used in Data Science

NumPy Library

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• Introduction to NumPy Library
• Creating NumPy Arrays
• Numpy Array Indexing
• Numpy Array Slicing
• Numpy Array Operations

Pandas Library

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• Introduction to Pandas Library
• Creating Series
• Accessing Series
• Creating DataFrames
• Accessing DataFrames
• Adding and Removing Rows in DataFrame
• Adding and Removing Columns in DataFrame
• Working with Missing Values in DataFrame
• Iterating elements of DataFrame
• Descriptive statistics in DataFrame
• Creating DataFrame from CSV file
• Writing DataFrame data into a CSV file

Matplotlib Library

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• Matplotlib Library
• Introduction to Matplotlib Library
• Creating a Line Plot
• Formatting a Line Plot
• Creating a Bar Plot
• Formatting a Bar Plot
• Creating a Scatter Plot
• Formatting a Scatter Plot
• Creating a Histogram Plot
• Formatting a Histogram Plot
• Creating a Box Plot
• Formatting a Box Plot
• Creating a Pie Plot
• Formatting a Pie Plot

Seaborn Library

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• Introduction to Seaborn Library
• Distribution Plots
• Categorical Plots
• Matrix Plots
• Grids
• Regression Plots
• Styling and Coloring Plots

Introduction to Machine Learning

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• What is Machine Learning?
• Need of Machine Learning
• History of Machine Learning
• Applications of Machine Learning
• Libraries used in Machine Learning
• Types of Machine Learning Algorithm

Supervised Machine Learning Algorithms

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Linear Regression Algorithm

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• Linear Regression Algorithm Concept
• Linear Regression Algorithm Program Implementation

Logistic Regression Algorithm

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• Logistic Regression Algorithm Concept
• Logistic Regression Algorithm Program Implementation

Logistic Regression Algorithm

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• Logistic Regression Algorithm Concept
• Logistic Regression Algorithm Program Implementation

KNN Algorithm

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• KNN Algorithm Concept
• KNN Algorithm Program Implementation

Naive Bayes Algorithm

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• Naive Bayes Algorithm Concept
• Naive Bayes Algorithm Implementation

Decision Tree Algorithm

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• Decision Tree Algorithm Concept
• Decision Tree Algorithm Program Implementation

Random Forest Algorithm

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• Random Forest Algorithm Concept
• Random Forest Algorithm Program Implementation

Support Vector Machine Algorithm

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• Support Vector Algorithm Concept
• Support Vector Algorithm Program Implementation

Unsupervised Machine Learning Algorithms

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• K-Means Algorithm
• K-Means Algorithm Concept
• K-Means Algorithm Program Implementation

Advance Concept

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• ANN Algorithm
• ANN Algorithm Concept
• ANN Algorithm Program Implementation

Project Work

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