Data Science and Machine Learning Basic to Advanced

Complete Introduction to Data Science and Machine Learning from Basic to Advanced.

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Last Updated: 2022-11-25 10:11:56 English Course Type: Self Learning

Students will develop understanding of libraries used for Data Analysis like Pandas and Numpy.
Learn to create impactful visualizations using Matplotlib and Seaborn. By creating these visualizations you will be able to derive better conclusions from data.
After this course you will learn to build complete Data Science Pipeline from Data preparation to building the best Machine Learning Model.
The course contains practical section after every new concept discussed and the course also has two projects at the end.

Learn how to use Numpy and Pandas for Data Analysis. This will cover all basic concepts of Numpy and Pandas that are useful in data analysis.
Learn to create impactful visualizations using Matplotlib and Seaborn. Creating impactful visualizations is a crucial step in developing a better understanding about your data.
This course covers all Data Preprocessing steps like working with missing values, Feature Encoding and Feature Scaling.
Learn about different Machine Learning Models like Random Forest, Decision Trees, KNN, SVM, Linear Regression, Logistic regression etc... All the video sessions will first discuss the basic theoretical concept behind these algorithms followed by the practical implementation.
Learn to how to choose the best hyperparameters for your Machine Learning Model using GridSearch CV. Choosing the best hyperparameters is an important step in increasing the accuracy of your Machine Learning Model.
You will learn to build a complete Machine Learning Pipeline from Data collection to Data Preprocessing to Model Building. ML Pipeline is an important concept that is extensively used while building large-scale ML projects.
This course has two projects at the end that will be built using all concepts taught in this course. The first project is about Diabetes Prediction using a classification machine learning algorithm and the second is about predicting the insurance premium using a regression machine learning algorithm.

Basic understanding of Python Programming Language.Anyone who is looking to start his or her Data Science and Machine Learning Journey. People who are at intermediate level and already have some basic understanding of Data Science will also find this course helpful.

Basic understanding of Python Programming Language.

Section 1 : Welcome and Course Overview 2 Lectures 00:08:05
Lecture 1 :
Welcome Preview
Lecture 2 :
Course Overview
Section 2 : Numpy 7 Lectures 00:59:53
Lecture 1 :
Numpy Introduction and Installation
Lecture 2 :
Creating Arrays in Numpy
Lecture 3 :
Array Shape and Reshape
Lecture 4 :
Array Indexing
Lecture 5 :
Array Iterating
Lecture 6 :
Array Slicing
Lecture 7 :
Searching and Sorting
Section 3 : Pandas 5 Lectures 00:19:43
Lecture 1 :
Pandas Introduction and Installation
Lecture 2 :
Pandas Series
Lecture 3 :
Pandas dataframe
Lecture 4 :
ReadCSV Pandas
Lecture 5 :
Analyzing data frames
Section 4 : Data Visualization 3 Lectures 00:25:47
Lecture 1 :
Matplotlib Introduction
Lecture 2 :
Different type of plots in Matplotlib
Lecture 3 :
Seaborn
Section 5 : Data Preparation 3 Lectures 00:28:00
Lecture 1 :
Handling Missing Values
Lecture 2 :
Feature Encoding
Lecture 3 :
Feature Scaling
Section 6 : Machine Learning 13 Lectures 01:51:06
Lecture 1 :
Machine Learning Introduction
Lecture 2 :
Supervised machine learning
Lecture 3 :
Unsupervised machine learning
Lecture 4 :
Train Test Split
Lecture 5 :
Regression Analysis
Lecture 6 :
Linear Regression
Lecture 7 :
Logistic Regression
Lecture 8 :
KNN
Lecture 9 :
SVM
Lecture 10 :
Decision Tree
Lecture 11 :
Random Forest
Lecture 12 :
K Means Clustering
Lecture 13 :
Grid Search CV
Section 7 : Machine Learning Pipeline 1 Lectures 00:09:36
Lecture 1 :
Machine Learning Pipeline
Section 8 : Projects 2 Lectures 00:00:01
Lecture 1 :
Diabetes Prediction
Lecture 2 :
Insurance Cost Prediction

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Raj Chhabria,

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1 Courses

My name is Raj Chhabria and I am a Computer Science Engineer with specialization in Data Science. I am an accomplished coder and programmer, and I enjoy using my skills to contribute to student community by my Udemy Courses. Here on this platform I intend to share my knowledge in most condensed form through my courses.