Python for Data Science and Machine Learning Bootcamp

About Course

Learn **Python for Data Science and Machine Learning** with this comprehensive **free** bootcamp from Udemy. This course is designed for both beginners with some programming experience and experienced developers looking to transition into data science. Master key concepts like Python programming, data visualization, and machine learning using popular libraries like NumPy, pandas, Matplotlib, and Scikit-learn.

This course is a perfect alternative to expensive data science bootcamps, covering a wide range of topics including:

Python Programming Fundamentals
NumPy for Numerical Computing
Data Manipulation with pandas DataFrames
Working with Excel Files using pandas
Web Scraping Techniques
Connecting Python to SQL Databases
Data Visualization using matplotlib and seaborn
Interactive Data Visualization with plotly
Machine Learning with Scikit-learn:
- Linear Regression
- K Nearest Neighbors
- K Means Clustering
- Decision Trees
- Random Forests
- Natural Language Processing
- Neural Networks and Deep Learning
- Support Vector Machines

Enroll now and embark on your journey to becoming a data scientist!

Use Python for Data Science and Machine Learning
Use Spark for Big Data Analysis
Implement Machine Learning Algorithms
Learn to use NumPy for Numerical Data
Learn to use Pandas for Data Analysis
Learn to use Matplotlib for Python Plotting
Learn to use Seaborn for statistical plots
Use Plotly for interactive dynamic visualizations
Use SciKit-Learn for Machine Learning Tasks
K-Means Clustering
Logistic Regression
Linear Regression
Random Forest and Decision Trees
Natural Language Processing and Spam Filters
Neural Networks
Support Vector Machines

Course Content

01. Course Introduction

A Message from the Professor
002. Course Help and Welcome.mp4

00:00
003. Course FAQs.html

00:00

02. Environment Set-Up

03. Jupyter Overview

04. Python Crash Course

001. Welcome to the Python Crash Course Section!.mp4

00:00
002. Introduction to Python Crash Course.mp4

00:00
003. Python Crash Course – Part 1.mp4

00:00
004. Python Crash Course – Part 2.mp4

00:00
005. Python Crash Course – Part 3.mp4

00:00
006. Python Crash Course – Part 4.mp4

00:00
007. Python Crash Course Exercises – Overview.mp4

00:00
008. Python Crash Course Exercises – Solutions.mp4

00:00
Section Quiz

05. Python for Data Analysis – NumPy

001. Welcome to the NumPy Section!.mp4

00:00
002. Introduction to Numpy.mp4

00:00
003. Numpy Arrays.mp4

00:00
004. Quick Note on Array Indexing.html

00:00
005. Numpy Array Indexing.mp4

00:00
006. Numpy Operations.mp4

00:00
007. Numpy Exercises Overview.mp4

00:00
008. Numpy Exercises Solutions.mp4

00:00
Section Quiz

06. Python for Data Analysis – Pandas

001. Welcome to the Pandas Section!.mp4

00:00
002. Introduction to Pandas.mp4

00:00
003. Series.mp4

00:00
004. DataFrames – Part 1.mp4

00:00
005. DataFrames – Part 2.mp4

00:00
006. DataFrames – Part 3.mp4

00:00
007. Missing Data.mp4

00:00
008. Groupby.mp4

00:00
009. Merging Joining and Concatenating.mp4

00:00
010. Operations.mp4

00:00
011. Data Input and Output.mp4

00:00
Section Quiz

07. Python for Data Analysis – Pandas Exercises

08. Python for Data Visualization – Matplotlib

09. Python for Data Visualization – Seaborn

001. Introduction to Seaborn.mp4

00:00
002. Distribution Plots.mp4

00:00
003. Categorical Plots.mp4

00:00
004. Matrix Plots.mp4

00:00
005. Grids.mp4

00:00
006. Regression Plots.mp4

00:00
007. Style and Color.mp4

00:00
008. Seaborn Exercise Overview.mp4

00:00
009. Seaborn Exercise Solutions.mp4

00:00
Section Quiz

10. Python for Data Visualization – Pandas Built-in Data Visualization

11. Python for Data Visualization – Plotly and Cufflinks

12. Python for Data Visualization – Geographical Plotting

13. Data Capstone Project

001. Welcome to the Data Capstone Projects!.mp4

00:00
002. 911 Calls Project Overview.mp4

00:00
003. 911 Calls Solutions – Part 1.mp4

00:00
004. 911 Calls Solutions – Part 2.mp4

00:00
005. Bank Data.html

00:00
006. Finance Data Project Overview.mp4

00:00
007. Finance Project – Solutions Part 1.mp4

00:00
008. Finance Project – Solutions Part 2.mp4

00:00
009. Finance Project – Solutions Part 3.mp4

00:00
Section Quiz

14. Introduction to Machine Learning

15. Linear Regression

16. Cross Validation and Bias-Variance Trade-Off

17. Logistic Regression

18. K Nearest Neighbors

19. Decision Trees and Random Forests

20. Support Vector Machines

21. K Means Clustering

22. Principal Component Analysis

23. Recommender Systems

24. Natural Language Processing

25. Neural Nets and Deep Learning

001. Download TensorFlow Notebooks Here.html

00:00
002. Quick Check for Notes.html

00:00
003. Welcome to the Deep Learning Section!.mp4

00:00
004. Introduction to Artificial Neural Networks (ANN).mp4

00:00
005. Installing Tensorflow.html

00:00
006. Perceptron Model.mp4

00:00
007. Neural Networks.mp4

00:00
008. Activation Functions.mp4

00:00
009. Multi-Class Classification Considerations.mp4

00:00
010. Cost Functions and Gradient Descent.mp4

00:00
011. Backpropagation.mp4

00:00
012. TensorFlow vs Keras.mp4

00:00
013. TF Syntax Basics – Part One – Preparing the Data.mp4

00:00
014. TF Syntax Basics – Part Two – Creating and Training the Model.mp4

00:00
015. TF Syntax Basics – Part Three – Model Evaluation.mp4

00:00
016. TF Regression Code Along – Exploratory Data Analysis.mp4

00:00
017. TF Regression Code Along – Exploratory Data Analysis – Continued.mp4

00:00
018. TF Regression Code Along – Data Preprocessing and Creating a Model.mp4

00:00
019. TF Regression Code Along – Model Evaluation and Predictions.mp4

00:00
020. TF Classification Code Along – EDA and Preprocessing.mp4

00:00
021. TF Classification – Dealing with Overfitting and Evaluation.mp4

00:00
022. TensorFlow 2.0 Project Options Overview.mp4

00:00
023. TensorFlow 2.0 Project Notebook Overview.mp4

00:00
024. Keras Project Solutions – Dealing with Missing Data.mp4

00:00
025. Keras Project Solutions – Dealing with Missing Data – Part Two.mp4

00:00
026. Keras Project Solutions – Categorical Data.mp4

00:00
027. Keras Project Solutions – Data PreProcessing.mp4

00:00
028. Keras Project Solutions – Data PreProcessing.mp4

00:00
029. Keras Project Solutions – Creating and Training a Model.mp4

00:00
030. Keras Project Solutions – Model Evaluation.mp4

00:00
031. Tensorboard.mp4

00:00
Section Quiz

26. Big Data and Spark with Python

001. Welcome to the Big Data Section!.mp4

00:00
002. Big Data Overview.mp4

00:00
003. Spark Overview.mp4

00:00
004. Local Spark Set-Up.html

00:00
005. AWS Account Set-Up.mp4

00:00
006. Quick Note on AWS Security.html

00:00
007. EC2 Instance Set-Up.mp4

00:00
008. SSH with Mac or Linux.mp4

00:00
009. PySpark Setup.mp4

00:00
010. Lambda Expressions Review.mp4

00:00
011. Introduction to Spark and Python.mp4

00:00
012. RDD Transformations and Actions.mp4

00:00
Section Quiz

27. BONUS SECTION THANK YOU!

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About Course

What Will You Learn?

Course Content

01. Course Introduction

A Message from the Professor

002. Course Help and Welcome.mp4

003. Course FAQs.html

02. Environment Set-Up

001. Python Environment Setup.mp4

Section Quiz

03. Jupyter Overview

002. Jupyter Notebooks.mp4

003. Optional Virtual Environments.mp4

Section Quiz

04. Python Crash Course

001. Welcome to the Python Crash Course Section!.mp4

002. Introduction to Python Crash Course.mp4

003. Python Crash Course – Part 1.mp4

004. Python Crash Course – Part 2.mp4

005. Python Crash Course – Part 3.mp4

006. Python Crash Course – Part 4.mp4

007. Python Crash Course Exercises – Overview.mp4

008. Python Crash Course Exercises – Solutions.mp4

Section Quiz

05. Python for Data Analysis – NumPy

001. Welcome to the NumPy Section!.mp4

002. Introduction to Numpy.mp4

003. Numpy Arrays.mp4

004. Quick Note on Array Indexing.html

005. Numpy Array Indexing.mp4

006. Numpy Operations.mp4

007. Numpy Exercises Overview.mp4

008. Numpy Exercises Solutions.mp4

Section Quiz

06. Python for Data Analysis – Pandas

001. Welcome to the Pandas Section!.mp4

002. Introduction to Pandas.mp4

003. Series.mp4

004. DataFrames – Part 1.mp4

005. DataFrames – Part 2.mp4

006. DataFrames – Part 3.mp4

007. Missing Data.mp4

008. Groupby.mp4

009. Merging Joining and Concatenating.mp4

010. Operations.mp4

011. Data Input and Output.mp4

Section Quiz

07. Python for Data Analysis – Pandas Exercises

001. Note on SF Salary Exercise.html

002. SF Salaries Exercise Overview.mp4

003. SF Salaries Solutions.mp4

004. Ecommerce Purchases Exercise Overview.mp4

005. Ecommerce Purchases Exercise Solutions.mp4

Section Quiz

08. Python for Data Visualization – Matplotlib

001. Welcome to the Data Visualization Section!.mp4

002. Introduction to Matplotlib.mp4

003. Matplotlib Part 1.mp4

004. Matplotlib Part 2.mp4

005. Matplotlib Part 3.mp4

006. Matplotlib Exercises Overview.mp4

007. Matplotlib Exercises – Solutions.mp4

Section Quiz

09. Python for Data Visualization – Seaborn

001. Introduction to Seaborn.mp4

002. Distribution Plots.mp4

003. Categorical Plots.mp4

004. Matrix Plots.mp4

005. Grids.mp4

006. Regression Plots.mp4

007. Style and Color.mp4

008. Seaborn Exercise Overview.mp4

009. Seaborn Exercise Solutions.mp4

Section Quiz

10. Python for Data Visualization – Pandas Built-in Data Visualization

001. Pandas Built-in Data Visualization.mp4

002. Pandas Data Visualization Exercise.mp4

003. Pandas Data Visualization Exercise- Solutions.mp4

Section Quiz

11. Python for Data Visualization – Plotly and Cufflinks