Python Data Science And Machine Learning Made Easy

What you'll learn
What is Data Science?
Why Python for Data Science?
Setting Up Your Environment (Jupyter Notebook, Anaconda, VSCode)
Exploring Datasets (Head, Tail, Describe, Info)
Introduction to Matplotlib and Seaborn
Customizing Plots (Labels, Colors, Themes)
Creating Visual Stories With Data
Summary Statistics & Data Distributions
Descriptive vs Inferential Statistics
Confidence Intervals and P-Values
Mini-Quizzes & Practice Problems
What is Machine Learning?
Linear Regression with Scikit-Learn
Logistic Regression
k-Nearest Neighbors
Decision Trees and Random Forest
Model Accuracy, Confusion Matrix, ROC Curves
Web Scraping With BeautifulSoup and Requests and more....
Requirements
No coding experience required
Description
Unlock the power of Python Data Science and Machine Learning and transform your data into actionable insights. This course is designed for beginners, aspiring data scientists, and developers who want to gain practical, hands-on experience in one of the fastest-growing fields in technology.You will start by learning the fundamentals of Python programming and how it applies to data science. Key concepts such as data types, loops, functions, and libraries will be introduced, giving you a solid foundation for more advanced topics in Machine Learning.You will dive into data manipulation and analysis using Python's powerful libraries such as Pandas and NumPy. You'll learn how to clean, organize, and explore data efficiently, preparing it for machine learning workflows and real-world applications.The course then covers Machine Learning concepts, including supervised and unsupervised learning, regression, classification, clustering, and model evaluation. You'll understand how to build predictive models and make data-driven decisions using Python.Throughout the course, you will gain practical skills including:Working with Python for data analysis and visualizationCleaning and preparing datasets for machine learningBuilding and evaluating machine learning modelsApplying algorithms such as regression, classification, and clusteringVisualizing insights using Python libraries like Matplotlib and SeabornBy the end of this course, you will be able to confidently apply Python Data Science and Machine Learning techniques to real-world problems. You'll know how to turn raw data into meaningful insights, create predictive models, and present your findings effectively.This course is perfect for:Beginners looking to enter the field of data science and machine learningDevelopers and analysts wanting to enhance their Python skillsStudents preparing for data science roles or competitionsAnyone interested in leveraging Python for data-driven decision-makingEnroll now to Master Python Data Science and Machine Learning, real-world examples, and hands-on exercises that will prepare you for a career in data science.
Anyone interested in leveraging Python for data-driven decision-making,Students preparing for data science roles or competitions,Beginners looking to enter the field of data science and machine learning,Developers and analysts wanting to enhance their Python skills
Homepage

https://www.udemy.com/course/python-data-science-and-machine-learning-made-easy/

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