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DevelopmentData SciencePython

2022 Python for Machine Learning & Data Science Masterclass

Learn about Data Science and Machine Learning with Python! Including Numpy, Pandas, Matplotlib, Scikit-Learn and more!
Rating: 4.7 out of 54.7 (8,108 ratings)
66,309 students
Created by Jose Portilla
Last updated 9/2021
English
English [Auto], Dutch [Auto], 

What you'll learn

  • You will learn how to use data science and machine learning with Python.
  • You will create data pipeline workflows to analyze, visualize, and gain insights from data.
  • You will build a portfolio of data science projects with real world data.
  • You will be able to analyze your own data sets and gain insights through data science.
  • Master critical data science skills.
  • Understand Machine Learning from top to bottom.
  • Replicate real-world situations and data reports.
  • Learn NumPy for numerical processing with Python.
  • Conduct feature engineering on real world case studies.
  • Learn Pandas for data manipulation with Python.
  • Create supervised machine learning algorithms to predict classes.
  • Learn Matplotlib to create fully customized data visualizations with Python.
  • Create regression machine learning algorithms for predicting continuous values.
  • Learn Seaborn to create beautiful statistical plots with Python.
  • Construct a modern portfolio of data science and machine learning resume projects.
  • Learn how to use Scikit-learn to apply powerful machine learning algorithms.
  • Get set-up quickly with the Anaconda data science stack environment.
  • Learn best practices for real-world data sets.
  • Understand the full product workflow for the machine learning lifecycle.
  • Explore how to deploy your machine learning models as interactive APIs.

Requirements

  • Basic Python Knowledge (capable of functions)

Description

This is the most complete course online for learning about Python, Data Science, and Machine Learning. Join Jose Portilla's over 2.6 million students to learn about the future today!

What is in the course?

Welcome to the most complete course on learning Data Science and Machine Learning on the internet! After teaching over 2 million students I've worked for over a year to put together what I believe to be the best way to go from zero to hero for data science and machine learning in Python!

This course is designed for the student who already knows some Python and is ready to dive deeper into using those Python skills for Data Science and Machine Learning. The typical starting salary for a data scientists can be over $150,000 dollars, and we've created this course to help guide students to learning a set of skills to make them extremely hirable in today's workplace environment.

We'll cover everything you need to know for the full data science and machine learning tech stack required at the world's top companies. Our students have gotten jobs at McKinsey, Facebook, Amazon, Google, Apple, Asana, and other top tech companies! We've structured the course using our experience teaching both online and in-person to deliver a clear and structured approach that will guide you through understanding not just how to use data science and machine learning libraries, but why we use them. This course is balanced between practical real world case studies and mathematical theory behind the machine learning algorithms.

We cover advanced machine learning algorithms that most other courses don't! Including advanced regularization methods and state of the art unsupervised learning methods, such as DBSCAN.

This comprehensive course is designed to be on par with Bootcamps that usually cost thousands of dollars and includes the following topics:

  • Programming with Python

  • NumPy with Python

  • Deep dive into Pandas for Data Analysis

  • Full understanding of Matplotlib Programming Library

  • Deep dive into seaborn for data visualizations

  • Machine Learning with SciKit Learn, including:

    • Linear Regression

    • Regularization

    • Lasso Regression

    • Ridge Regression

    • Elastic Net

    • K Nearest Neighbors

    • K Means Clustering

    • Decision Trees

    • Random Forests

    • Natural Language Processing

    • Support Vector Machines

    • Hierarchal Clustering

    • DBSCAN

    • PCA

    • Model Deployment

    • and much, much more!


As always, we're grateful for the chance to teach you data science, machine learning, and python and hope you will join us inside the course to boost your skillset!


-Jose and Pierian Data Inc. Team

Who this course is for:

  • Beginner Python developers curious about Machine Learning and Data Science with Python

Featured review

Eric Esajian
Eric E.
56 courses
30 reviews
Rating: 5.0 out of 5a year ago
Jose is pro, and has perfected online teaching. I've taken basically all his courses, and I am never disappointed. He is thorough, clear, and concise in his teaching and this course is no different. Every Python course he puts out on Udemy, I will continue to take! Thanks, Eric

Instructor

Jose Portilla
Head of Data Science at Pierian Training
Jose Portilla
  • 4.6 Instructor Rating
  • 912,935 Reviews
  • 2,906,179 Students
  • 52 Courses

Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science, Machine Learning and Python Programming. He has publications and patents in various fields such as microfluidics, materials science, and data science. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming, the ability to analyze data, and the skills needed to present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Training and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, The New York Times, Credit Suisse, McKinsey and many more. Feel free to check out the website link to find out more information about training offerings.

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