Udemy

Python for Data Science and Machine Learning Bootcamp

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  • 798,577 Students
  • Updated 5/2020
4.6
(156,242 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Language
English
Taught by
Jose Portilla, Pierian Training
Rating
4.6
(156,242 Ratings)
1 views

Course Overview

Python for Data Science and Machine Learning Bootcamp

Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more!

Are you ready to start your path to becoming a Data Scientist! 

This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!

Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world's most interesting problems!

This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!

This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! With over 100 HD video lectures and detailed code notebooks for every lecture this is one of the most comprehensive course for data science and machine learning on Udemy!

We'll teach you how to program with Python, how to create amazing data visualizations, and how to use Machine Learning with Python! Here a just a few of the topics we will be learning:

  • Programming with Python
  • NumPy with Python
  • Using pandas Data Frames to solve complex tasks
  • Use pandas to handle Excel Files
  • Web scraping with python
  • Connect Python to SQL
  • Use matplotlib and seaborn for data visualizations
  • Use plotly for interactive visualizations
  • Machine Learning with SciKit Learn, including:
  • Linear Regression
  • K Nearest Neighbors
  • K Means Clustering
  • Decision Trees
  • Random Forests
  • Natural Language Processing
  • Neural Nets and Deep Learning
  • Support Vector Machines
  • and much, much more!

Enroll in the course and become a data scientist today!


Course Content

  • 10 section(s)
  • 165 lecture(s)
  • Section 1 Course Introduction
  • Section 2 Environment Set-Up
  • Section 3 Jupyter Overview
  • Section 4 Python Crash Course
  • Section 5 Python for Data Analysis - NumPy
  • Section 6 Python for Data Analysis - Pandas
  • Section 7 Python for Data Analysis - Pandas Exercises
  • Section 8 Python for Data Visualization - Matplotlib
  • Section 9 Python for Data Visualization - Seaborn
  • Section 10 Python for Data Visualization - Pandas Built-in Data Visualization

What You’ll Learn

  • 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


Reviews

  • A
    Aditya Suhas Munde
    5.0

    It's a great platform to learn . Skills make a person thoughtfull and gain practicle knowledge . In the modern era of python and Ai automation one can learn this and visualize the data.

  • A
    Arth Gameti
    5.0

    this course taught me many things about python, Data Science and machine learning if you r thinking to buy you can go for it with any doubt , Totally worth it

  • M
    Martha Elena Estrada Palafox
    4.0

    I think some topics as spark should be re making since a lot has change in these years. Despite this, I've learned so much

  • A
    Aditya Tongse
    5.0

    Great explanation and how you highlight the real enterprise environment is priceless.

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