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Development Data Science Machine Learning

Python for Data Science and Machine Learning Bootcamp

Learn how to use NumPy, Pandas, Seaborn , Matplotlib , Plotly , Scikit-Learn , Machine Learning, Tensorflow , and more!
Rating: 4.6 out of 54.6 (96,500 ratings)
431,214 students
Created by Jose Portilla
Last updated 5/2020
English
English, French [Auto], 
30-Day Money-Back Guarantee

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
Curated for the Udemy for Business collection

Course content

27 sections • 165 lectures • 24h 54m total length

  • Preview03:33
  • Preview00:36
  • Course FAQs
    03:02

  • Preview11:14

  • Updates to Notebook Zip
    00:09
  • Jupyter Notebooks
    13:48
  • Optional: Virtual Environments
    09:51

  • Welcome to the Python Crash Course Section!
    00:17
  • Introduction to Python Crash Course
    01:26
  • Python Crash Course - Part 1
    19:29
  • Python Crash Course - Part 2
    15:14
  • Python Crash Course - Part 3
    16:39
  • Python Crash Course - Part 4
    15:37
  • Python Crash Course Exercises - Overview
    03:35
  • Python Crash Course Exercises - Solutions
    11:56

  • Welcome to the NumPy Section!
    00:10
  • Introduction to Numpy
    02:12
  • Numpy Arrays
    16:49
  • Quick Note on Array Indexing
    00:48
  • Numpy Array Indexing
    18:23
  • Numpy Operations
    07:04
  • Numpy Exercises Overview
    02:46
  • Numpy Exercises Solutions
    15:31

  • Welcome to the Pandas Section!
    00:14
  • Introduction to Pandas
    01:44
  • Series
    10:39
  • DataFrames - Part 1
    15:31
  • DataFrames - Part 2
    17:10
  • DataFrames - Part 3
    09:12
  • Missing Data
    06:19
  • Groupby
    06:48
  • Merging Joining and Concatenating
    08:55
  • Operations
    12:04
  • Data Input and Output
    14:00

  • Note on SF Salary Exercise
    00:22
  • SF Salaries Exercise Overview
    01:55
  • SF Salaries Solutions
    15:25
  • Ecommerce Purchases Exercise Overview
    02:11
  • Ecommerce Purchases Exercise Solutions
    15:12

  • Preview00:22
  • Introduction to Matplotlib
    Preview03:02
  • Matplotlib Part 1
    16:57
  • Matplotlib Part 2
    15:51
  • Matplotlib Part 3
    11:51
  • Matplotlib Exercises Overview
    01:46
  • Matplotlib Exercises - Solutions
    10:19

  • Introduction to Seaborn
    02:58
  • Distribution Plots
    Preview18:20
  • Categorical Plots
    17:17
  • Matrix Plots
    10:14
  • Grids
    08:30
  • Regression Plots
    07:13
  • Style and Color
    08:21
  • Seaborn Exercise Overview
    01:53
  • Seaborn Exercise Solutions
    07:08

  • Pandas Built-in Data Visualization
    13:27
  • Pandas Data Visualization Exercise
    01:22
  • Pandas Data Visualization Exercise- Solutions
    08:55

Requirements

  • Some programming experience
  • Admin permissions to download files

Description

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!


Who this course is for:

  • This course is meant for people with at least some programming experience

Featured review

Jerry Morrow
Jerry Morrow
1 course
1 review
Rating: 5.0 out of 55 months ago
This was my first course in Udemy, and with this instructor. This was an excellent first class to jump into the world of data science. All of the explanations were clear, and you can tell the instructor truly cares about software education. It covers all the most important topics in machine learning, and gives just enough theoretical knowledge to have some basic understanding of the algorithms behind the scenes. I'm already using some of the knowledge learned (and practiced!) here at work.

Instructor

Jose Portilla
Head of Data Science, Pierian Data Inc.
Jose Portilla
  • 4.6 Instructor Rating
  • 720,351 Reviews
  • 2,204,076 Students
  • 32 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 and programming. He has publications and patents in various fields such as microfluidics, materials science, and data science technologies. 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, as well as present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Data Inc. 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 contact him on LinkedIn for more information on in-person training sessions or group training sessions in Las Vegas, NV.

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