Description

Do you want to learn:

How to teach a self-driving car to navigate a highway?

How to detect objects, emotions and colors in videos?

How to restore images with code?

Build the next big machine learning app!

Learn how to:

build machine learning projects

add machine learning and data science to your resume

This bundle:

does not assume any level of experience

is perfect for beginners

THE COMPLETE SOURCE CODE WILL BE AVAILABLE.

No math or programming experience necessary.

Learn how to code in Python.

Build and run your first Python projects.

Think like a Python developer.

Learn how to use popular Python libraries:

NumPy - fundamental package for scientific computing in Python

Matplotlib’s Pyplot - data visualization with plots, graphs and charts

Pandas - fast, powerful, flexible and easy to use data analysis and manipulation tool

Learn machine learning and artificial intelligence from scratch.

Learn how machine learning can solve problems in all disciplines.

Learn how to build a machine learning program.

Take your skills to the next level by building a huge range of models.

Build regression and classification models

Build artificial intelligence search algorithms

Build a full portfolio with practical machine learning projects.

Use Tensorflow 2.0 and Keras to build fun beginner projects.

Classify images, species of plants and more.

Dive into deep learning and master highly desirable skills.

Add projects to your resume in no time.

Learn a hireable skill and powerful technology

Help businesses find customer trends, leverage data to cut costs, and much more.

Requirements

No programming or machine learning experience needed - We’ll teach you everything you need to know.

A Mac, PC or Linux computer.

We’ll walk you through, step-by-step how to get all the software installed and set up

The only course you need to learn Machine Learning. With over 50,000 reviews, our courses are some of the HIGHEST RATED courses online!

This masterclass is without a doubt the most comprehensive course available anywhere online. Even if you have zero experience, this course will take you from beginner to professional.

• 1. Python Introduction
  • 00. Introduction

    4:48

  • 01. Intro To Python

    5:46

• 2. Code Python on the Web
  • 02.01 What is Google Colab

    4:25

  • 02.02 What If I Get Errors

    2:40

  • 02.03 How Do I Terminate a Session

    2:40

• 3. Python Language Fundamentals: Learn Python from Scratch
  • 01. Variables

    19:20

  • 02. Type Conversion Examples

    10:07

  • 03. Operators

    28:54

  • 04. Collections

    8:25

  • 05. List Examples

    19:41

  • 06. Tuples Examples

    8:37

  • 07. Dictionaries Examples

    14:27

  • 08. Ranges Examples

    8:32

  • 09. Conditionals

    6:44

  • 10. If Statement Examples

    21:32

  • 11. Loops

    29:42

  • 12. Functions

    17:02

  • 13. Parameters And Return Values Examples

    13:55

  • 14. Classes And Objects

    34:12

  • 15. Inheritance Examples

    17:29

  • 16. Static Members Examples

    11:06

  • 17. Summary And Outro

    4:09

• 4. Data Visualization with Python and Matplotlib
  • 00. Course Intro

    5:31

  • 01. Intro To Pyplot

    5:11

  • 02. Installing Matplotlib

    5:52

  • 03. Basic Line Plot

    7:54

  • 04. Customizing Graphs

    10:47

  • 05. Plotting Multiple Datasets

    8:11

  • 06. Bar Chart

    6:26

  • 07. Pie Chart

    9:14

  • 08. Histogram

    10:15

  • 09. 3D Plotting

    6:29

  • 10. Course Outro

    4:09

• 5. Beginners Data Analysis with Pandas
  • 00. Panda Course Introduction

    5:44

  • 01. Intro To Pandas

    7:55

  • 02. Installing Pandas

    5:28

  • 03. Creating Pandas Series

    20:34

  • 04. Date Ranges

    11:29

  • 05. Getting Elements From Series

    19:21

  • 06. Getting Properties Of Series

    13:04

  • 07. Modifying Series

    19:02

  • 08. Operations On Series

    11:49

  • 09. Creating Pandas Dataframes

    22:57

  • 10. Getting Elements From Dataframes

    25:12

  • 11. Getting Properties From Dataframes

    17:44

  • 12. Dataframe Modification

    36:24

  • 13. Dataframe Operations

    20:10

  • 14 Dataframe Comparisons And Iteration

    15:35

  • 15. Reading CSVs

    12:00

  • 16. Summary And Outro

    4:15

• 6. Data Mining with Python! Real-Life Data Science Exercises
  • Introduction to Data Mining

    9:31

• 7. 2-1 Data Wrangling - A Complete Overview
  • Data Wrangling Demystified

    1:03:56

• 8. 2-2 Data Mining Fundamentals
  • 01. Cluster Analysis

    20:08

  • 02. Classification and Regression

    34:31

  • 03. Association and Correlation

    13:10

  • 04. Dimensionality Reduction

    25:39

• 9. 2-3 Frameworks Explained - Taming Big Data with Spark
  • 01. Apache Spark - An Overview Of The Framework

    26:36

  • 02. Spark Key Functions

    20:27

  • 03. Spark Machine Learning

    7:32

  • 04. EXAMPLES - Using The Machine Learning Pipeline

    6:17

• 10. 2-4 EXAMPLES - Mining and Storing Data
  • 01. Text Mining

    15:06

  • 02. Network Mining

    10:12

  • 03. Matrix

    7:17

  • 04. SQL

    12:36

• 11. 2-5 NLP (Natural Language Processing)
  • 01 NLP Data Cleaning

    6:55

  • 02. Count Vectorizer

    7:58

  • 03. NLP Example with Spam

    9:59

  • 04. Tweak Model with Spam Data

    5:33

  • 05. Pipeline with Spam Data

    4:48

• 12. 2-6 Conclusion and Summary
  • 06. Conclusion and Challenge

    4:40

• 13. PySpark - Build DataFrames with Python, Apache Spark and SQL
  • 00 Project Preview

    2:34

  • 02 What Are Resilient Distributed Datasets

    1:08

  • 01 What Is Apache Spark

    2:37

  • 03A What Is A Dataframe

    1:47

  • 03B What You'll Need

    1:47

• 14. PySpark - Build DataFrames from Spreadsheets
  • 04 Start A Spark Session

    3:48

  • 05 Load Data As A CSV

    6:02

  • 06 Perform Basic Dataframe Operations

    4:02

  • 07 Format Dataframe Table

    5:14

  • 08 Perform Dataframe Math Operations

    7:32

  • 09 Perform Dataframe Queries

    14:23

  • 10 Build SQL Queries With Spark

    7:24

• 15. Python Data Analysis Bootcamp with Pandas and NLTK
  • 00 Project Preview

    3:38

  • 01 Convert CSV File To A Python List

    13:50

  • 02 Tokenize Text Data

    26:25

  • 03 Find Most Popular Lemmatized Words

    11:36

  • 04 Build Dataframes Per Part Of Speech

    3:56

  • 05 Plot Word Frequency

    9:10

• 16. Exploratory Data Analysis Bootcamp with Python, Seaborn and Pandas
  • 00 Project Preview

    4:04

  • 01 Load A Dataset

    9:43

  • 02 Analyze The Main Feature

    2:47

  • 03 Analyze Numerical Features

    7:26

  • 04 Analyze Categorical Features

    9:33

• 17. Visualize - Exploratory Data Analysis Bootcamp with Python, Seaborn and Pandas
  • 01 Find Relationships Between Numerical Features

    11:27

  • 02 Find Relationships Between Categorical Features

    7:52

  • 03 Build Conditional Plots

    7:04

• 18. Overview - Introduction to Databases with Python SQL
  • 00 Course Overview

    2:16

  • 01 What You'll Need

    3:13

• 19. 01 Introduction to data
  • 01 Why You Must Know How To Work With Data

    5:22

• 20. 02 Entity Relationship Modeling (ERM)
  • 01 How To Read An ER Model

    5:32

• 21. 03 Introduction to databases and relational databases
  • 01 What Is A Database

    8:27

  • 02 What Is A Relational Database

    4:33

• 22. 04 How to build an organized database
  • 01 How To Design Columns And Data Types

    3:14

  • 02 Use Normal Forms To Check Your Design

    7:16

• 23. 05 Build a SQLite database with Python
  • 01 Build A Sqlite Database With Python

    8:02

  • 02 Add An Entry To The Table With SQL

    6:45

  • 03 Add More Records To The Table

    6:30

  • 04 Build A Second Table For Cross-Referencing

    10:57

  • 05 Select Rows That Meet Conditions

    7:15

• 24. Feature Analysis and Data Science with Stocks for Beginners
  • Course Overview

    3:51

  • 01 Load And Create Data

    9:55

  • 02 Perform Exploratory Data Analysis

    3:42

  • 03 Visualize Data With Different Plots

    11:07

  • 04 Analyze Features With More Plots

    6:18

  • 05 Build Plots With Seaborn

    4:35

  • 06 Build A Bokeh Plot

    6:17

  • 07 Build A 3D Scatter Plot

    3:46

  • 08 Rank Feature Importance

    7:13

  • 09 Compare Positive And Negative Returns

    8:07

• 25. The Definitive Python Time Series Analysis Masterclass
  • 00 Project Preview

    3:03

  • 01 Load Crypto Prices Dataset

    10:29

  • 02 Visualize Bitcoin Price Trend

    4:54

  • 03 Predict Price With Facebook Prophet

    6:23

  • 04 Analyze Model Performance

    9:38

  • 05 Visualize Model Results

    3:58

  • 06 Predict Monthly Trend

    9:28

  • 07 Predict Weekly Trend

    5:36

  • 08 Compare Final Stock Price Of Different Strategies

    6:23

• 26. 1). Stock Market Data Analysis and Visualization
  • 00 Project Preview

    3:17

  • 01 Fetch Stock Data

    9:13

  • 02 Visualize Stock Data Features

    7:32

  • 03 Calculate Daily Return

    3:28

  • 04 Compare Returns Of Different Stocks

    10:45

  • 05 Compare Closing Prices

    8:48

• 27. 2). Stock Market Data Analysis and Visualization
  • 01 Visualize Standard Deviation And Expected Returns

    5:45

  • 02 Calculate Value At Risk

    3:53

  • 03 Monte Carlo Analysis To Estimate Risk

    9:11

  • 04 Visualize Price Distribution

    9:07

• 28. Scrape the Web - Python and Beautiful Soup Bootcamp
  • 00 What Is Web Scraping

    5:39

  • 01 What You'll Need

    1:30

  • 02 Build An Html Webpage To Scrape

    12:42

  • 03 Select Data Structures From A Webpage

    5:48

  • 04 Extract URLsAnd Text

    5:25

  • 05 Work With Tags

    8:07

  • 06 Work With Attributes

    5:19

  • 07 Add Navigation To A String

    5:29

  • 08 Navigate Html Contents

    7:16

  • 09 Find All Filter

    4:52

• 29. Build Interactive Python Dashboards with Plotly and Dash
  • 01 Project Preview

    1:40

  • 02 What Is Plotly And Dash

    3:59

  • 03 What You'll Need

    2:10

  • 1-01 Build A Dash App

    11:44

  • 1-02 Build A Graph In The Dash App

    12:05

  • 2-01 Load Data From Vega Datasets

    5:34

  • 2-02 Build The Layout

    10:27

  • 2-03 Build A Chart With Altair

    11:56

• 30. Data Mining with Python and NumPy - Build a Video Recommender System
  • 00 Project Preview

    2:48

  • 01 Build A Dataset

    23:45

  • 02 Compute Support And Confidence - If A Person Watches X, They Will Watch Y

    10:06

  • 03 Compute Support And Confidence For All Channels

    14:21

  • 04 Determine Which Videos Are Best To Recommend

    9:58