# Udemy - Introduction to Machine Learning for Data Science

#### Category: Tutorial

Posted on 2019-10-08, by phaelx.

Description

Date: March 2019

Author: David Valentine

Size: 3.5 GB

Format: MP4

Author: David Valentine

Size: 3.5 GB

Format: MP4

Download >> https://earn4files.com/lkjbbeht044b

What you'll learn

*Genuinely understand what Computer Science, Algorithms, Programming, Data, Big Data, Artificial Intelligence, Machine Learning, and Data Science is.

*To understand how these different domains fit together, how they are different, and how to avoid the marketing fluff.

*The Impacts Machine Learning and Data Science is having on society.

*To really understand computer technology has changed the world, with an appreciation of scale.

*To know what problems Machine Learning can solve, and how the Machine Learning Process works.

*How to avoid problems with Machine Learning, to successfully implement it without losing your mind!

Course content

Introduction

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

Conclusion

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Section 1 -Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Section 3 - Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Hands on Running Python

Section 4 - Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Hands on Running Python

Foundations of Machine Learning and Data Science - Definitions and concepts.

Foundations of Machine Learning and Data Science - Machine Learning Workflow

Foundations of Machine Learning and Data Science - Algorithms, concepts and more

Section 5 -Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Hands on Running Python

Foundations of Machine Learning and Data Science - Definitions and concepts.

Foundations of Machine Learning and Data Science - Machine Learning Workflow

Foundations of Machine Learning and Data Science - Algorithms, concepts and more

Introducing the essential modules for Machine Learning, and NumPy Basics

Pandas and Matplotlib

Analysis using Pandas, plotting in Matplotlib, intro to SciPy and Scikit-learn

Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Hands on Running Python

Foundations of Machine Learning and Data Science - Definitions and concepts.

Foundations of Machine Learning and Data Science - Machine Learning Workflow

Foundations of Machine Learning and Data Science - Algorithms, concepts and more

Introducing the essential modules for Machine Learning, and NumPy Basics

Pandas and Matplotlib

Analysis using Pandas, plotting in Matplotlib, intro to SciPy and Scikit-learn

A Titanic Example - Getting our start.

A Titanic Example - Understanding the data set.

A Titanic Example - Understanding the data set in regards to survival

A Titanic Example - Preparing the right data and applying a basic algorithm

A Titanic Example - Applying regression algorithms.

A Titanic Example - Applying Decision Trees (example of overfit and underfit)

Section 7 -Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Hands on Running Python

Foundations of Machine Learning and Data Science - Definitions and concepts.

Foundations of Machine Learning and Data Science - Machine Learning Workflow

Foundations of Machine Learning and Data Science - Algorithms, concepts and more

Introducing the essential modules for Machine Learning, and NumPy Basics

Pandas and Matplotlib

Analysis using Pandas, plotting in Matplotlib, intro to SciPy and Scikit-learn

A Titanic Example - Getting our start.

A Titanic Example - Understanding the data set.

A Titanic Example - Understanding the data set in regards to survival

A Titanic Example - Preparing the right data and applying a basic algorithm

A Titanic Example - Applying regression algorithms.

A Titanic Example - Applying Decision Trees (example of overfit and underfit)

Conclusions - for our Titanic Example, important concepts and where to go next!

Bonus Content

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Hands on Running Python

Foundations of Machine Learning and Data Science - Definitions and concepts.

Foundations of Machine Learning and Data Science - Machine Learning Workflow

Foundations of Machine Learning and Data Science - Algorithms, concepts and more

Introducing the essential modules for Machine Learning, and NumPy Basics

Pandas and Matplotlib

Analysis using Pandas, plotting in Matplotlib, intro to SciPy and Scikit-learn

A Titanic Example - Getting our start.

A Titanic Example - Understanding the data set.

A Titanic Example - Understanding the data set in regards to survival

A Titanic Example - Preparing the right data and applying a basic algorithm

A Titanic Example - Applying regression algorithms.

A Titanic Example - Applying Decision Trees (example of overfit and underfit)

Conclusions - for our Titanic Example, important concepts and where to go next!

Bonus Article - The startling breakthrough in Machine Learning from 2016.

*Genuinely understand what Computer Science, Algorithms, Programming, Data, Big Data, Artificial Intelligence, Machine Learning, and Data Science is.

*To understand how these different domains fit together, how they are different, and how to avoid the marketing fluff.

*The Impacts Machine Learning and Data Science is having on society.

*To really understand computer technology has changed the world, with an appreciation of scale.

*To know what problems Machine Learning can solve, and how the Machine Learning Process works.

*How to avoid problems with Machine Learning, to successfully implement it without losing your mind!

Course content

Introduction

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

Conclusion

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Section 1 -Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Section 3 - Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Hands on Running Python

Section 4 - Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Hands on Running Python

Foundations of Machine Learning and Data Science - Definitions and concepts.

Foundations of Machine Learning and Data Science - Machine Learning Workflow

Foundations of Machine Learning and Data Science - Algorithms, concepts and more

Section 5 -Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Hands on Running Python

Foundations of Machine Learning and Data Science - Definitions and concepts.

Foundations of Machine Learning and Data Science - Machine Learning Workflow

Foundations of Machine Learning and Data Science - Algorithms, concepts and more

Introducing the essential modules for Machine Learning, and NumPy Basics

Pandas and Matplotlib

Analysis using Pandas, plotting in Matplotlib, intro to SciPy and Scikit-learn

Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Hands on Running Python

Foundations of Machine Learning and Data Science - Definitions and concepts.

Foundations of Machine Learning and Data Science - Machine Learning Workflow

Foundations of Machine Learning and Data Science - Algorithms, concepts and more

Introducing the essential modules for Machine Learning, and NumPy Basics

Pandas and Matplotlib

Analysis using Pandas, plotting in Matplotlib, intro to SciPy and Scikit-learn

A Titanic Example - Getting our start.

A Titanic Example - Understanding the data set.

A Titanic Example - Understanding the data set in regards to survival

A Titanic Example - Preparing the right data and applying a basic algorithm

A Titanic Example - Applying regression algorithms.

A Titanic Example - Applying Decision Trees (example of overfit and underfit)

Section 7 -Bonus course - Machine Learning in Python and Jupyter for Beginners

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Hands on Running Python

Foundations of Machine Learning and Data Science - Definitions and concepts.

Foundations of Machine Learning and Data Science - Machine Learning Workflow

Foundations of Machine Learning and Data Science - Algorithms, concepts and more

Introducing the essential modules for Machine Learning, and NumPy Basics

Pandas and Matplotlib

Analysis using Pandas, plotting in Matplotlib, intro to SciPy and Scikit-learn

A Titanic Example - Getting our start.

A Titanic Example - Understanding the data set.

A Titanic Example - Understanding the data set in regards to survival

A Titanic Example - Preparing the right data and applying a basic algorithm

A Titanic Example - Applying regression algorithms.

A Titanic Example - Applying Decision Trees (example of overfit and underfit)

Conclusions - for our Titanic Example, important concepts and where to go next!

Bonus Content

Course Promotion Video

A special message for hard of hearing and ESL students

Thank you for investing in this Course!

Course Overview

Secret sauce inside!: How to get the most out of this course.

Core Concepts Overview

Computer Science - the `Train Wreck' Definition

What's Data / 'I can see data everywhere!'

Structured vs Unstructured Data

Structured and Unstructured Data

Computer Science - Definition Revisited & The Greatest 'lie' ever SOLD....

What's big data?

Big Data - Quiz

What is Artificial Intelligence (AI)

What is Machine Learning? - Part 1 - The ideas

What is Machine Learning? - Part 2 - An Example

What is data science?

Recap & How do these relate to each other?

Impacts, Importance and examples - Overview

Why is this important now?

Computers exploding! - The explosive growth of computer power explained.

What problems does Machine Learning Solve?

Where it's transforming our lives

The Machine Learning Process - Overview

5 Step Machine Learning Process Overview

1 - Asking the right question

2 - Identifying, obtaining, and preparing the right data

3 - Identifying and applying a ML Algorithm

4 - Evaluating the performance of the model and adjusting

5 - Using and presenting the model

Machine Learning - Process

How to apply Machine Learning for Data Science - Overview

Where to begin your journey

Common platforms and tools for Data Science

Data Science using - R

Data Science using - Python

Data Science using SQL

Data Science using Excel

Data Science using RapidMiner

Cautionary Tales

All done! What's next?

Introduction and Anaconda Installation

What will we cover!

Introduction and Setup

Crash course in Python - Beginning concepts

Crash course in Python - Strings, Slices and Lists!

Crash course in Python - Expressions, Operators, Conditions and Loops

Crash course in Python - Functions, Scope, Dictionaries and more!

Hands on Running Python

Foundations of Machine Learning and Data Science - Definitions and concepts.

Foundations of Machine Learning and Data Science - Machine Learning Workflow

Foundations of Machine Learning and Data Science - Algorithms, concepts and more

Introducing the essential modules for Machine Learning, and NumPy Basics

Pandas and Matplotlib

Analysis using Pandas, plotting in Matplotlib, intro to SciPy and Scikit-learn

A Titanic Example - Getting our start.

A Titanic Example - Understanding the data set.

A Titanic Example - Understanding the data set in regards to survival

A Titanic Example - Preparing the right data and applying a basic algorithm

A Titanic Example - Applying regression algorithms.

A Titanic Example - Applying Decision Trees (example of overfit and underfit)

Conclusions - for our Titanic Example, important concepts and where to go next!

Bonus Article - The startling breakthrough in Machine Learning from 2016.

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