Section 1 : Introduction
Lecture 1 Course Promotion Video copy 00:01:52 Duration
Lecture 2 A special message for hard of hearing and ESL students 00:00:58 Duration
Lecture 3 Thank you for investing in this Course! 00:00:45 Duration
Lecture 4 Course Overview 00:03:03 Duration
Lecture 5 Secret sauce inside! How to get the most out of this course 00:05:20 Duration
Lecture 6 Course Survey 00:04:07 Duration

Section 2 : Core Concepts
Lecture 1 Core Concepts Overview 00:01:20 Duration
Lecture 2 Computer Science - the `Train Wreck' Definition 00:00:54 Duration
Lecture 3 What's Data I can see data everywhere! 00:05:34 Duration
Lecture 4 Structured vs Unstructured Data 00:02:45 Duration
Lecture 5 Computer Science - Definition Revisited & The Greatest lie ever SOLD 00:11:03 Duration
Lecture 6 What's big data 00:06:40 Duration
Lecture 7 What is Artificial Intelligence (AI) 00:11:58 Duration
Lecture 8 What is Machine Learning - Part 1 - The ideas
Lecture 9 What is Machine Learning - Part 2 - An Example 00:06:49 Duration
Lecture 10 What is data science 00:05:06 Duration
Lecture 11 Recap & How do these relate to each other 00:03:28 Duration

Section 3 : Impacts, Importance and examples
Lecture 1 Impacts, Importance and examples - Overview 00:00:44 Duration
Lecture 2 Why is this important now
Lecture 3 Computers exploding! - The explosive growth of computer power explained 00:13:24 Duration
Lecture 4 What problems does Machine Learning Solve 00:04:29 Duration
Lecture 5 Where it's transforming our lives 00:09:16 Duration

Section 4 : The Machine Learning Process
Lecture 1 The Machine Learning Process - Overview 00:01:15 Duration
Lecture 2 Machine Learning Process Overview 00:01:54 Duration
Lecture 3 Asking the right question 00:02:49 Duration
Lecture 4 Identifying, obtaining, and preparing the right data 00:11:22 Duration
Lecture 5 Identifying and applying a ML Algorithm 00:11:09 Duration
Lecture 6 Evaluating the performance of the model and adjusting 00:04:05 Duration
Lecture 7 Using and presenting the model 00:01:58 Duration

Section 5 : How to apply Machine Learning for Data Science
Lecture 1 How to apply Machine Learning for Data Science - Overview 00:00:32 Duration
Lecture 2 Where to begin your journey 00:00:58 Duration
Lecture 3 Common platforms and tools for Data Science 00:01:57 Duration
Lecture 4 Data Science using - R 00:01:58 Duration
Lecture 5 Data Science using - Python 00:02:27 Duration
Lecture 6 Data Science using SQL 00:01:50 Duration
Lecture 7 Data Science using Excel
Lecture 8 Data Science using RapidMiner 00:01:11 Duration
Lecture 9 Cautionary Tales 00:01:46 Duration

Section 6 : Conclusion
Lecture 1 All done! What's next 00:00:41 Duration

Section 7 : Section 1 -Bonus course - Machine Learning in Python and Jupyter for Beginners
Lecture 1 Introduction and Anaconda Installation 00:04:52 Duration
Lecture 2 What will we cover! 00:06:13 Duration
Lecture 3 Introduction and Setup 00:08:18 Duration

Section 8 : Section 2 -Bonus course - Machine Learning in Python and Jupyter for Beginners
Lecture 1 Crash course in Python - Beginning concepts 00:06:07 Duration
Lecture 2 Crash course in Python - Strings, Slices and Lists! 00:07:04 Duration
Lecture 3 Crash course in Python - Expressions, Operators, Conditions and Loops
Lecture 4 Crash course in Python - Functions, Scope, Dictionaries and more! 00:05:26 Duration

Section 9 : Section 3 - Bonus course - Machine Learning in Python and Jupyter for Beginners
Lecture 1 Hands on Running Python 00:10:49 Duration

Section 10 : Section 4 - Bonus course - Machine Learning in Python and Jupyter for Beginners
Lecture 1 Foundations of Machine Learning and Data Science 00:05:38 Duration
Lecture 2 Foundations of Machine Learning and Data Science 00:05:09 Duration
Lecture 3 Foundations of Machine Learning and Data Science 00:07:09 Duration

Section 11 : Section 5 -Bonus course - Machine Learning in Python and Jupyter for Beginners
Lecture 1 Introducing the essential modules for Machine Learning, and NumPy Basics 00:07:17 Duration
Lecture 2 Pandas and Matplotlib 00:09:44 Duration
Lecture 3 Analysis using Pandas, plotting in Matplotlib 00:05:25 Duration

Section 12 : Section 6 - Bonus course - Machine Learning in Python and Jupyter for Beginners
Lecture 1 A Titanic Example - Getting our start 00:09:33 Duration
Lecture 2 A Titanic Example - Understanding the data set 00:11:26 Duration
Lecture 3 A Titanic Example - Understanding the data set in regards to survival 00:08:55 Duration
Lecture 4 A Titanic Example - Preparing the right data 00:12:57 Duration
Lecture 5 A Titanic Example - Applying regression algorithms
Lecture 6 A Titanic Example - Applying Decision Trees 00:06:00 Duration

Section 13 : Section 7 -Bonus course - Machine Learning in Python and Jupyter for Beginners
Lecture 1 Conclusions - for our Titanic Example, 00:06:06 Duration

Section 14 : Bonus Content
Lecture 1 Bonus Article - The startling breakthrough in Machine Learning from 2016