#### Section 1 : Welcome and Logistics

 Lecture 1 Introduction and Outline copy 7:41 Lecture 2 Extra Resources 3:27

#### Section 2 : Numpy (New)

 Lecture 3 Numpy Section Introduction 5:28 Lecture 4 Arrays vs Lists 10:45 Lecture 5 Dot Product Lecture 6 Speed Test 2:55 Lecture 7 Matrices 14:45 Lecture 8 Solving Linear Systems 3:38 Lecture 9 Generating Data 14:32 Lecture 10 Numpy Exercise 1:5 Lecture 11 Where to Learn More Numpy 6:55 Lecture 12 Suggestion Box 2:27

#### Section 3 : Matplotlib (New)

 Lecture 13 Matplotlib Section Introduction 2:39 Lecture 14 Line Chart 3:50 Lecture 15 Scatterplot Lecture 16 Histogram 2:26 Lecture 17 Plotting Images 7:40 Lecture 18 Matplotlib Exercise 1:39 Lecture 19 Where to Learn More Matplotlib 13:10

#### Section 4 : Pandas (New)

 Lecture 20 Pandas Section Introduction 1:17 Lecture 21 Loading in Data 3:52 Lecture 22 Selecting Rows and Columns 9:48 Lecture 23 The apply() Function 2:32 Lecture 24 Plotting with Pandas 2:46 Lecture 25 Pandas Exercise 2:10 Lecture 26 Where to Learn More Pandas 4:24

#### Section 5 : Scipy (New)

 Lecture 27 Scipy Section Introduction 1:25 Lecture 28 PDF and CDF 3:6 Lecture 29 Convolution 4:34 Lecture 30 Scipy Exercise 1:3 Lecture 31 Where to Learn More Scipy 7:47

#### Section 6 : Bonus Exercises

 Lecture 32 More Exercises 8:55

#### Section 7 : Machine Learning Basics

 Lecture 33 Machine Learning Section Introduction 7:47 Lecture 34 What is Classification 12:22 Lecture 35 Classification in Code 14:38 Lecture 36 What is Regression 12:13 Lecture 37 Regression in Code 8:29 Lecture 38 What is a Feature Vector 6:49 Lecture 39 Machine Learning is Nothing but Geometry 4:50 Lecture 40 All Data is the Same 5:23 Lecture 41 Comparing Different Machine Learning Models Lecture 42 Machine Learning and Deep Learning Future Topics 5:55 Lecture 43 Machine Learning Section Summary

#### Section 8 : Setting Up Your Environment (FAQ by Student Request)

 Lecture 44 Windows-Focused Environment Setup 2018 20:20 Lecture 45 How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow

#### Section 9 : Extra Help With Python Coding for Beginners (FAQ by Student Request)

 Lecture 46 Python 2 vs Python 3 4:38 Lecture 47 Proof that using Jupyter Notebook is the same as not using it 12:29

#### Section 10 : Effective Learning Strategies for Machine Learning (FAQ by Student Request)

 Lecture 48 Machine Learning and AI Prerequisite Roadmap (pt 1) 11:19 Lecture 49 Machine Learning and AI Prerequisite Roadmap (pt 2) 16:7