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Learning Path: Julia: Explore Data Science with Julia

Video Introducing this tutorial

Chapter 1 : Julia for Data Science
The Course Overview 00:02:41
Installing a Julia Working Environment 00:05:13
Working with Variables and Basic Types 00:08:07
Controlling the Flow 00:05:18
Using Functions 00:08:36
Using Tuples, Sets, and Dictionaries 00:05:54
Working with Matrices for Data Storage and Calculations 00:08:25
Using Types and Parameterized Methods 00:06:43
Optimizing Your Code by Using and Writing Macros 00:07:11
Organizing Your Code in Modules 00:06:26
Working with the Package Ecosystem 00:06:19
Reading and Writing Data Files and Julia Data 00:07:41
Using DataArrays and DataFrames 00:07:41
The Power of DataFrames 00:06:36
Interacting with Relational Databases Like SQL Server 00:07:21
Interacting with NoSQL Databases Like MongoDB 00:06:24
Exploring and Understanding a Dataset Statistically 00:06:38
An Overview of the Plotting Techniques in Julia 00:03:02
Visualizing Data with Scatterplots, Histograms, and Box Plots 00:04:24
Distributions and Hypothesis Testing 00:05:35
Interfacing with R 00:04:25
Basic Machine Learning Techniques 00:06:15
Classification Using Decision Trees and Rules 00:07:01
Training and Testing a Decision Tree Model 00:03:58
Applying a Generalized Linear Model with GLM 00:06:17
Working with Support Vector Machines 00:07:11


Chapter 2 : Julia Solutions
The Course Overview 00:05:03
Handling Data with CSV Files 00:06:29
Handling Data with TSV Files 00:03:33
Interacting with the Web 00:06:43
Representation of a Julia Program 00:06:38
Symbols 00:03:07
Quoting 00:03:32
Interpolation 00:03:49
The eval Function 00:03:25
Macros 00:04:31
Metaprogramming with DataFrames 00:07:57
Basic Statistics Concepts 00:05:15
Descriptive Statistics 00:07:04
Deviation Metrics 00:03:37
Sampling 00:06:28
Correlation Analysis 00:07:53
Dimensionality Reduction 00:05:09
Data Preprocessing 00:05:16
Linear Regression 00:03:20
Classification 00:03:20
Performance Evaluation and Model Selection 00:04:47
Cross Validation 00:03:29
Distances 00:04:35
Distributions 00:05:14
Time Series Analysis 00:01:36
Plotting Basic Arrays 00:06:22
Plotting DataFrames 00:05:12
Plotting Functions 00:05:32
Exploratory Data Analytics Through Plots 00:05:13
Line Plots 00:02:46
Scatter Plots 00:03:33
Histograms 00:03:45
Aesthetic Customizations 00:03:49
Basic Concepts of Parallel Computing 00:05:46
Data Movement 00:02:45
Parallel Maps and Loop Operations 00:03:25
Channels 00:02:09