Basic Syntax, Variables & Operations

Control Structures, Iterations and Ranges

Data Structures in Julia: Lists/Arrays, Tuples, Named Tuples

Dictionaries (Maps), Symbols in Julia

Arrays, Matrices, Tensors, Reshaping, Helper Functions

Data Type Details, Casting Among Types

Defining Functions, Overloading, Multiple – Dispatch

Anonymous Functions (and their importance), Splatting and Slurping

Functional Programming, Broadcasting – Most Important Concept in Julia

Interfacing with Python and R

Plotting Basics

Data Wrangling, Reading CSV Files, Descriptive Case Study

Further Data Manipulation, Apache Arrow, Grouping and analysis

Case Study: Clustering for Housing/Map Data

Classifications with Decision Tree/ Random Forests

Writing a Neural Network from scratch in a few lines

Multiple Layers, State-of-the-Art in a Few More Lines

Case Study: MNIST, Modifying Data for Model, Avoiding Pitfalls

MNIST Continued, Creating the Deep Model, Training and Testing

Saving and Loading Models, Exploring More Options

Where to Go from Here: Pointers for Further Learning