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Julia Programming Language – Next Gen Data Science and Machine Learning

Video Introducing this tutorial
1. The Next Gen Language - Julia
2. Installing Julia (Windows, Linux and MacOS)
3. Packages and Interactive Notebook
4. Basic Syntax, Variables and Operations
5. Control Structures, Iterations and Ranges
6. Data Structures in Julia: Lists/Arrays, Tuples, Named Tuples
7. Dictionaries (Maps), Symbols in Julia
8. Arrays, Matrices, Tensors, Reshaping, Helper Functions
9. Data Type Details, Casting Among Types
10. Defining Functions, Overloading, Multiple-Dispatch
11. Anonymous Functions (and their importance), Splatting and Slurping
12. Functional Programming, Broadcasting - Most Important Concept in Julia
13. Interfacing with Python and R
14. Plotting Basics - Prettier Julia Plots
15. Data Wrangling, Reading CSV Files, Descriptive Case Study
16. Further Data Manipulation, Apache Arrow, Grouping and analysis
17. Case Study: Clustering for Housing/Map Data
18. Classification with Decision Trees/Random Forests
19. Writing a Neural Network from Scratch in a Few Lines
20. Multiple Layers, State-of-the-Art in a Few More Lines
21. Case Study: MNIST, Modifying Data for Model, Avoiding Pitfalls
22. MNIST Continued, Creating the Deep Model, Training and Testing
23. Saving and Loading Models, Exploring More Options
24. Where to Go from Here: Pointers for Further Learning