Programming with Julia

Do you want to learn data science, machine learning, deep learning, and AI but you are not sure about the programming language to learn?

Or you may be using Python and R, but you are tired of their low speed.

Julia is a modern programming language developed for data science, machine learning and AI. It is a dynamically typed language which is easy to learn and use and has the speed of C.

This is the first of a series of courses I plan to teach data science, machine learning and deep learning using Julia. Other courses, "Data Science with Julia", "Machine Learning with Julia" and "Deep Learning with Julia" will follow. In this course, you will learn programming in Julia proficiently. In the upcoming courses you will learn both machine learning and deep learning algorithms and how to build those algorithms from scratch using Julia.

Besides being ideal for data science and machine learning, Julia is also ideal for production environments. Being one of the most modern languages, Julia can be used to build entire applications and microservices.

Julia combines best features of dynamic languages like Python and R and low-level languages like C, C# and Java. You can develop a machine learning model or an algorithm in Julia and use that code in a production environment. You don't have to use different languages for development and production.

The only prerequisite is the motivation of learning.,No programming experience is required.,A computer running Windows, MAC or Linux.

• 10 hours on-demand video
• 10 articles
• 6 downloadable resources
• Access on mobile and TV
• Full lifetime access
• Certificate of completion

1. This course gives a very good and comprehensive overview over starting in Julia. The instructor goes into enough detail to get some good understanding of how Julia works and what makes it different to other languages. But it's not overwhelming details.
2. I would have wished for some exercies for the more advanced lectures as well not just the first basic ones, that is why i substracted half a star.
3. Simply put, the best introductory course that I found in Julia. It covers the most important parts of the program in detail but takes sufficient time to explain them properly. Highly recommend for those planning to start the Julia journey.
4. The course quite good, especially for beginners. However, some parts wasn't explained clearly. I couldn't cover metaprogramming. The last section @btime used but not explained what it was.
5. Also, debugging, environment variable of julia maybe communication with C or Java can be explained. Let me know if some new chapters are added, please.
6. Excellent introductory course to Julia.
7. Very informative.
8. I'm looking forward to the next data science classes with Julia.