Instructor-led premium online courses
Premium scheduled courses led by experienced Julia programmers and teachers that help you learn, program and deploy Julia in production. Book your slot today.
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Customised training online or at your site
Modular customised courses for your organization tailored to your needs. Conducted online or at your premise.
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Learn from the best.
All of our instructors are experienced Julia Computing programmers and teachers
Prof. Alan Edelman
Professor of Computer Science and Applied Mathematics (MIT), Director of the Julia Lab at MIT, Co-Creator of Julia and Co-Founder and Chief Scientist of Julia Computing
Avik Sengupta
VP Engineering Julia Computing, MS Computational Finance (Carnegie Mellon), MBA (Indian Institute of Management-Bangalore)
Dr. Matt Bauman
Director of Applications Engineering at Julia Computing, PhD Bioengineering (University of Pittsburgh)
Introduction to Julia
- What problem(s) was Julia created to solve?
- What makes Julia so much faster, more productive and easier to learn?
- Getting started with Julia - Learn key differentiating programming paradigms of Julia
- Powerful type system, multiple dispatch, support for meta programming, first class mathematical libraries
- Begin programming in Julia
Introduction to Machine Learning and Artificial Intelligence
- Learn machine learning and artificial intelligence concepts
- Learn to leverage Julia’s superior speed, capacity and productivity to move from prototype to production quickly
- Write machine learning and artificial intelligence applications
- Understand concepts of deep learning to solve cutting edge applications like object recognition using Flux.jl
Parallel Computing in Julia
- Learn about graphics processing units (GPUs), tensor processing units (TPUs), multithreading, distributed computing and more
- Identify the challenges in converting a program from serial to parallel
- Discover the different forms of parallelism Julia offers and when to use each
- Learn how to structure programs to take advantage of parallel computation
- Write programs using each kind of parallelism
Each training can be customized to meet your needs. For example, we can use datasets, examples and case studies from your business or industry, we can modify the length and material covered, and we can modify the mode of instruction based on your requirements.
Most of our trainings use JuliaPro, our free download and fastest on-ramp to Julia for any developer.
Contact us for scheduling and pricing of customized courses for your organization online.
Our Julia experts conduct this three day workshop providing a hands-on in-depth exploration of the Julia language.
The course curriculum is designed with the objective of enabling beginner level programmers in getting up to speed with Julia, while also helping advanced programmers progress towards building highly successful applications using Julia.
The course introduces Julia language by covering topics like basic Julian syntax, efficient development setup, type system and multiple dispatch which makes Julia perform at C/Fortran speeds while still providing features of a high level language, and then moves on to more advanced topics like metaprogramming. The audience is expected to have basic understanding of high school math and basics of computer science.
For more information including pricing to organize this training for your organization or institution, contact us at [email protected].
The advanced training program is entirely customizable. With a hand-picked combination of basic, intermediate and advanced topics, these modules are tailored to your organization’s needs, including the number of days you want the workshop for.
For more information including pricing to organize this training for your organization or institution, contact us at [email protected].
This is a specially designed 3 day workshop that provides a thorough introduction to Artificial Intelligence and Machine Learning in Julia.
The training covers introduction to Julia, vector and array operations in Julia, followed by introductory machine learning techniques and applications. The course then takes a deep dive into introducing concepts of neural networks. This section involves engaging the learner with all sorts of AI applications, including handwriting recognition, object detection, language modeling and text generation.
The last day of the workshop proactively involves each and every student in building an application in Julia from scratch, with the students assuredly walking away feeling comfortable with machine learning and its underlying algorithms.
UNIVERSITIES TEACHING AND USING JULIA
