The best way to learn Python! But what makes ArrivingSkills.AI different? All our tuition and training products are tailored to exactly what you need.

• Complete beginner? No problem, we don’t skip the basics. And we provide a syllabus tailored to exactly what you need to achieve your learning goals.
• Need to accelerate skill learning after mastering the basics? We do that.
• How about learning specialist Python skills, such as advanced syntax, third party packages for web and data science? No problem.
• We also provide refresher and catch up tuition, which is always popular with students at all levels who feel they are falling behind on classes.

Our tuition is geared towards learning how to apply Python code to produce real applications. Endless theory doesn’t not exist here. We offer patient tuition that can help anyone learn Python at the pace they need.

Code has never been important in and of itself. The single most important part of software development is delivering value to those who need our programs.

Many forms of code have (almost) died out over the years. Machine code and assembly language used be the norm. Now they are rare for coding. We have evolved to higher levels of abstraction when telling computers what to do, and the tools to do this support more efficient delivery of value.

In the 1980s the 4th Generation Language was going to become the best way to allow non-technical people to deliver value with software. But despite claims to the contrary theses 4GLs as they were known (where would we be without another acronym?) never achieved their lofty, albeit relevant goals.

This is the backdrop against which we should evaluate LLMs and other AI tools. We are now closer than ever to being able to program in natural language. Sure, there are intermediate products as the software is prepared to be executed on a computer, that includes translation to a programming language (Python, Java etc.) And this is the identical model to when languages like COBOL, Java and others replace machine code. It’s still there; we just don’t need to see it.

Now, while that isn’t quite true with LLM / AI generated code yet, it is now closer than it has ever been. The pace at which it becomes viable is accelerating rapidly. What is possible now was thought impossible even 6 months ago.

It’s time to stop pretending that LLMs and AI are a fad and don’t work. Now is the time to learn and embrace using them.

The major challenge with LLMs and AI at present is how do the ever increasing costs of tokens impact the ability to deliver value wit this technology.