Written By Jennifer Inglis
Edited By Jess Feldman
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Course Report strives to create the most trust-worthy content about coding bootcamps. Read more about Course Report’s Editorial Policy and How We Make Money.
With the steep increase in the use of AI in all facets of tech, including software development, sales, or marketing, tools like ChatGPT, Github CoPilot, and Llama 3.1 are reshaping the way developers create and program software and solve problems. In fact, it’s estimated that by 2030, the adoption of AI will add $15.7 trillion to the global economy, and 70% of businesses will have integrated some form of AI into their operations. While we have a few years left before then, having a handle on some current AI tools will give you a leg-up in finding a tech job, as it will open the doors to your chosen industry and position yourself as a “go-to” person in a cutting-edge field.
Even if you have no plans to specialize in artificial intelligence, learning AI tools as a software engineer is valuable, as most industries have integrated AI into their processes. Routine data extraction and analysis may now be handled by AI, freeing engineers and developers to focus on more creative, innovative tasks. Learning AI can safeguard your tech career, as you’ll have the skills necessary to be at the forefront of whatever is coming next, whether it’s as a designer, programmer, or thought leader.
WebXR Developer & Coding Temple graduate Lee points out that, "[AI] makes things faster, especially with the 3D work. I use ChatGPT to get the basics of a component and I’ll make it work with Typescript. Aktïga also hooked me up with Github Copilot and it’s a game-changer! Sometimes I want to turn it off when it autocompletes a filter and I want to test myself to remember the syntax, but overall it speeds things up so much."
So how can understanding AI tools as a software engineer help you?
It helps you become a more efficient (and innovative) engineer. AI automates many routine tasks (such as debugging, testing, and code generation), which streamlines and reduces tedious work. This allows engineers to focus on more creative and strategic aspects of software development.
You can work on a wider range of projects, such as natural language processing, robotics, or data science.
AI can support your work by decreasing the chances of human errors and detecting issues before they become a problem, improving the overall user experience and improving client satisfaction.
As the demand for AI skills grows, more companies want to hire engineers who know how to incorporate AI into their products and processes to support productivity, creativity, and innovation. If you know AI, it makes you much more competitive in an already competitive job market!
The number of AI tools in the market is swiftly growing, but these three AI tools are widely used and can help you nail your first tech interview.
ChatGPT is an AI “chatbot” developed by OpenAI that’s designed to have a “conversation” with users. It’s meant to mimic natural human dialogue and is being used as a search engine, to create content, translate languages, and solve mathematical equations, among many others. “GPT” is an acronym for generative pre-trained transformer, which means it’s designed to spot patterns and make decisions based on the information it’s given.
Software engineers should learn ChatGPT because:
Software engineers can use ChatGPT in their day-to-day job by using it to perform research and delegate routine tasks such as identifying bugs, adding comments to created code, identifying weak spots in the code, and generating basic code on which they can expand.
Keep in mind, though, that even with the use of AI tools such as ChatGPT, the role of the software engineer isn't going away anytime soon. As Software Engineer & Coding Temple grad Nate says, “Overall [ChatGPT] does an extremely good job if you ask it to perform a specific task. ChatGPT can produce code, but often there will still be small errors that I have to actually look at and think about as a human.”
How is ChatGPT used in the real world?
ChatGPT can be used in the deployment of software solutions, which require detailed preparation, forethought, and implementation. ChatGPT can help facilitate this implementation by creating automated code as well as supplying other critical services such as support and cloud deployment. This means having an extra layer of assurance that an engineer’s solutions are error-free and on time. ChatGPT can also assist with deploying solutions on the cloud and integrating several systems into one cohesive platform.
GitHub CoPilot is an AI coding assistant that helps a software engineer do their job more easily and efficiently, allowing more time for problem-solving, collaboration, and innovation. It differs from ChatGPT in that it’s more useful for coding, whereas ChatGPT can perform tasks like content creation and NLP (natural language processing) functions that are beyond GitHub CoPilot’s scope. It’s used by software engineers (such as Software Engineer & Springboard grad Kevin) to:
Software engineers should learn GitHub CoPilot because:
How is GitHub CoPilot used in the real world?
Software engineers can use GitHub CoPilot to streamline how they write VS code with the use of “ghost text,” the AI’s suggestions to complete lines of code, which can be adjusted depending on the language and framework being utilized. GitHub CoPilot’s Chat function also offers the ability to “talk” to the app, learning how to decipher lines of code, increase readability, fix errors, or implement new functions.
Llama 3.1 is another AI tool that is helpful to learn before a tech interview. It was developed by Meta and is a LLM (large language model). With 405 billion parameters, it’s the largest open-source AI model in the marketplace and supports a larger range of languages, which makes it more accessible for users across the globe. It also has an extended context length, which means it can process longer strings of text and perform more complex tasks and data analysis. With its increased size and capability, you’ll likely run into this tool at some point in your career, so it’s a good one with which to become familiar.
Software engineers should learn Llama 3.1 because:
How is Llama 3.1used in the real world?
As far as its use in the real world, Meta insists that engineers and developers can “generate an entire app from a prompt” using the Llama Coder App in Llama 3.1. Engineers can use Llama 3.1 to create Custom Language Models, which have taken AI to the next level, with high-level capabilities for translation, summaries, text generation, and so on.
If you’re already working as a software engineer, you can learn AI tools through an Advanced AI Courses for Tech professionals. These courses may either be self-paced or include live instruction, but most importantly, they are short courses that you can complete while working.
If you are totally new to tech and looking to become a software engineer, enrolling at the right coding bootcamp may be the next best step. You could also enroll in an Artificial Intelligence for Beginners course to help you get the basics on today’s in-demand AI tools.
Jennifer Inglis is a freelance writer, editor, and content creator with extensive professional expertise in advertising, media analysis, teaching, writing, and literature. Prior to becoming a writer, Jennifer was a Media Analyst for ten years and then earned her master's degree in Teaching, instructing middle-school students in college/career readiness, writing, and public speaking..
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