
Artificial Intelligence (AI) is no longer just limited to science fiction and movies. In fact, AI is an aspect of our everyday lives. From asking a live chatbot in your browser to chatting with Siri or Alexa, AI is real and widely used. AI has even emerged as one of the most popular buzzwords on the internet.
With every individual and business looking to implement AI-based applications in one way or another, this particular field is creating endless AI-related job and career opportunities.
Artificial Intelligence Course
For example, use the search tab and type in “AI courses” and you'll see a variety of issues and topics related to AI or machine learning courses, short or long term, personal or corporate.
Artificial intelligence is a sub-field of computer science that studies and develops the ability of machines to mimic human intelligence and exhibit skills like the human brain. Medical diagnosis, language translation, facial recognition, companion apps, etc. are some of the practical applications of AI technology.
These are specific programs and AI-based courses that help you acquire knowledge and skills across the AI ecosystem. These courses can be developed at both advanced and beginner levels, and a basic form of delivery is usually accessible. Furthermore, let's say you are serious about continuing your education with an AI course. In that case, you should have some knowledge and experience with at least one programming language such as Python, C/C++, or MATLAB.
GitLab AI Courses
The potential of AI in GitLab is code suggestions, vulnerability explanations, and DevSecOps automation to increase the efficiency of development operations. These include leveraging AI-based services to increase code quality, security, and deployment speed. GitLab courses are practical training on how to use these capabilities, enabling developers to incorporate advanced technologies such as AI into software development. Let's take a quick look at GitLab's top AI courses to master artificial intelligence.
AI Courses to Master Artificial Intelligence
Here is a list of top AI courses in GitLab that will boost your knowledge and skills. In these courses, you will learn how to use Duo Codes to improve code suggestions in GitLab, including using artificial intelligence to help complete and generate code, provide real-time suggestions, generate code from comments made in natural language, and more.
Turning ML models into online apps
We will show you how to integrate machine learning (ML) models into online applications on the GitLab DevSecOps platform and Vertex AI. Learners will gain a deeper understanding of their work by providing a live demo of how to implement ML models into a web app without interruption.
Train ML models on GPU-enabled runners
This course teaches you how to use GitLab CPU-enabled runners to advance machine learning (ML) model training and discusses optimization strategies to speed up ML workflows.
There is no MLOps without DevSecOps
In this blog, we will discuss the different ways the GitLab Data Science team uses the DevSecOps platform to train machine learning models and improve and track experiments. We will provide real-world examples to help you understand the steps required to optimize the process.
Fix vulnerabilities with GitLab AI
In this class, you will learn about the Vulnerability AI feature, which runs Google AI to provide a brief description of the vulnerabilities identified. As part of the learning process, users will enable this feature and apply the AI-generated recommendations to learn how to mitigate the identified checks exhibited by SQL Injection.
GitLab Duo Case Study – Demo
The objective of this tutorial is to familiarize the reader with GitLab Duo and the types of AI-based DevSecOps solutions. It will introduce strategic ways to configure, integrate test, and deploy an LLM chatbot using GitLab to improve cycle time performance while introducing AI solutions in the software development value chain.
Learn Rust with AI
This tutorial helps you learn Rust using AI-powered suggestions from GitLab Duo Code Suggestions. To help you apply Rust effectively, participants will participate in hands-on training sessions aimed at improving the effectiveness of AI.
Advanced Rust with AI
This course follows on from our previous tutorial, “Learn Rust with AI,” and builds on the concept of a feed reader application. This course takes a more hands-on approach, taking users through a Rust programming project while incorporating AI support to enhance the experience.
Introduction to CI/CD
This article provides a brief overview of CI/CD and its role within the DevSecOps process and the GitLab ecosystem. Through these AI courses from Gitlab, you will be able to define CI/CD, outline its benefits, and explain the mechanics of CI/CD pipelines and GitLab in the software development lifecycle.
The benefits of a career in AI
AI and ML are rapidly evolving technologies with practical applications in industry. Skills in these technologies are therefore marketable. This program will not only give you more practical experience but also give you a credible qualification that is entirely focused on AI, which will make you valuable in the context of emerging AI opportunities.
The benefits of a career in AI
Some of the biggest companies like Google, Amazon, Nokia, Microsoft, Nike, Apple, etc. offer AI candidates, so you are guaranteed a promising and big career.
We guarantee employment in a variety of roles including Data Scientist, Software Engineer, Natural Language Processing Engineer, AI Engineer, Data Miner, ML Engineer and many more.
It will expand the scope of participation in various sectors such as health, automobile manufacturing, banking and financial institutions.
It contributes to enhancing and building professional experience and skills with a broader perspective at an international level.
Lastly, since AI is still relatively new and evolving, pursuing an AI-related profession can definitely help you earn a decent living as those who decide to learn such skills can earn a good income.
FAQ
1. Does GitLab use AI?
Yes, GitLab incorporates AI into various aspects of its platform. It employs AI technologies in features such as assisted code reviews, automated testing, and project management. Additionally, GitLab integrates AI-powered tools for tasks such as code analysis, issue prioritization, and continuous integration to make software development teams more collaborative and efficient.
2. What is Apple’s AI called?
Apple's AI is called “Core ML”, an Apple-developed machine learning framework that enables developers to integrate trained machine learning models into their iOS, macOS, watchOS, and tvOS applications, enabling tasks like image recognition, natural language processing, and sentiment analysis to run directly on Apple devices, improving performance, privacy, and user experience.
3. Is AI a great career for the future?
AI has a promising career outlook as it is in high demand across various industries. With advancements in technology, AI professionals can look forward to diverse opportunities in fields such as healthcare, finance, autonomous vehicles, and more. Pursuing a career in AI can lead to rewarding roles in research, development, implementation, and innovation to help shape the future of technology and society.
4. Where do you see AI in five years?
Over the next five years, AI will become deeply integrated into our daily lives, revolutionizing industries such as healthcare, transportation, finance, and entertainment. AI is expected to enable more personalized experiences, improve decision-making processes, and automate routine tasks. Advances in AI have the potential to lead to breakthroughs in areas such as natural language processing, robotics, and autonomous systems. However, as AI's influence grows, ethical considerations and regulation will become increasingly important. Overall, the trajectory of AI suggests a future in which AI plays a central role in shaping how we live, work, and interact with technology.
5. What jobs will AI replace by 2030?
According to some reports, about 50% of the transportation industry and more than 5% of the warehousing industry are at high risk of being replaced by AI and robots by 2030. This means that more than 10 million jobs could be lost in the United States alone over the next five to ten years.