Artificial intelligence is everywhere these days – from your phone to your car. Learning AI isn’t just for tech experts anymore. It’s becoming a must-have skill for anyone who wants to stay ahead.

Sadly, AI learning can feel overwhelming for many. This rapidly evolving field comes with complex terminology and far-reaching applications, which can be difficult for newcomers to grasp. However, understanding AI is becoming increasingly important for professionals across various industries. 

In this article, we’ll explore the fundamentals of AI and how to begin your AI learning journey.

Understanding artificial intelligence (AI)

Artificial intelligence, or AI, is a wide-ranging field in which computer systems can perform tasks traditionally done by humans. These smart systems can handle complex jobs like understanding images, recognizing speech, making decisions, and translating languages. 

What makes AI unique is its ability to improve over time. As these systems encounter new information and situations, they can learn, adapt, and become more efficient at their tasks, much like humans do with practice and experience.

AI solutions drive innovation and efficiency for businesses. AI has changed business operations, from automating everyday tasks to giving you actionable insights from complex data sets. Its applications span industries, enhancing productivity and enabling new healthcare, finance, and education possibilities. 

Different types of AI

To effectively learn AI, you need to understand the various types available. These include: 

  • Narrow AI: This is the most common form of AI, designed for specific tasks. Examples include voice assistants like Siri or Alexa and recommendation systems used by streaming platforms. Most AI systems for software teams use narrow AI to automate tasks, streamline processes, and improve productivity. 
  • General AI: This more advanced type of AI aims to give computers the same level of intelligence as humans, making them capable of performing intellectual tasks. While still theoretical, it’s a major focus of AI research. 
  • Superintelligent AI: This hypothetical AI would surpass human intelligence across all domains. It remains a concept explored in research and science fiction. 

Currently, most AI applications in business and technology fall under Narrow AI, while General AI and Superintelligent AI remain areas of ongoing research and development. 

AI vs machine learning & deep learning

While often used interchangeably, AI, machine learning, and deep learning are distinct but related concepts. 

Artificial intelligence, commonly known as AI, is an expansive area of computer science aimed at developing intelligent systems. These systems are designed to carry out complex tasks that usually need human-level thinking. AI equips machines with the capacity to process information, reason, and make choices, similar to how people do.

AI machine learning, a type of AI, involves teaching computers to learn from data. Instead of following strict programming rules, these systems improve their performance over time as they process more information – similar to how humans get better at a task with practice.

While machine learning is a type of AI, deep learning is a type or subset of machine learning. It uses complex systems called neural networks, which are inspired by how the human brain works. These networks have many layers (that’s why they are called “deep”) and can understand complicated patterns in data, allowing them to tackle complex problems like image recognition or language translation.

Each field builds upon the other, creating an ecosystem of intelligent systems. 

How to learn AI

Learning AI can seem complicated, but anyone can understand the basic concepts with the right approach. Here’s a step-by-step guide to help you begin learning AI:

Set goals and expectations

Before you begin learning AI, you should have a clear idea of what you want to achieve in a professional context. 

Set realistic timeframes for learning AI, considering any current commitments you have. At this point, you should also identify the resources needed to reach your goals, including courses, books, and practical projects. 

Build a strong foundation

A solid foundation in programming and mathematics is crucial for AI learning. Consider learning a programming language like Python, widely used in AI development. 

Additionally, you should study essential math concepts like linear algebra, calculus, and statistics. This will help you familiarize yourself with basic computer science principles and algorithms. 

Several online courses are available to help you understand these principles and begin your AI learning journey.

Develop AI skills

Once you have the basics, start developing practical AI skills. You can begin with introductory AI courses online from reputable platforms and work on hands-on projects to apply your knowledge to real-world scenarios. 

Here are some ways to gain experience: 

  • Online learning platforms: Explore e-learning websites offering AI and machine learning courses. Many platforms partner with universities and industry experts to provide high-quality content. 
  • Open-source AI libraries: Familiarize yourself with popular open-source AI libraries and frameworks. These tools are widely used in the industry and can help you implement AI algorithms efficiently.
  • AI communities and forums: Join online communities focused on AI and machine learning. These platforms often share resources, discuss new developments, and offer opportunities for collaboration on AI projects.

Explore AI tools

To understand AI’s practical applications, explore AI-powered tools that influence industries. Luckily, you don’t have to be a developer to learn how to use AI in the workplace or to improve your daily life. 

Most tools with AI features will walk you through how to use them. So, whether you’re a marketing professional looking to optimize your content strategy or a project manager who wants to streamline your workflow, there’s an AI tool to help you achieve your goals. 

Here are some popular types of AI productivity tools to explore:

  • Generative AI tools: These create new content from scratch, like text, images, or music. 
  • AI-enhanced project management tools: These use AI to optimize task allocation, predict project timelines, refine project scope, and identify potential risks.
  • AI-powered analytics platforms: These tools use machine learning to derive insights from complex datasets, aiding in data-driven decision-making.
  • Chatbots and virtual assistants: These AI-driven conversational interfaces can handle customer queries or assist with task management.
  • AI writing assistants: These help improve writing by suggesting edits, generating content, or even translating between languages.

To effectively use these tools: 

  • Start using the basic features provided and gradually explore more advanced capabilities.
  • Pay attention to how the AI generates or processes information to understand its strengths and limitations.
  • Regularly check for updates, as AI tools constantly improve and add new features.
  • Consider how these tools can be incorporated into your existing workflows for maximum efficiency.
  • Always maintain a critical perspective and verify AI-generated outputs when necessary.

Ready to get started with AI? Atlassian Intelligence is a powerful tool that enhances project management and team collaboration. It integrates AI capabilities into workflows, offering features like smart task prioritization, predictive analytics for project timelines, and AI-assisted documentation. 

Atlassian AI showcases how AI can boost team productivity and improve decision-making processes in real-world business scenarios. By exploring Atlassian Intelligence, you can gain practical insights into how AI transforms project management and collaboration.

Create a learning plan

A well-structured learning plan can significantly boost your progress in mastering AI. Set realistic goals and break them down into milestones. This project management approach helps you track progress and stay motivated while learning AI.

Consider carving out specific time slots in your weekly schedule for AI study, ensuring they align with your professional and personal commitments. Aim for regular, focused study sessions rather than sporadic, lengthy ones to build consistency and maintain momentum.

Enhance your understanding by exploring video tutorials, podcasts, and academic papers, which offer diverse perspectives on AI concepts. 

Be prepared to adjust your plan as you progress; flexibility allows you to adapt to the learning methods that work best for you. 

Why is it important to learn AI?

A strong understanding of AI is increasingly valuable for professionals at all levels. Learning AI offers numerous benefits for professionals in the workplace, such as: 

  • Career advancement: AI skills are in demand across industries, opening up new opportunities for career growth.
  • Problem-solving: AI techniques can be applied to solve complex real-world problems, improving decision-making processes.
  • Competitive advantage: Companies with AI-savvy professionals are better positioned to leverage technology for business success.
  • Automation and efficiency: AI knowledge enables the implementation of automation strategies, increasing operational efficiency.

Tips for excelling in AI

Follow these tips to excel when learning AI:

  • Stay curious and open-minded about new developments in the field.
  • Practice regularly with hands-on projects that simulate real-world applications.
  • Keep up with the latest AI developments through industry publications.
  • Collaborate with others on AI projects to gain diverse perspectives and insights.
  • Apply AI concepts to solve real-world problems in your current role or industry.

Remember, learning AI is a process that requires continuous improvement. As AI evolves, so should your knowledge and skills. 

Master AI with Atlassian Intelligence

Atlassian Intelligence offers a unique opportunity to enhance your AI learning experience by providing hands-on exposure to AI-powered tools in the workplace. Integrating AI capabilities across platforms like Jira, Confluence, and Bitbucket, Atlassian Intelligence shows you how AI can enhance project management, content creation, and team collaboration. 

As you explore features like automated content generation with generative AI, smart searches, and data summarization, you’ll gain insights into how AI can streamline workflows and boost productivity in real-world scenarios.

To leverage Atlassian tools and integrate AI skills into your professional workflow and project planning process, start by familiarizing yourself with the AI-driven features in your daily tasks. Experiment with AI for content creation in Confluence, task automation in Jira, or code analysis in Bitbucket. 

Learn more about Atlassian Intelligence.

How to learn AI for beginners