This guide to learning artificial intelligence is suitable for any beginner, no matter where you’re starting from.
Every time you shop online, search for information on Google, or watch a show on Netflix, you interact with a form of artificial intelligence (AI). The applications of AI are everywhere and will only continue to grow.
From factory workers to waitstaff to engineers, AI is quickly impacting jobs. Learning AI can help you understand how technology can improve our lives through products and services. There are also plenty of job opportunities in this field, should you choose to pursue it.
Learning AI doesn’t have to be difficult, but it does require a basic understanding of math and statistics. In this guide, we’ll take you through how to learn AI and create a learning plan.
What is artificial intelligence? And, why should you learn it?
Artificial intelligence (AI) is the process of simulating human intelligence and task performance with machines, such as computer systems. Tasks may include recognizing patterns, making decisions, experiential learning, and natural language processing (NLP). AI is used in many industries driven by technology, such as health care, finance, and transportation.
Learning AI is increasingly important because it is a revolutionary technology that is transforming the way we live, work, and communicate with each other. With organizations across industries worldwide collecting big data, AI helps us make sense of it all.
AI engineers earn a median salary of $136,620 a year, according to the US Bureau of Labor Statistics [1]. Professionals in this field can expect the number of jobs to grow by 23 percent over the next decade.
Besides being a lucrative career path, it is a fast-growing field and an intellectually stimulating discipline to learn.
Hear more about AI in this lecture from Stanford and DeepLearning.AI’s Machine Learning Specialization:
How long does it take to learn AI?
The amount of time it takes to learn artificial intelligence depends on several factors, including:
- Prerequisite knowledge: If you have general knowledge of math and statistics, you can skip straight toward learning AI skills and tools.
- Career intent: If you want to pursue a job in the AI field, you’ll want a more comprehensive education than someone who simply wants to add context to their data analytics role.
- Background knowledge: If you’re switching from another major or field, then it’ll take longer to learn than someone who is already working in the technology field and has a basic understanding of its complex jargon.
How to learn artificial intelligence
Here are four steps to guide your learning. To start your journey into AI, develop a learning plan by assessing your current level of knowledge and the amount of time and resources you can devote to learning.
1. Create a learning plan.
Before you dive into a class, we recommend developing a learning plan. This includes a tentative timeline, skill-building goals, and the activities, programs, and resources you’ll need to gain those skills.
First, ask yourself the following questions:
- Your level of knowledge of artificial intelligence: Are you a true beginner? Do you have a foundation in math and statistical skills? Are you familiar with basic terminology and concepts?
- Your intention for learning: Are you pursuing a new career or just supplementing your current career?
- How much time you can spend learning: Are you currently employed? Do you want to learn full-time or part-time?
- How much money you can spend: Do you want to invest in a boot camp, take professional courses online, or watch some videos on YouTube and TikTok?
- How do you want to learn: Are you interested in pursuing a degree program, a boot camp, or self-teaching through a variety of online courses?
Later in this article, we’ll provide an example of a learning plan to help you develop yours.
2. Master the prerequisite skills.
Before starting your learning journey, you’ll want to have a foundation in the following areas. These skills form a base for learning complex AI skills and tools.
- Basic statistics: AI skills are much easier to learn when you have a firm grasp of statistics and interpreting data. You’ll want to know concepts such as statistical significance, regression, distribution, and likelihood, all of which play a role in AI applications.
- Basic math: Understanding AI, especially machine learning and deep learning, relies on knowing mathematical concepts such as calculus, probability, and linear algebra. These frequently appear in AI algorithms and models.
- Curiosity and adaptability: AI is complex and rapidly evolving, so there is a constant need to keep up with new techniques and tools. Those looking to pursue a career in AI should have an insatiable thirst for learning and an adaptable mindset for problem-solving.
The depth to which you’ll need to learn these prerequisite skills depends on your career goals. An aspiring AI engineer will definitely need to master these, while a data analyst looking to expand their skill set may start with an introductory class in AI.
If you already have a baseline understanding of statistics and math and are open to learning, you can move on to Step 3.
3. Start learning AI skills.
Once you’ve covered the prerequisites, let’s dive into the essential skills you’ll need for AI. Your level of mastery will depend on the type of role you’re pursuing.
Programming
Knowing how to code is essential to implementing AI applications because you can develop AI algorithms and models, manipulate data, and use AI programs. Python is one of the more popular languages due to its simplicity and adaptability, R is another favorite, and there are plenty of others, such as Java and C++.
From: Coursera