Artificial intelligence is a hot topic in the tech industry. You may have heard about AI but don’t know much about it or how to get started in this field. If so, this post is for you. In it, I’ll walk you through six steps that will help you become more informed about AI and give you an edge in any job search related to artificial intelligence.
1. Read About Artificial Intelligence
To get started on your journey, we recommend reading the following books:
- Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig. This book is a comprehensive guide to artificial intelligence, covering everything from its history to the most recent research in areas such as machine learning and natural language processing.
- Artificial Intelligence for Humans by Alan Winfield. This book offers an overview of different types of AI that can be applied to real-world problems, along with helpful examples of how these techniques are being put into practice today (e.g., using genetic algorithms in optimizing manufacturing processes).
- The Master Algorithm by Pedro Domingos. In this book, you’ll learn about some of the most popular machine learning algorithms used today (such as neural networks or k-means clustering) and their strengths and weaknesses when used for specific applications like speech recognition or self-driving cars.
2. Get Informed About Emerging AI Tools
The second step is to understand the emerging AI tools. If you’re new to the industry, it’s very likely that these technologies are unfamiliar to you. Fortunately, there are some great resources online that can help get you up to speed on DevOps, Kubernetes registry, and Docker—three of the most critical emerging tools in AI.
Getting yourself up to speed on these tools will give you the knowledge needed to understand how they work, how they’re used in the context of AI development, and what their advantages and disadvantages are compared to other tools.
3. Learn an AI Programming Language
Once you’ve decided to pursue a career in AI, you’ll need to learn one of the three most popular programming languages: Python, Java, or R. These are all common languages for artificial intelligence applications and tools because they’re used to create machine learning models.
Why Are These Languages Important?
There are many reasons why these three programming languages are essential for learning AI. First off, they can be used on almost any operating system (Windows, macOS, Linux). This means that once you’ve become familiar with them on one platform, switching over will be pretty easy no matter where you work. In addition to this cross-platform compatibility benefit, each language has its strengths and weaknesses, which may make one more suitable than others depending on your needs:
- Python is known for being easy to use and read
- R is favored by analysts due to its vast library of statistical analysis tools
- JavaScript has been used extensively in web development
4. Develop Your Data Skills
Data skills are essential to AI and are a great way to differentiate yourself from the competition. The ability to collect, clean, organize and analyze data is critical for any industry that uses AI technologies. Data scientists need to know how to gather relevant information from multiple sources to make sense of it all.
5. Start an AI Project
Once you’ve learned the basics of AI, it’s time to put your skills to use. Start by building something simple with a minimal dataset and then expand from there. Consider asking for help from colleagues or friends if needed: There are lots of resources available online that can provide insight into how others have solved similar problems in the past. The most important thing is learning how to work with these tools so that when more complex tasks arise, your success rate won’t be too low!
6. Know the Types of AI Jobs Available
AI jobs are available in many different fields and industries. When you think about AI’s impact on our lives, you may be surprised to learn how diverse these jobs are.
There are AI jobs for people with different skill sets, including data scientists and software engineers. Career paths require specialized training or expertise and opportunities for people who want to get started in a new industry but don’t have much experience yet.
For example, if you’re an experienced programmer and math whiz with a passion for machine learning algorithms and the inner workings of neural networks (a type of deep learning algorithm), then it’s possible that your dream job is just waiting for you! But if this sounds intimidating or too technical, don’t worry: there are plenty of other ways to start working with AI without getting a Ph.D. first!
Conclusion
As you can see, there are many ways to get started in artificial intelligence. If you’re interested in a career in AI, we recommend starting by reading up on the field and learning about emerging tools and languages. Then, develop your data skills (especially machine learning techniques), and start an AI project that aligns with your interests and strengths. Finally, keep an eye out for job openings where employers need expertise in one or more of these areas—and don’t forget that it’s okay if they don’t call themselves “AI jobs.”