How to learn AI on your own (a self-study guide)

Estimated reading time: 5 minutes

Artificial intelligence (AI) is one of the most exciting and rapidly evolving fields of computer science. AI is the science and engineering of creating intelligent machines that can perform tasks that normally require human intelligence, such as vision, speech, reasoning, decision making, and more.

But how can you learn AI on your own, without enrolling in a formal course or degree program? Is it possible to master the concepts and skills of AI by self-study?

The answer is yes, if you are motivated, curious, and willing to invest some time and effort. In this blog post, I will share with you some tips and resources that can help you learn AI on your own, at your own pace and level of interest.

Here are the steps that News Round the Clock (NRTC) recommend for self-study AI:

1. Learn the basics of programming and math

AI requires a strong base in programming and math; build expertise in these areas for a successful exploration into AI.

Also read: Positioning yourself for the future of work: acquiring skills and having a product to sell

Basic coding requires familiarity with variables, data types, loops, functions, arrays, lists, dictionaries, classes, objects, inheritance, recursion, algorithms, logic, sets, graphs, matrices, vectors, calculus, and statistics.

If you need to brush up on these topics, there are many online courses and books that can help you. For example, you can check out Codecademy for programming, Khan Academy for math, or Coursera for both.

2. Choose an AI subfield that interests you

AI is a broad and diverse field that encompasses many subfields and applications. Some of the major subfields are machine learning, deep learning, natural language processing, computer vision, speech recognition, robotics, artificial neural networks, genetic algorithms, expert systems, fuzzy logic, and more.

Each subfield has its own theories, methods, tools, and challenges. You don’t need to learn everything about AI, but you should pick one or a few subfields that interest you and focus on them.

You can explore the different subfields by reading articles, watching videos, listening to podcasts, or browsing websites that showcase AI projects and applications. For example, you can check out Towards Data Science for articles, TED for videos, Lex Fridman Podcast for podcasts, or Kaggle for projects.

3. Learn the theory and practice of your chosen subfield

Once you have chosen a subfield that interests you, you should learn both the theory and the practice of it. The theory will help you understand the principles and concepts behind the algorithms and techniques that are used in AI.

The practice will help you apply the theory to real-world problems and data sets. You should balance both aspects of learning by reading books and papers that explain the theory in depth and by taking online courses or tutorials that teach you how to implement the theory in code.

For example, you can check out Artificial Intelligence: A Modern Approach for a comprehensive book on AI theory or fast.ai for a practical course on deep learning.

4. Build your own projects and portfolio

The best way to learn AI is by doing it. You should not only learn from existing examples and exercises but also create your own projects that showcase your skills and creativity. One can use open-source frameworks and libraries such as TensorFlow , PyTorch , scikit-learn , OpenCV , NLTK , etc., to build your own AI models and applications.

You can also use public data sets such as UCI Machine Learning Repository , ImageNet , COCO , SQuAD , etc., to train and test your models.

One should document your projects with clear code comments , README files , blog posts , presentations , etc., and share them with others on platforms such as GitHub , Medium , SlideShare , etc., to get feedback and exposure.

5. Keep learning and improving

AI is a fast-moving field that is constantly evolving with new research findings , innovations , trends , and challenges .

You should not stop learning after completing a project or a course but keep updating your knowledge and skills with the latest developments in the field. You can follow blogs , newsletters , podcasts , YouTube channels , Twitter accounts , etc., that cover AI news and insights .

One can also join online communities such as Reddit , Stack Overflow , Quora , Discord , etc., where you can ask questions , answer questions , discuss ideas , share resources , network with other learners and experts , etc.

Learning AI on your own is not easy but it is rewarding . You will not only gain valuable knowledge and skills that can boost your career prospects but also have fun exploring the fascinating world of artificial intelligence .

I hope this News Round the Clock (NRTC) post has given you some guidance and inspiration on how to start your self-study journey . Remember that learning is a lifelong process that requires curiosity , persistence , and passion . Happy learning !