Best Resources to Learn Artificial Intelligence in 2024

Artificial intelligence (AI) is one of the most transformative technologies of our time, rapidly changing the world around us. From self-driving cars to medical diagnosis to customer service, AI solves complex problems and improves our lives in countless ways. It is among the most sought-after technical skills demanded by recruiters. This article will help you with the best resources to learn AI.

Intelligent systems, capable of learning automatically with the help of artificial intelligence (AI), are increasingly part of our lives. These systems recommend which products to buy, which videos to watch, what music to listen to, and who to interact with on social platforms, and they even respond to us they consult and dialogue as if they were another person. There is a lack of professionals in this discipline, and companies demand skilled AI professionals. Beginning to explore this new paradigm allows us to find new educational possibilities. Internet hosts hundreds and thousands of free and paid AI resources to help professionals hungry to develop their AI skills. Take a look at a few of the best resources to learn artificial intelligence and kickstart your journey towards learning AI.

Must Read – What is Artificial Intelligence?

What is Required to Study AI?

One of the main reasons people do not jump right into AI is that they don’t know where to start. Many technicalities get in the way when looking for resources to learn Artificial Intelligence. Here are some suggestions before you get started learning Artificial Intelligence.

1. Work Upon Fundamentals

One of the best ways to get started in AI is to brush up on the fundamentals. You can start with basic mathematics, such as computer science fundamentals, statistics, probability, vectors, linear algebra, calculus, etc. You can then move on to learning a programming language such as Python or R since both languages ​​have sets of libraries that can implement any complex algorithm with a few lines of code.

In addition to these fundamentals, there is more knowledge to help you better manage your data. Here, the basic concepts of databases such as SQL, NoSQL, relational and non-relational databases, data visualization tools like Tableau or MS Excel, and data formats (JSON, CSV, XML), among others, stand out.

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2. Learn Data Pre-processing

Once you understand how to deal with data, it is recommended that you learn different techniques to convert unstructured data into structured data and obtain valuable information by applying Machine Learning algorithms. These methods include principal component analysis, dimensionality reduction, normalization, data elimination, sampling, feature extraction, etc.

How to Study Artificial Intelligence?

Now that you have worked on your basics and figured that you are all set to enter the technicalities of Artificial Intelligence, you need to explore different types of resources available to help you learn the subject. Today, there are a lot of online courses and tutorials, YouTube channels, distance learning courses, bootcamps, and MOOCs (Massive Open Online Courses) from recognized universities and institutes, which follow tested and proven methodologies to help you learn the subject.

After completing basic training, you can always start a specialization in a specific domain, such as big data, robotics, deep learning, computer vision, machine learning, cognitive robotics, computational perception, and natural language processing (NLP), among others.

Also Read – Top Real-World Artificial Intelligence Applications

Online Artificial Intelligence Courses

Below are some online learning resources from the leading online learning platforms.

• Welcome to Artificial Intelligence by Udemy – The course can help you understand the basics of Artificial Intelligence and Machine Learning.
• AI for Everyone by IBM on Coursera – AI for Everyone is among the most popular AI courses online. It covers the basics of AI, including neural networks, AI ethics, problem-solving in AI, building AI strategies, etc.
• Knowledge-Based AI: Cognitive Systems by Udacity – This is a free, advanced-level AI course that covers structured knowledge representations, problem-solving methodologies, planning, decision-making, and learning methods.
• Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning by Coursera – As the name suggests, you will get to work with TensorFlow to implement the principles of Artificial Intelligence, Machine Learning, and Deep Learning in creating scalable models WRT real-world problems.
• IBM Applied AI Professional Certificate by IBM on Coursera – The IBM Applied AI Professional Certificate will give you an understanding of AI technology, its applications, and its use cases.
• Fundamentals Of Artificial Intelligence by NPTEL – Fundamentals of Artificial Intelligence by IIT Guwahati on NPTEL gives an overview of concepts of problem-solving, knowledge representation, reasoning, and learning methods of AI.

Must Explore – Artificial Intelligence Online Courses & Certifications

Books on Artificial Intelligence

Books never get out of fashion when it comes to learning the content thoroughly and keeping the knowledge handy. These artificial intelligence books can certainly help you sharpen your skills further.

1. Artificial Intelligence – A Modern Approach – by Stuart Russell & Peter Norvig – This is a series of three books that cover the basic concepts of AI and is particularly helpful for beginners or non-programmers.
2. Driven: The Race to Create the Autonomous Car by Alex Davies – The book refutes the outdated theory of big, brawny, brainy dudes reshaping the future and talks about autonomous vehicles or, popularly, robot cars.
3. New Laws of Robotics: Defending Human Expertise in the Age of AI by Frank Pasquale – The book explores the world of AI and gives a sneak peek into the future that would have factory robots, medical diagnosis algorithms, and online learning.
4. Artificial Intelligence and Soft Computing: Behavioral and Cognitive Modeling of the Human Brain by Amit Konar – This book focuses on the tools and techniques required for the intelligent realization of machines.
5. Human + Machine by Paul R. Daugherty and H. James Wilson – This book discusses the role of artificial intelligence with respect to businesses and economic applications.

YouTube Channels to Learn AI

YouTube channels are among the most popular learning resources among tech enthusiasts. All you have to do is get subscribed to your chosen channel and learn the practical aspects of artificial intelligence or other related topics. Let’s look at some of the popular YouTube channels for AI learners.

• 3Blue1Brown – Explains the content through animation.
• Computerphile – Focuses primarily on AI techniques and covers a range of content such as security vulnerability, processing power, security, etc.
• Two Minute Papers – With over 1.12M subscribers, this channel is a rage among hardcore learners. Two Minute Papers shares summaries of newly published AI research.
• Artificial Intelligence – All in One – This channel covers content related to Artificial Intelligence, Deep Learning, Machine Learning, Natural Language Processing, Computer Vision, and Data Science.

AI Experts to Follow

You can also follow famous AI engineers and entrepreneurs online. Some of the popular names are –

• Jeremy Howard (fast.ai)
• Andrew Ng (Coursera)
• Andrej Karpathy (Tesla AI)
• Yann LeCun (Facebook AI)
• Rachel Thomas (fast.ai, data ethics)
• Francois Chollet (Google)
• Fei-Fei Li (Stanford)
• Anima Anandkumar (Nvidia AI)
• Demis Hassabis (DeepMind)
• Geoffrey Hinton (Google)

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More Resources

Apart from the course format, we can and should use much more content on the Internet to deepen our knowledge about Artificial Intelligence. Let us review some of them:

• Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data: The Becoming Human blog offers this huge compilation of cheat sheets on AI and related topics
• Machine Learning Glossary: A comprehensive glossary – with graphics and formulas – on concepts related to machine learning.
• Mining of Massive Datasets: A book on big data, written by three Stanford professors, and legally available on the Internet
• Understanding Machine Learning: From Theory to Algorithms: Book is used as the basis of many university courses on machine learning and is legally available on the Internet. In English.
• A Brief Introduction to Neural Networks: Book posted by its author, a German data scientist, to introduce us to neural networks
• Notes On Using Data Science & Machine Learning To Fight For Things That Matter: The director of machine learning at the Wikimedia Foundation offers an extensive compilation of commented code cheats.

Here are some additional tips for getting started with AI:

• Focus on the basics. Take your time, try to learn slowly and grasp concepts better. Focus on learning the fundamental concepts of AI, such as linear algebra, calculus, probability theory, statistics, and computer science.
• Be patient. Learning AI takes time and effort. Don't get discouraged if you don't understand everything right away. Just keep practising and learning.
• Find a mentor. If you know someone experienced in AI, ask them to be your mentor. They can provide guidance and support as you learn.
• Join a community. There are many online and offline communities for AI enthusiasts. Joining a community can help you stay motivated and learn from others.

Conclusion

This new world, full of intelligent systems capable of learning quickly, brings us many benefits and presents us with enormous challenges. In this reality where artificial intelligence (AI) is gaining more prominence daily, we can only be consumers or go one step further. Learn the concepts of AI through these best resources to learn artificial intelligence and be a part of the world of innumerable possibilities.

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