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Technology and in particular Artificial Intelligence (AI) is disrupting every industry and at the same time is opening up new avenues for disruption. Still, regardless of whether you’re new to the workforce or a seasoned professional, building an AI skill set can lead to some great career opportunities. In this guide, we’ll go through step-by-step how to get started with AI and provide a list of recommended courses, books, and other materials.
There are many online courses that can help you learn the basics of AI at your own convenience. Here are some top courses to consider:
a. Google AI Essentials:
Google provides an online course on AI called AI Essentials that requires no coding background. In the course, learners will be introduced to generative AI tools, the tutorial besides the prompt, and/ or responsible AI use cases. This course is well scheduled to suit everybody’s daily routines.
b. Stanford Online:
Stanford University offers many artificial intelligence courses through its online platform. These courses are offered at various levels such that you can begin right from learning the basics to courses for higher expertise. The curriculum comprises current information about industries, skills, and academic knowledge. Such courses include ‘Artificial Intelligence for Engineers and Technical Professionals’.
c. Coursera:
Coursera also provides some AI courses like IAI AI for Everyone, IAI Machine Learning, and IAI Convolutional Neural Networks. It is noteworthy that among them there are several courses by Andrew Ng like ‘Machine Learning with Andrew Ng from Stanford University’ and “AI For Everyone with Andrew Ng’, which is designed for a non-technical audience.
d. edX:
edX is a platform that hosts MIT and Harvard AI courses among other universities. For those who want to get down to the basics of AI, they will benefit from taking the ‘Artificial Intelligence for Everyone’ ‘Artificial Intelligence: Principles and Techniques’ course offered by Stanford University.
Reading is one of the best ways through which you can expand your knowledge of Artificial intelligence. Here are some highly recommended titles:
a. "Artificial Intelligence: A Modern Approach" by Stuart Russell and Peter Norvig:
This is probably the most renowned book on the subject of artificial intelligence. It encompasses a broad area of AI such as; search, learning, and robotics. They can be used effectively to teach all skill levels; starting from the basic level to the advanced level.
b. "Machine Learning Yearning" by Andrew Ng:
Thus, this book offers a roadmap on how to approach machine learning projects, specifically the aspects relating to the projects’ architectures. Co-authored by one of the leading authorities in the subject, it is an ideal book for anybody who wants to effectively adopt AI in practical applications.
c. "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville:
This encyclopedia-like book deals with deep learning from the basics of neural networks, optimization techniques, and further appurtenant advancements and uses. Unfortunately, it is best suited for the people, who are interested in the detailed specifics of the Artificial Intelligence field.
d. "Artificial Intelligence and Machine Learning" by Vinod Chandra S. S and Anand Hareendran S:
This book is recommended and suitable for undergraduate and postgraduate students. It offers a brief and effective concept regarding artificial intelligence and machine learning.
e. "Superintelligence: ”Three Worlds, Paths, Dangers, Strategies” by Nick Bostrom
This book aims to discuss the probable future applications of AI, its challenges, and the underlying issues accompanying them. For anyone who wants to be exposed to the general issues with AI, the book is quite a stimulating one.
Beyond courses and books, there are other valuable resources to help you develop your AI skillset:
a. Online Tutorials and Blogs:
Some of the platforms on which one can come across tutorials, articles, and case studies related to AI include Medium, Towards Data Science, KDnuggets, and many others. It is with these resources that one will be in a position to know the new trends and techniques being developed.
b. GitHub Repositories:
GitHub is an AI developer’s virtual treasure chest containing a wealth of AI-proof projects and code repositories. Engaging with these projects can give practical experience as well as knowledge of how these various algorithms function in real life.
c. AI Communities and Forums:
Some of the communities you might want to consider are reddit’s r/MachineLearning and Alignment Forum. These are good for seeking information, sharing information, and learning more about the industry ever changing innovations.
d. Conferences and Workshops:
Some crucial advantages that may be found are attending the AI conferences and workshops including NeurIPS, ICML, and CVPR, all of which are great opportunities to network and get a glimpse of the most significant developments in the field. Some of these meetings also allow participating in an online mode.
e. Practical Projects:
The best way of learning is by working on assignments that can be implemented in real-life situations. You can engage in some of the AI competitions that are available on sources such as Kaggle where you get to solve real-life challenges and also involve other persons with expertise in data science.
Education in the field of artificial intelligence involves both, didactic learning and the application of such skills into practice. By enrolling in online classes, reading great books, and use of other materials, you can have a strong basis in Artificial Intelligence. Regardless of your choice of becoming an academic, working in industry, or doing research in the trend and fast-growing field of AI, these tools and strategies will guide you.
