Artificial Intelligence Is One Of The Most Interesting Topics In Recent Years, Which Raised Both In The University And Industry. Today, The Most Important Question Is: How To Learn Artificial Intelligence?

At this time, it is at the peak of its power, and everyone is looking for a way to use it. In addition to high attractiveness, artificial intelligence brings many benefits to humans. The production of intelligent robots used in large industries and daily life is one of the advantages of artificial intelligence.

Due to the critical capabilities of this science, many people seek to learn and enter this field. In this field there are many training and educational resources that people can use and start their activities in this field. There are different types of books, articles, training videos, websites, training classes, etc., that you can use for training.

In all these courses, the required topics are taught theoretically, and then with the help of existing tools and specialized software, artificial intelligence-based systems are implemented. The most comprehensive and valuable artificial intelligence learning resources have been reviewed in the following.

How does artificial intelligence work?

As the hype of artificial intelligence has increased, governments worldwide are moving towards this area to get the most for the least amount of money. Also, one of the most significant applications of artificial intelligence is to reduce the amount of trial and error in the activities that use it.

Artificial intelligence requires a foundation of specialized hardware and software to write and train machine learning algorithms. Python is the most popular programming language used in artificial intelligence, which we have fully explained in the artificial intelligence roadmap course. AI systems generally work by taking large amounts of labeled training data, analyzing the data for correlations and patterns, and using these patterns to predict future states.

In this way, a chatbot fed samples of text chats can learn to create real-world exchanges with people, or an image recognition tool can learn to recognize and describe objects in images by going through millions of examples.

In the artificial intelligence roadmap, we will see that programming focuses on three cognitive skills: learning, reasoning, and self-correction. This aspect of synthetic intelligence programming learning processes focuses on acquiring data and creating rules for turning data into actionable information. Rules, called algorithms, provide step-by-step instructions for computing devices to complete a specific task.

AI reasoning processes are focused on choosing the correct algorithm to achieve the desired result. Also, AI’s self-correcting processes are designed to adjust algorithms and continuously ensure the most accurate results.

Why is it important to (have/know) an artificial intelligence roadmap?

An AI roadmap is essential because it can give its users insights into their operations that they may not have been aware of before. Because, in some cases, artificial intelligence can perform tasks better than humans. Especially when it comes to repetitive and detail-oriented tasks such as analyzing large numbers of legal documents to ensure that the relevant fields are filled out correctly.

Artificial intelligence tools often do things quickly and with minimal errors. Artificial intelligence has been able to help a lot in productivity and opened the door to new business opportunities for businesses and industries, of course. Before the current wave of artificial intelligence, using computer software to connect and communicate with people was challenging and unbelievable.

But Uber, the most famous internet taxi in the world, has become one of the largest companies in the world to use artificial intelligence to communicate with taxi drivers.

The algorithms used in Uber are as follows; It uses sophisticated machine learning algorithms to predict when people are likely to need a car in certain areas. These algorithms help drivers to move on the roads before they need to actively. The world’s largest and most successful companies have used artificial intelligence to improve their performance and gain an advantage. The artificial intelligence roadmap is a path-breaker for all people who intend to start their professional activities like the super companies of the world.

Artificial intelligence courses on Coursera

Coursera also organizes many different training courses in the field of teaching artificial intelligence concepts. Participating in these courses for a few weeks can bring a person to mastery and sufficient knowledge in this field. These courses are as follows, and you can join them according to your needs.

Machine Learning

Andrew Wu teaches this course, recognized as one of the most influential people in artificial intelligence. This course is in French, English, Japanese, and Indian languages. By participating in this course, after eleven weeks, the student can reach a suitable level of knowledge about machine learning topics. Practical and essential subjects such as regression, linear algebra, neural networks, recommender systems, large-scale machine learning, etc., are taught in this course.

Algorithms, Part I & II

Topics such as data structure concepts, algorithm design, search algorithms, graph processing, etc., are essential for learning artificial intelligence and machine learning. These concepts are taught by two professors named Kevin Wayne and Robert Sedgwick. By participating in this course, after six weeks and 6 to 10 hours of training every week, students can gain good knowledge in this field.

Neural Networks and Deep Learning

This course is also taught by Andrew Wu, Kian Ketanfarush, and Younes Bensouda to introduce the concepts of neural networks and deep learning. Different types of deep learning trends, the construction of neural networks, and their implementation are trained in this course. This course is suitable for people who have basic knowledge of artificial intelligence. Concepts such as Python programming, data structures, and linear algebra are required to participate in this course.

Structuring Machine Learning Projects

This course teaches people how to do successful machine-learning projects. After two weeks of participating in this course, you can learn error detection in machine learning systems. This course is also considered for beginners and is taught by Andrew Wu, Kian Ketanfarush, and Younes Bensouda.

In addition to those above, other sites such as EdX and Udacity also hold a wide variety of courses from beginner to advanced that you can participate in according to your level of knowledge in artificial intelligence. Most of these courses are in English, and others are in several languages. Participating in these courses can provide you with excellent and practical knowledge and experience, and you can become an expert in artificial intelligence and its subsets.

Participation in educational boot camps

Bootcamps are almost intensive courses in which the topics are presented in total, and people work in groups on practical projects. Participating in boot camps has other benefits in addition to training. In these courses, a person can achieve good mastery of artificial intelligence by completing practical projects; after completing the course, he is introduced to essential and active companies and organizations in this field to find a suitable job in them. Some artificial intelligence bootcamps are presented below.

Maps boot camp

Mapsa Bootcamp is one of the most reliable centers for holding educational bootcamps in Iran. Various bootcamps for Python and machine learning bootcamps are contained in this collection. All the subjects needed to learn and work on different projects in the field of artificial intelligence are presented in this boot camp, and after finishing it, you will gain proper knowledge in this field. Machine learning boot camp is suitable and practical for basic science and engineering graduates and people interested in working in the artificial aquarium field. This course includes more than 300 hours of face-to-face classes and practical workshops that can provide you with proper knowledge in this field. Finally, the institution’s valid certificate is awarded.

Learning through YouTube

One way to learn artificial intelligence for free is to use tutorial videos on websites like YouTube. Although this training may be scattered, it can convey helpful knowledge and information. Below are links to some examples of free training courses on YouTube that you can use for training.

• Artificial intelligence classroom at MIT
• Synthetic intelligence training for beginners
• Background and Future of artificial intelligence
• Artificial intelligence with Python
• Artificial Intelligence Syllabus Discussion and Analysis for NTA NET

last word

Like any other science, learning artificial intelligence and its subcategories requires reliable sources. In addition, your practice and effort to learn is critical. This article introduced as many valuable resources as possible for learning artificial intelligence. After choosing these methods and courses, you must practice hard and persistently to become an artificial intelligence expert.