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Anyone who wants to learn AI is a beginner at some time, whether it is a fresh college graduate or an individual already working and wants to move into this career path. Everyone starts somewhere someday. So, never take the pressure of the syllabus. For sure, learning is huge, but it is not complex.Read more
Anyone who wants to learn AI is a beginner at some time, whether it is a fresh college graduate or an individual already working and wants to move into this career path. Everyone starts somewhere someday. So, never take the pressure of the syllabus. For sure, learning is huge, but it is not complex. If followed properly, anyone can achieve it and interest matters more than the discussion on difficulty level. AI is very vast and similarly artificial intelligence syllabus is also very vast but there are some of the most important topics in artificial intelligence syllabus which are mostly relevant in the current scenario.
See lessIn this article, I will tell you about the most important artificial intelligence syllabus
Natural Language Processing : This entails understanding and generating content in natural language (e.g. English). Chatbots are an application of NLP
Machine learning: Machine learning deals with statistical and mathematical models used by algorithms to learn some functions by way of examples. ML is heavily used in all types of tech processes.I love this part of the artificial intelligence syllabus. Machine learning is a set of tools data scientists use to discover correlations between input data and desired outputs. A lot of data science projects use machine learning, but not all data science is about machine learning. Data science also involves analytic problem solving, business insight, data manipulation and other skills. The amount of time a data scientist often spends on the machine learning part is usually much lower than the time spent on analyzing the business case, cleaning up data, reshaping data into a form you can use and making sure the results make sense (cross validating, hypothesis testing etc.)
Symbolic logic: This is where A.I started or you can say the basis of all the artificial intelligence syllabus. Symbolic logic is not a field with great many applications but it is important for its historic context.
Deep learning: A related field is deep learning, where the learning takes place through black-box algorithms with several complicated/inter-connected layers of processing units. Artificial neural networks are an example of this.
These are some of the important parts of the artificial intelligence syllabus.