Last updated on October 12th, 2022 at 06:55 am
Technological advancements are taking the world by storm. Scientific innovations are changing lives drastically. This is the age of Artificial Intelligence (AI) and Machine Learning (ML). Days are not far when we will have a replacement of human force with robots that have features just like humans.
In fact, many industries are already implementing such changes in their work. Due to the increased demands for such technology, artificial intelligence and machine learning courses are being offered by many institutes all over the world.
However, anyone and everyone cannot take up an AI certification course. There are certain subjects and concepts which you have to know to be able to take up an AI course. In this article, we will discuss that in detail.
5 things about which you must know before choosing an AI certification course
Before choosing to enroll in an artificial intelligence course, it is important that you have clear concepts about certain subjects. They are as follows:
Thorough knowledge of mathematics - While studying artificial intelligence, you will need to have a thorough knowledge and a deep understanding of mathematics. This conceptual understanding helps in writing algorithms and programs for AI. It is important to have a basic understanding of mathematical concepts like calculus, linear algebra and probability.
In machine learning, linear algebra is a compulsory subject to know. The dynamics between ML and linear algebra are explicable via certain abstract concepts like matrix operations and vector spaces.
For building a machine learning model, calculus is inevitable. Along with having a basic knowledge of differentiation and integration, you should also know gradient or slope, partial derivatives and chain rules.
Good knowledge of programming language - If you are aiming to become proficient in artificial intelligence, then it is important that you have fair ideas and knowledge of various programming languages like Java, Python and C++. This is because algorithms of machine learning are put into effect with the help of codes only.
As per tech experts, the best language to learn for artificial intelligence is Python. With the help of this language, you will be able to create extremely complex algorithms quite easily. The programming language has a concise and easily readable syntax. It is almost the same as writing commands in the English language. There are different libraries in Python and they are particularly useful for machine learning and artificial intelligence.
Knowledge of algorithms and data structures - When it comes to ML and AI, having a basic understanding of data structure and algorithms is mandatory.
Learning data structures is essential for learning data collection and for performing various kinds of operations on collected data.
On the other hand, algorithms are a set of step-by-step instructions, which are written in that order for accomplishing and completing a specific and predefined work. Algorithms are expressed in the form of flow charts or pseudocode.
Slight concept of machine learning - Machine learning is actually a subset of artificial intelligence. In machine learning certification, you mainly study and learn about computer algorithms. In the ML algorithm, you create a mathematical model, which is based on some kind of sample data to make decisions without being programmed explicitly.
Statistics - Statistics mainly deals with data - right from collection to analysis, from sorting to interpretation, and finally presentation. Therefore, its importance in machine learning is quite obvious and evident. A candidate studying AI and ML should be familiar with outliers, mean, standard deviation, median, and histogram.
Conclusion
Lucrative career opportunities are waiting in the artificial intelligence and machine learning industry. Enroll in the best course on the subjects from a reputed institute and obtain a globally-accredited certification to fly high in your career. Check out the official website of Imarticus Learning for more details.
