Today, artificial intelligence experts need to master multiple programming languages rather than one to effectively execute across various silos. There are so many use cases and more than one solution to every problem. Solving an issue and implementing these use cases requires deep knowledge in multiple one programming languages. Don’t you think?
Hence, in this article, we have discussed the top 5 languages that any expert needs to learn to complete an AI certification.
Our list of languages is obvious and it is highly likely that you were already looking forward to these languages. Let’s clear your confusion and help you explore why you need to learn python, lisp, Matlab, prolog, and java.
Best Programming Languages for AI Certification
If you wish to upsurge your artificial intelligence career and complete an AI certification course, get acquainted with the following programming languages. Here’s why you need to know these programming languages:
1. Python
Ever since its inception, python has been one of the most preferred programming languages in general too. In fact, it is so popular that it will cross the mind of every beginner at least once. Then, how can experts not know how to work in python?
Python is a robust language, which is widely utilized for artificial intelligence. This language offers you an array of libraries that provides flexibility in development. You further get access to a huge community of python that assists you whenever you get stuck. These communities are truly an inspiration and an amazing source of information. Its features including extensive frameworks and platform independence help in machine learning and deep learning developments.
2. Lisp
Lisp is the most popular language if you want to solve the inductive logic related project in artificial intelligence. We have included lisp in this list because it helps you with various functions such as symbolic programming support, no distinction in code and data, etc.
When you are using this programming language for your artificial intelligence projects, you will realize that this language is more extensible when compared to other languages. This improves your development efficiency.
Lisp, additionally, offers interactive programming and provides a feasible environment for incremental compilations, debugging, etc.
.3. Matlab
When you are working on projects that require complex math operations, Matlab is your programming language. With the help of this programming language, you can extend your capabilities to TensorFlow and Caffe. Simply put, using Matlab for programming means that you are ready for artificial intelligence without expertise in machine learning.
4. Java
Java is one of the most preferred programming languages across the globe. Everywhere around the world, developers learn Java programming at some point in their careers for better growth. Undoubtedly, Java helps artificial intelligence experts as well. Java allows AI development in various ways through its flexible nature, platform independence, and user-friendliness.
For instance, TensorFlow has Java as one of its supported languages. You can use Deep Java Library by Amazon for deep learning projects. In all, if Java is utilized effectively in the right manner, it is highly likely for this language to offer you profitable, feasible results. We believe this is the first language that you should embark upon after Python; if you don’t already know to program in Java.
5. Prolog
Prolog imparts some unique features like automatic backtracking and pattern matching. Needless to say, these features work like charm when used for artificial intelligence projects.
There are 4 fundamental terms of Prolog:
- True statements are given by Facts.
- Conditions and definitions are given by Rules.
- Analysis of where the statements stand is given by Goals.
- The final analysis is given by Queries.
The best thing about this language is that you can utilize it in two manners:
- The statistical manner which includes data mining, neural sets, machine learning, etc.
- The symbolic manner which is used for theorem proven, rule-based systems, and constraint-based methods.
Conclusion
In effect, every language that we have discussed so far is important to gain expertise in artificial intelligence and complete an AI certification. Hence, start from the first programming language and complete the list.
It is necessary to understand that artificial intelligence is a huge domain that requires expertise in multiple areas and languages. If you want to become an artificial intelligence expert, it is inevitable to avoid the above programming languages.
If you want to gain expertise in artificial intelligence, you can also complete an AI certification course from Global Tech Council. Check our website to understand what the course delivers.