How to Become an AI Developer
Hi everyone! In today, I’m gonna talk about how to become an Artificial Intelligence (AI) developer. Artificial Intelligence (AI) is the hottest area of techonology and demand is increasing axponentiallyfor AI developers. So, right now, we will discuss
- What is AI ?
- Who is an AI developer ?
- Responsibilities of an AI developer,
- Skills to become an AI developer
- Career and roles in AI.
If you are ready, let’s start.
What is Artificial Intelligence (AI) ?
AI is basically the ability of computer systems to mimic human behavior. Well, how works AI sytems. Firstly, AI systems learn from past datas. AI systems process these datas with its algorithms and finally try to mimic human behaviors by using outputs. I’m gonna mention machine learning (ML) algorithms after. If you are interested AI that probably you hear terms like machine learning (ML) or deep learning (DL). What is difference amoung of these terms. You can think like that AI is skull, ML is a brain that does main learning work and DL is a specific part of brain that make like visual, hearing etc. functions. If you are wondering more, you can look at my machine learning github repository here.
Who is an AI developer ?
AI developers build AI models using machine learinig algorithms and deep neural networks to draw business insights and these insights can be used to make business decisions that effect the entire organization. AI developers have a sound understanding of programming software developers as well as data science. They use different tools and techniques and they can process data and develop as well as maintain AI systems.
Responsibilities of an AI developer
AI developers have wide responsibility in business area. Some of these responisibilites are:
- Develop, test, deploy AI models.
- Convert machine learning models into APIs so that other aplications can use it.
- Build AI models from scratch and help product managers and stakeholders understand results.
- Build data ingestion and data transformation infrastructure.
- Automate infrastructure used by the data science team.
- Carry out statistical analysis and tune the results to derive better insights.
- Set up and manage AI development and production infrastructure.
- Coordinate work with data analyst and business analyst teams.
Skills to become an AI developer
Let’s talk about the skills required to become an AI developer.
Programming Skills
For becoming proficient is AI, it is mandatory for developers to learn programming languages such as Python, R to build and implement algorithms. If you look at my github repository, you can see that I use Python programming langauge. Because Python is general-purpose language and if you are new in programming or data science that I recommend python to you.
Linear Algebra, Probability and Statistical
Contrary to thought, AI is not just software. All machine learning algorithms and more are created with linear algebra, probability and statisctical in math. For instance, Linear Regression algorithm in machine learning is same time y = ax + b equation in math. Another example, you have to convert your datas to matrix and tensor shape in linear algebra before process it with algortihms. So, AI developers must have quite good math knowledge as in software. Of course, Math is so wide brache in positive sciences. Just it will be enough to know linear algebra, probability, statistical and basics general math for AI.
Knowledge on Spark and Big Data Technologies
AI Developers work with large volumnes of streaming, real-time production-level data at terabyte and sometimes perabyte scale. So they need to know on Spark and Big Data Technologies to make sense of this data. In here you can look at Apache Spark, Hadoop, Cassandra technologies.
Algorithms and Frameworks
Sure, another necessary requireds are algorithms and frameworks. Roughly, we can separate machine learning algorithms into two part. First is classical machine learning algorithms and second is deep neural networks. I’m not gonna indicate details. Because, I’ve written related post on medium before. Generally, classical machine learning algorithms are fed with structured data and some of algorithms are:
- Linear Regression
- Support Vector Machine (SVM)
- Random Forest
- Decision Tree
- K-NN
- Logisitc Regression
- XGBoost etc.
To learn more that you can look at my github repository.
Deep neural networks is a bit different rather than classical machine learning. Deep neural networks are fed with unstructured data, multiple layers and created by inspiring natural neural networks. Especially, if you have datas that involved images, text, or voices, you must use deep neural networks. Some algortihms are:
- Artificial Neural Networks (ANNs)
- Convulational Neural Networks (CNNs)
- Recurrent Neural Networks (RNNs)
- GAN etc.
To more knowledge:
Apart from that It’s important, you use frameworks as algorithms. Of course, I can not say like which frameworks is better or you must use this frameworks but I can suggest to you from my experience. I’m using VS Code for my standard coding and Anaconda Navigator for my artificial intelligence and data analysis works.
To learn more:
Communication and Problem Solving Skills
AI Developers need to communicate correctly to pitch their product and ideas to the stakeholders and should have excellent problem-solving skills to resolve obstacles for decision making and drawing business insights.
Career and Roles in AI
Careers in AI have grown exponentially to meet the demands of various industries. Here are some of the roles in AI.
AI Engineer
Work closely with Electrical Enginners and develop software to build AI robots.
AI Architect
Work, closely with clients to provide constructive business and system integration services and also create and maintain the entire architecture.
Machine Learning Engineer
Build predictive models using vast volumes of data and have in-depth knowledge of machine learning algorithms, deep learning algorithms and deep learning frameworks.
Data Scientist
Collect, clean, analyze and interpret large and complex datasets by leveraging both machine learning and predictive analytics.
BI Developer
Responsible for designing, modelling and analyzing complex data to identify business and market trends.
