One of the most promising career paths in technology today is machine learning. As more businesses are keen to implement machine learning in their fields to remain competitive in the market, there is an increasing demand for AI and ML engineers at a rapid rate. But to succeed, you’ll need to possess a solid set of abilities and the best machine learning certifications that will enable you to create and implement efficient machine-learning models.
There is a strong need for AI engineers, as the U.S. Bureau of Labor Statistics estimates job growth of 21% for this area by 2024. (source- emeritus) This means that there is a high potential in the industry of artificial intelligence and machine learning engineering, so professionals must invest by learning important skills.
How has Machine Learning evolved over the years?
- AI Trends in Autonomous Vеhiclеs: The topic of autonomous vehicles has long piqued interest, and in 2024, artificial intelligence will advance the widespread adoption of these vehicles. Furthermore, AI/ML developments in computer vision and sensor technologies, along with machine learning algorithms, will improve the security and effectiveness of self-driving automobiles.
- AI-led Cybersecurity: Technology and the threats it poses are always evolving. By 2024, artificial intelligence and AI professionals will be essential to bolster cybersecurity initiatives. We already have artificial intelligence (AI)-powered threat detection systems like Darktrace, Tessian, Cyble Inc., etc., which are constantly observing network traffic and quickly detecting anomalies and possible security breaches.
- Use of AI in content creation: Artificial Intelligence is revolutionizing the process of creating content. We can anticipate seeing more AI-generated content in 2024, such as articles, videos, and artwork. Furthermore, Generative Adversarial Networks (GANs) can create visually stunning images and videos, and Natural Language Generation (NLG) algorithms promise to produce human-like written content with the help of AI professionals.
What makes learning AI ML a popular choice in 2024?
- Pursuing A Career in AI and Machine Learning Is Promising
Studying AI and ML can lead to a plethora of opportunities for developing cutting-edge technologies in a variety of fields, including computer security, image recognition, pharmacy, and facial recognition. This is because every company wants to incorporate AI Engineers into their team.
- Machine learning and artificial intelligence are versatile fields
Artificial Intelligence and Machine Learning find applications not only in computing and space-related fields but also in sectors closely associated with the general public, including banking, finance, healthcare, and automotive.
- Artificial Intelligence and Machine Learning Helps In Times of Disasters.
In addition to the help offered by governmental organizations, locals frequently look to social media for support when a natural disaster threatens their state or neighborhood. Videos that are taken by victims of natural disasters are also uploaded to social media platforms which use AI-enabled programs that serve as a channel for the distribution of disaster-related information.
Top 4 Machine Learning Skills for AI Engineers
1. Programming Language
Working with machine principles is not the same as dealing with simple tasks like writing simple programs or scripting web pages. It calls for a high level of programming knowledge and proficiency. An in-depth understanding of a programming language like Python is the most fundamental skill for an AI career.
Considering that it is more useful and simpler to learn than many other languages. The foundation of machine learning is Python. Although Java is necessary to work with Hadoop, Hive, and other technologies needed for a machine learning engineer, knowing C++ can help you write faster programs.
2. Machine Learning algorithms
What is a critical competency for a machine learning engineer to possess? Naturally, being familiar with all of the popular machine learning algorithms is crucial for determining which algorithms to use and when. Supervised, unsupervised, and reinforcement machine learning algorithms are the three main categories into which machine learning algorithms fall.
To be more specific, a few of the frequently used ones are the Random Forest, Apriori Algorithm, K Means Clustering, Naïve Bayes Classifier, Support Vector Machine, Linear Regression, and Logistic Regression. Thus, before starting your career as an ML engineer, it’s beneficial if you have a solid understanding of each of these algorithms and relevant Machine learning certifications.
3. Deep Learning and Neural Networks
The goal of deep learning, a quickly developing area of machine learning, is to create neural networks that can learn from vast amounts of unstructured data. Deep learning is especially helpful for tasks that need processing and comprehension of complex data, like natural language, videos, and images.
Deep learning techniques are one of the most crucial skills for certified AI engineers to have because they allow them to build more complex and accurate models that can be used in a variety of domains.
4. Data Visualization
Data visualization is a crucial aspect of machine learning. Python tools such as Matplotlib, Seaborn, or Plotly can help make data visualization possible. Understanding patterns, trends, and correlations is made easier with the help of data visualization.
When creating dashboards, popular data visualization tools like Tableau, Qlikview, Dash, and others are easily available and frequently utilized which are taught in AI and Machine learning engineer certifications. Possessing prior experience with data wrangling and dashboard building in any of the data visualization technologies is advantageous.
Machine learning engineers need to be eager lifelong learners, just like in most tech roles. You must be knowledgeable about the most recent practices, technologies, and frameworks. As an ML engineer, you should practice resilience, patience, and openness to learning. Global Market Insights projects that starting in 2024, the market for AI ML engineers would develop at a rate of about 35% CAGR, causing a high demand for their job roles. (source- global market insights) Although the journey is laborious and time-consuming, it is highly rewarding.