The exponential rate at which technology is evolving makes it so that some professions seem to outweigh most in our society today. Machine learning engineers, in particular, play a unique role in the direction that human technology is heading.
Understanding the nature of how engineering in this field works will allow you to decide whether taking up a course in machine learning is worth it or not. Let’s learn what skills are required for Machine Learning to become a Machine Learning engineer.
It won’t be long before machine learning expands its influence beyond the typical applications and starts saving lives. Scientists and engineers predict that machine learning will eventually become advanced enough to help detect and cure diseases. Healthcare is only the beginning, and machine learning will soon become a vital part of every industry worldwide.
Prerequisites of Machine Learning
You must understand the different aspects of what an individual is required to learn to start pursuing an engineering career in machine learning. It may seem daunting to most people the number of lessons and information needed to succeed in such a complicated industry. With proper dedication, hard work, and the right skills, becoming a machine learning engineer is possible.
Some of the standard requirements include having a bachelor’s degree in any course related to machine learning. Most instructors would advise pursuing a master’s or even doctorate in computer vision, neural networks, or deep understanding to increase one’s assets on the road to becoming a machine learning engineer.
It shouldn’t be a surprise that machine learning requires a lot of knowledge in mathematics. Some of the most talented and decorated engineers in the industry hold several degrees in mathematics which explains why popular machine learning applications are related to the understanding of data in ones and zeroes.
Listed below are some of the basic knowledge and information that will help answer the question, “What skills required for machine learning?” as well as a roadmap for the lessons you need to tackle before applying for a course in machine learning.
- Statistics: Tools and techniques learned in statistics allow engineers to understand the outcome of different data sets better. The transformation of data into meaningful information is essential to the success of any AI-based system that benefits from machine learning. Inferential and descriptive statistics are two of the common lessons that will be brought up consistently while learning machine learning. We’ve listed the best courses to learn Statistics and Probability for Machine Learning.
- Linear Algebra: Different vectors, matrix systems, and linear transformations drive different operations in machine learning. Linear algebra helps engineers to perform better functions in various datasets to produce a better outcome.
- Calculus: Knowledge in the integrations and different variables allow machine learning engineers to build models for future algorithms. Calculus is a skill required for machine learning engineers in machine learning and any other related field.
- Probability: Predicting the likelihood of an event happening will help engineers gauge the outcome of different occurrences. Understanding what may or may not occur will become the foundation for any machine learning application.
- Programming Language: Most people know that programming plays a considerable role in machine learning. Aside from the essential languages such as Python, SQL, Java, and C++, here are some of the additional tools and programs you can learn on your own. Programming language is a skill required for machine learning jobs in some of the biggest companies in the world today.
- Spark and Hadoop
- R Programming
- Apache Kafka
- Google Cloud ML Engine
- Amazon Machine Learning
- PytorchJupyter Notebook
- IBM Watson
Machine learning engineers also need to process, analyze, and extract valuable information from different sets of data. Adapting to algorithms, models, and outcomes is a must for any engineer, especially those in the machine learning industry.
Best Courses to Learn Machine Learning
To equip you with the best resources to learn Machine Learning we’ve listed the top course to take online. All the courses are self-paced with several mini projects for practice.
- Become a Machine Learning Engineer Nanodegree Program – Udacity
- Machine Learning for All – Coursera
- Machine Learning for Everyone – Datacamp
- Machine Learning by Columbia University
- Introduction to Machine Learning with Pytorch – Udacity
- Machine Learning with Python – Coursera
- Machine Learning for Data Science and Analytics Course – EdX
Once you’ve completed these courses, you may take additional training by working on guided machine learning projects.
Benefits of Machine Learning
One of the goals of machine learning engineers is to help create a better future for humans. This is done through the invention of different artificial intelligence algorithms to support other sectors. Engineers might say that machine learning is best used in scenarios where vast amounts of data with increasing complexity are processed. That’s because machine learning strives to imitate the human brain.
Artificial intelligence systems learn by observing, and machine learning algorithms enable them to operate with minimal risk. However, ML is far from perfect, and there are also disadvantages to its applications, but the positives significantly outweigh the negatives, making it an irreplaceable engineering field.
To better understand the real-world benefits of machine learning, here are some of the business applications of the systems that make use of machine learning algorithms.
- Sales Forecast and Simplification of Product Marketing: Machine learning allows different business sectors to advertise and market their products efficiently and even help predict various sales trends. The application for machine learning in this field is beneficial to the success of any company. Here are some of the techniques and processes that ML utilizes in Sales Forecast and Product Marketing.
- Unlimited Consumption of Data from Multiple Sources
- Analysis, Prediction, and Processing
- Interpretation of Customer Behaviors
- Prediction of Healthcare Related Issues and Medical Diagnosis: Like what was said at the start of this article, machine learning will eventually become advanced enough to predict and cure diseases. Today, high-risk patients in medical facilities are much harder to identify when relying solely on human employees’ intelligence, which makes artificial intelligence systems even more crucial to medical protocols.
- Increasing Efficiency in Manufacturing: Machine learning algorithms help greatly with automated factories to give workers opportunities to work on other things. At the same time, production is being supported by systems that have machine learning embedded into them. A skill required for machine learning jobs is to adapt to different field applications, and the manufacturing industry is one of them.
Salary of Machine Learning
The road to becoming a machine learning engineer may be difficult. Still, once you attain a position in any company, the hefty salary will be more than enough to compensate you for the hard work you’ve done to reach that point.
- Machine Learning Engineer with 0-4 years of experience = Approximately $97,090 with potential bonuses and profit-sharing, increasing the amount to at least $130,000.
- Machine Learning Engineer with 5-9 years of experience = Approximately $112,095 with potential bonuses and profit-sharing, increasing the amount to at least $160,000.
- Machine Learning Engineer with 10+ years of experience = Approximately $132,500 with potential bonuses and profit-sharing, increasing the amount to at least $181,000.
Summary: Skill Required for Machine Learning Jobs
Pursuing a career in Machine Learning may not be the easiest thing to do, but hopefully, you can make that decision today with the help of this article. Machine learning engineers are some of the most in-demand jobs in the industry today, and succeeding in this field will not only secure your future but will also allow you to help our society grow. We hope this article on what skills required for Machine Learning was helpful to you.
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