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How to Become a Machine Learning Engineer

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January 6, 2022

  • In Banking & Finance – Machine learning is used to identify and prevent fraudulent financial transactions, as well as to identify opportunities for investment.
  • In Transportation – The self-driving cars being built by Google and Tesla are powered by machine learning systems, including deep learning technology so that they can drive safely without human input.
  • In Healthcare – Medical professionals have begun to use machine learning solutions to detect the presence of diseases. 
  • In Manufacturing – Manufacturers use machine learning processes to reduce loss and operating costs and to increase production capacity.
  1. Machine learning engineers get to play an incredibly important role in modern businesses, helping them develop cutting-edge, next-generation technologies.
  2. This is an excellent career for anyone looking to earn a considerable salary, as Indeed.com reports the average base salary for machine learning engineers was $150,961 per year, as of February 9th, 2023.
  3. Demand for machine learning engineers is set to explode, with Forbes recently reporting that demand for AI and machine learning job skills is predicted to grow by 71% over the next 5 years.
  • Utilizing machine learning to perform a variety of different tasks, including complex processes like image analysis and reconstruction.
  • Analyzing and applying machine learning principles for reasoning processes and uncertainty.
  • Solving a variety of complicated problems by implementing advanced machine learning and AI-driven solutions.
  • Designing and then building machine learning and AI-based systems and solutions to perform complex tasks that model, but outperform human behavior.
  • Evaluating and improving technologies, systems, and solutions that rely on machine learning and AI processes.
  1. Mastery of Computer Science Fundamentals – You need knowledge, awareness, and expertise in several fundamentals of computer science, including data structures, algorithms, computability and complexity, and computer architecture, as all of these are critical to the role of machine learning engineer.
  2. Computer Programming Skills – You’ll have to build computer programming skills, including the ability to apply, implement, modify, and address the computer science fundamentals listed above while performing programming tasks.
  3. Advanced Probability and Statistics Skills – Machine learning algorithm technology is rooted in probabilities and techniques derived from probability and statistics, so you’ll need to develop expertise in each of these areas. 
  4. Data Modeling Skills – Many machine learning algorithms utilize data modeling processes, so you’ll need to be capable of evaluating data sets to uncover useful patterns, correlations, clusters, and other relationships in fields of data to evaluate and predict outcomes of various data modeling techniques. 
  5. Software Engineering and Systems Design Skills – Typically, machine learning engineers deliver software solutions, so to be successful in this role, you’ll want to develop an advanced understanding of software engineering best practices.
  6. Experience Using Machine Learning Algorithms and Libraries – Machine learning algorithms rely on deep-learning libraries like Tensorflow, Theano, Spark MLlib, H2O, etc., and you’ll need to be familiar with their use so that you can apply them appropriately when developing a suitable model for machine learning applications.
  • Analyzing systems to monitor and control technology-driven development projects.
  • Establishing and achieving objectives using techniques related to AI and machine learning reasoning and uncertainty.
  • Applying logic, probably analysis, and machine learning concepts to solve complicated technological problems.
  • Utilizing machine learning best practices and principles to build applications that perform data processing, data mining, speech recognition, image recognition, robotic control, and other similar functions.
  • Use machine learning principles and techniques to solve complex business problems.
  • Model human behavior with advanced AI and machine learning solutions. 
  • Implement solutions that utilize AI and machine learning principles. 
  • Evaluate the performance of applications based on AI and machine learning best practices.
  • Use principles and techniques associated with modern software development.
  • Springboard’s own Machine Learning Bootcamp
  • Amazon’s AWS Certified Machine Learning Specialty
  • Google’s Professional Machine Learning Engineer Certification
  • Microsoft’s Azure AI Engineer Certification
  • IBM’s Machine Learning Professional Certificate
  • No requirements to show up at set times or in physical locations
  • Monthly class starts
  • Accelerated courses
  • A #10 ranking for Best Online Colleges for ROI from OnlineU.
  • A #1 ranking for Best Online Colleges & Schools in Colorado from Best Accredited Colleges.
  • A #1 ranking for Best Online Colleges in Colorado from Best Colleges.
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