Top Machine Learning Certifications

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As artificial intelligence (AI) continues to revolutionize many sectors, the vital field of machine learning rises in importance. Because of this, there is a high demand for ML engineers as companies look to implement it into their processes and products. It is quickly becoming one of the top jobs on the market.

Given all of this, a machine learning certification can open up many opportunities.

Here is a look at the top machine learning certifications:

1. IBM Machine Learning Professional Certificate

This certificate from IBM is aimed at those looking to develop the skills and experience necessary for a career in Machine Learning. The program consists of 6 courses that help you develop an understanding of the main algorithms and their uses. While the intermediate program is useful for anyone with computer skills and an interest in leveraging data, some background in Python programming, statistics, and linear algebra is recommended.

Here are the main aspects of this certification:

2. IBM AI Engineering Professional Certificate

Another one of the top machine learning certifications, this 6-course Professional Certificate is aimed at giving individuals the tools necessary to succeed as an AI or ML engineer. It covers fundamental concepts of Machine Learning and Deep Learning, such as Supervised and Unsupervised Learning. You will also learn how to build, train, and deploy deep architectures.

Here are the main aspects of this certification:

  • 6-course program
  • Supervised and Unsupervised Learning with Python
  • Apply popular Machine Learning and Deep Learning libraries like SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow
  • Tackle problems involving Object Recognition, Computer Vision, Image and Video Processing, Text Analytics, and NLP
  • Digital badge from IBM upon completion
  • Duration: 8 months, 3 hours/week

3. Machine Learning by Stanford University

This class offered by Stanford University teaches the most effective machine learning techniques, and you get the chance to implement them to work for yourself. The class also provides the knowledge needed to apply the techniques to new problems. It is a broad course and an introduction to Machine Learning, Datamining, and Statistical Pattern Recognition.

Here are the main aspects of this course:

  • Topics like Supervised and Unsupervised Learning
  • Numerous case studies and applications
  • Applying learning algorithms to build Smart Robots, Text Understanding, Computer Visions, Medical Informatics, Audio, and Database Mining
  • Shareable certificate upon competition
  • Duration: 60 hours

4. Getting Started with AWS Machine Learning

This short but impressive course helps you get started with AWS Machine Learning. It covers important topics such as Machine Learning on AWS, Computer Vision on AWS, and Natural Language Processing on AWS. There are several modules within each topic, and they cover various ML concepts and AWS services.

Here are the main aspects of this course:

  • Insights from experts
  • An intermediate-level course
  • Key problems that ML can address and solve
  • Building intelligent applications with Amazon AI services such as Amazon Comprehend, Amazon Rekognition, and Amazon Translate
  • Build, train, and deploy models using Amazon SageMaker with built-in algorithms and Jupyter Notebook instance
  • Look at AWS DeepLens, the first ever deep learning enabled video camera
  • Duration: 8 hours

5. Machine Learning by Georgia Tech

This free course on Udacity is offered by Georgia Tech. The first part of the course if focused on Supervised Learning, the second part is on Unsupervised Learning, and the final part is on Reinforcement Learning. It is recommended that you have a strong familiarity with Probability Theory, Linear Algebra, and Statistics, as well as some experience in programming and with neural networks.

Here are the main aspects of this course:

  • Intermediate level
  • Learning content, interactive quizzes, industry experts, and self-paced
  • Real-world projects involving topics like Asset Management and Trading Signal Generation
  • Supervised Learning, Unsupervised Learning, and Reinforcement Learning
  • Duration: 4 months

Machine learning is one of the fastest growing areas in technology, and it is becoming increasingly important in the job market. According to the World Economic Forum, the growth of AI could create 58 million net new jobs in the next few years, and while there are millions of AI engineers needed, there are currently around 300,000.

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