Home Education Top 3 Most Popular Machine Learning Certification Courses in 2022

Top 3 Most Popular Machine Learning Certification Courses in 2022

Machine Learning is becoming famous day by day in the world of technology. Therefore, every IT company needs people who are well aware of Machine learning and are an expert in it as it helps them reach new heights of success.


What is Machine Learning?

Machine Learning (ML), a subset of artificial intelligence (AI), enables software applications to improve their propensity to predict outcomes without being specifically programmed. To forecast new output values, machine learning algorithms use historical data as input.

Many Machine Learning online courses teach in detail to strengthen your knowledge about it. Here are the top 3 most popular Machine Learning Certification Courses in 2022

1.    Professional Machine Learning Engineer

It is offered by Google and is one of the most challenging Machine Learning Certificate courses. It is divided into six sections and takes about 2 hours to finish.

Section 1: Framing Machine Learning problems

  • Converting business problems into machine learning use cases.
  • Defining Machine Learning problems.
  • Defining business success criteria.
  • Recognising potential challenges to the viability of machine learning solutions.

Section 2: Architecting Machine Learning solutions

  • Designing Machine Learning solutions that are dependable, scalable, and highly available.
  • Selecting suitable Google Cloud hardware elements.
  • Designing architectural solutions that adhere to security requirements across sectors and industries.

Section 3: Designing data preparation and processing systems

  • Exploring data (EDA).
  • Building data pipelines.
  • Developing features for input (feature engineering).

Section 4: Developing Machine Learning models

  • Building models.
  • Training models.
  • Testing models.
  • Scaling model training and serving.

Section 5: Automating and orchestrating Machine Learning pipelines

  • Designing and implementing training pipelines.
  • Implementing serving pipelines.
  • Tracking and auditing metadata.


Section 6: Monitoring, optimising and maintaining Machine Learning solutions

  • Monitoring and troubleshooting Machine Learning solutions.
  • Tuning performance of Machine Learning solutions for training and serving in production.

2.    Unsupervised Learning, Recommenders, Reinforcement Learning

It is a unique and informative three-week course and part of the Machine Learning Specialisation by Coursera. It teaches the following things how:

  • Build recommender systems with a collaborative filtering approach and a content-based deep learning method
  • Make use of unsupervised learning strategies, such as clustering and anomaly detection
  • Create a model for deep reinforcement learning.

3.    Structuring Machine Learning Projects

It will teach you how to create a productive machine learning project and practise making judgements as a machine learning project leader in the third course of the Deep Learning Specialisation.

For students with introductory machine learning knowledge, this course can be beneficial for them in various ways as it provides the “industry experience” that you might otherwise only acquire after years of Machine Learning work experience if you want to become a technical leader who can direct an AI team.

  • Machine Learning Strategy

You can streamline and optimise your Machine Learning production workflow by implementing strategic guidelines for goal-setting and utilising human-level performance to help define critical priorities.

  • Machine Learning Strategy

Gain intuition for splitting your data and when to use multitasking, transferring, and deep end-to-end learning. Develop time-saving error analysis procedures to analyse the most valuable options to pursue.


So, which course are you going to choose? An autonomous vehicle course or a machine learning course? Hope this blog helps you to decide better. All the best!


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