Are you looking for Machine Learning certification courses but struggling with which course to take?
There are various machine learning courses available on various learning platforms. But they might confuse you about which is the best online machine learning course certification among them.
In spite of that, it is important to make sure that what you are opting for before you jump into machine learning courses.
So, taking that into consideration I did some research and listed out the top 11 online machine learning certification courses to help you out with the confusion. Let’s have a look at them!
Top Online Machine Learning Certification Courses: In A Nutshell (2023)
Here is a quick list of the best online machine learning certification courses.
|1.||Machine Learning Specialization||Coursera|
|2.||Machine Learning Nanodegree Program||Udacity|
|3.||Mathematics for Machine Learning Specialization||Coursera|
|4.||Professional Certificate in Machine Learning||edX|
|5.||Understanding Machine Learning||Pluralsight|
|6.||Advanced Machine Learning Specialization||Coursera|
|7.||Deep Learning A-Z||Udemy|
|8.||Supervised Machine Learning: Regression and Classification||Coursera|
|9.||Fundamentals of Machine Learning on AWS||Pluralsight|
|10.||Fundamentals of Google AI for Web-Based Machine Learning||edX|
|11.||Machine Learning with python||Coursera|
|12.||Machine Learning Cornell Certificate Program||eCornell|
So what are you waiting for? Let’s dive into the machine learning field.
1. Machine Learning Specialization (Coursera)
It is a beginner-level friendly course that helps you master the important AI concepts and covers practical machine learning skills.
This program not only covers the theoretical knowledge of machine learning but also provides practical aspects that are important to apply to real-world scenarios.
The course contains 3 sessions that guide you to complete an introduction to modern machine learning.
These sessions cover supervised and unsupervised learning that includes, decision trees, logistic regression, multiple linear regression, clustering, and recommender systems.
It also gives an in-depth knowledge of the practical approach to machine learning innovation and artificial intelligence.
Get introduced to statistical pattern recognition and data mining as well.
|Duration||3 months 9 hrs/week|
- Get proficient in various fundamentals of machine learning.
- Learn machine learning algorithms that build smart robots.
- Adapt models to real-world information and tasks.
- Get a sharable certificate after completion of the course.
2. Machine Learning Nanodegree Program with PyTorch (Udacity)
This course is a complete guide to different significant machine learning techniques. You will be covered with all unsupervised and supervised algorithms along with the data manipulation.
It is an intermediate-level program that expects basic Python programming knowledge, and proficiency in probability and statistics.
It will teach you advanced machine learning tools and techniques for your models. Also helps in do your performance evaluation of your models by A/B testing.
What’s more? You will also learn the deployment of models to the cloud of Amazon SageMaker.
- Get training from industry experts.
- Acknowledge important frameworks like Tensorflow, Keras, and Sklearn.
- Guide from industry experts.
- Learn performance evaluation of your models including A/B testing.
- Work on machine learning case studies.
3. Mathematics for Machine Learning Specialization (Coursera)
This beginner-level course focus on all linear mathematics that is important to machine learning. If Get your basics clear of linear algebra and mathematic equations with this course.
You will examine what linear algebra is and how it applies to data. Also, it covers what metrics and vectors are and how to use them.
This intermediate-level course necessitates prior Python and NumPy experience.
By the end of this course, you will gain total mathematical knowledge to master complete machine learning.
Develop your concepts of calculus and mathematics with this course.
|Duration||4 months (4 hrs/week)|
- Work on mathematical basics to use them in machine learning.
- Learn how orthogonal projection works.
- Get mastery over the applications in data science and machine learning.
- Learn PCA.
4. Professional Certificate in Machine Learning (edX)
This course contains various fundamental concepts of neural networks for unsupervised and supervised learning including deep learning. This is one of the best edX courses in the machine learning category.
You will learn the use of top deep learning libraries like PyTecch, Tensorflow, and Keras.
Also, it helps train and build different types of convolutional networks, autoencoders, deep architectures, and recurrent networks.
By end of this course, you get covered with all the applications of deep learning that are used in real-world scenarios.
|Duration||7 months (2-4 hrs/week)|
- Learn the application of Deep Learning to real-world situations.
- Hands-on experience with live projects, and assignments.
- Learn computer vision natural language processing, text analytics, and object recognition.
- Get Training from industry peers and experts.
5. Understanding Machine Learning (Pluralsight)
This is a perfect course for anyone even if you are a novice in machine learning.
The course is completely beginner-level and covers an overall introduction to machine learning.
You will be covered with the training and testing model and also how to use the model.
It is a complete understanding of open source programming language R. other than that, you will be covered with categorizing machine learning problems, styles of machine learning algorithms, and data pre-processing.
- Clear all your basics.
- Get training from leaders.
- Learn the complete machine learning process.
- In-depth sessions.
6. Advanced Learning Algorithms (Coursera)
Advanced learning algorithms are a thorough introduction to contemporary machine learning.
It covers supervised learning (logistic regression, multiple linear, decision trees, and neural networks), and unsupervised learning (dimensionality reduction, clustering, recommender systems).
You will learn the best techniques for machine learning and artificial intelligence used in Silicon Valley.
After completing this course, you will have learned fundamental theoretical ideas and acquired the practical skills necessary to apply machine learning swiftly and effectively.
Advanced Machine Learning Specialization is the ideal place to start if you want to get into AI or develop a career in machine learning.
|Duration||Approx 30 hrs|
- Get specialized in machine learning.
- Train a neural network with TensorFlow.
- Learn to use decision trees and various methods of tree ensembles.
- Get feedback on how to apply machine learning.
7. Deep Learning A-Z: Hands-On Artificial Neural Networks (Udemy)
This course is for you if you’re serious about mastering Deep Learning for applications in image identification, stock trading, business analytics, and more. It is one of the best Udemy courses in the machine learning category.
With its practical lessons, hands-on coding exercises, and six projects that address real-world issues, this course organically leads to a career in data science.
Additionally, you will receive the best in-course support, with the guarantee that their questions will be answered by a team of experts in no longer than 48 hours.
|Level||Beginner to Intermediate|
- Get mastery over machine learning on Python and R.
- Learn important topics like NLP and deep learning.
- Build powerful machine learning models.
- Perform powerful analysis.
8. Supervised Machine Learning: Regression and Classification (Coursera)
You will study the principles of machine learning and how to apply these methods to create practical AI applications in this beginner-friendly class.
In this course, you will learn about how to utilize the well-known machine learning packages NumPy and scikit-learn to create machine learning models in Python.
You will also learn to create and refine supervised machine learning models for binary classification and prediction problems, such as logistic regression.
Get pro in various machine learning skills like supervised learning, linear regression, logistic regression for classification, etc.
|Duration||approx .33 hours|
- Learng Python models that are using the best machine learning tools like Scikit-learn and NumPy.
- Train and build machine learning models that can be used for prediction.
- Learn binary classification tasks that include linear and logistic regression.
- Learn thorough interactive sessions.
9. Fundamentals of Machine Learning on AWS (Pluralsight)
In this course, you will learn how to use AWS machine learning tools to solve business challenges in Fundamentals of Machine Learning on AWS.
You will first examine what machine learning is and how it connects to deep learning and artificial intelligence. You’ll then discover how to spot and structure machine learning opportunities.
The entire machine learning process will then be revealed to you, including data retrieval, preparation, cleaning, and training as well as model deployment and monitoring.
After completing this course, you’ll be equipped with the abilities and knowledge of AWS machine learning tools required to address practical issues.
Additionally, this program will lay the groundwork for the AWS machine learning specialty certification.
|Duration||Approx 3 hrs|
- Get a pro in fundamentals of machine learning on AWS.
- Explore ML and how it supports AI and deep learning.
- Identify and frame opportunities for machine learning.
- Learn AWS machine learning technologies and artificial intelligence..
10. Fundamentals of Google AI for Web Based Machine Learning (edX)
This program aims to break through the hype and clarify what artificial intelligence actually is and isn’t.
To help you understand and use these technologies with others, it discusses the value of data and illustrates how data, machine learning, and artificial intelligence are related.
The curriculum begins with a Google AI for Anyone course that introduces the fundamentals of AI and ML as well as how AI is applied in daily life.
You will investigate what machine learning programming looks like at a high level, studying concepts like neural networks from Google AI specialists and practitioners.
- Learn to convert Python models to Tensor.js format.
- Use industry-standard models for NLP and object detection.
- Learn complete machine learning at your own pace.
- Get expert feedback and instructions.
11. Machine Learning with python (Coursera)
This course explores the fundamentals of machine learning using Python, a user-friendly and well-known programming language.
It discusses two key elements in this course:
- You will first discover what machine learning is used for and how it works in practice.
- You will also learn about machine learning approaches, including unsupervised vs. supervised learning, model evaluation, and machine learning algorithms.
In this course, you practice with actual machine learning instances and observe how technology influences society in unexpected ways.
You will receive an IBM digital badge in addition to the Coursera course certificate if you decide to take this course and successfully complete it.
|Duration||24 Hours in total|
- Study various examples of various industries of machine learning
- Learn steps to solve problems with machine learning
- Learn skills like Hierarchical Clustering, Python libraries.
- Get sharable certificate and training from industry experts.
12. Machine Learning Cornell Certificate Program (eCornell)
This Machine Learning program teaches you to implement the algorithms of Machine Learning using Python. The instructors of this course will teach you to form Machine Learning problems using your intuition and Maths, and after that, you will be able to approach these problems as a Data Scientist would.
The best part about this course is that it is instructor-led, meaning you will get access to the course materials, and an instructor will walk you through the entire course online.
The length of this course is two weeks, but if you follow the instructor-led training, then it will take you three and half months to finish the course. This certification program consists of seven different courses that you will be going through.
|Platform||eCornell (Cornell University)|
|Price||$3750 once or seven payments of $586|
|Duration||3.5 months (6-9 hours/week)|
- Machine Learning Certificate From Cornell University
- 12.6 CEUs (126 Development Hours)
- Learn to create image face recognition system
- Learn the foundational Linear Algebra
Final Thoughts: Best Online Machine Learning Certification (2023)
One of the well-known tech fields that go beyond programming and calls on math, problem-solving abilities, and even communication skills is machine learning.
In this article, I have covered all the top online machine learning certifications that will definitely help you to master machine learning.
I hope this list of certification courses was helpful.
If you are still in the confusion then here is my suggestion:
- If you are new to machine learning then Machine Learning A-Z is a great choice by Udemy.
- And if you want to get mastery over machine learning then, Professional Certificate in Machine Learning by edX might work perfectly for you!
Let us know in the comment section below which course did you choose.
- Shonda Rhimes MasterClass Review 2023: How Good Is It? - February 8, 2023
- How to Create an Infographic in Powerpoint (Detailed Guide) - February 8, 2023
- Top 10 Lowest Acceptance Rate Colleges (Updated 2023) - February 7, 2023