7 Best Certifications for Machine Learning You Must Know in 2024

Are you looking for the Best Certifications for Machine Learning? If yes, this article is for you. In this article, I listed the 7 Best Certifications for Machine Learning. So, give a few minutes to this article and find the Best Certifications for Machine Learning for you.

Now without further ado, let’s get started-

Best Certifications for Machine Learning

How I Chose These Courses

I picked these certifications based on the following:

• Course Content: What you’ll learn and how deep it goes.
• Duration: How long it takes to complete.
• Ratings and Reviews: What other students are saying.
• Extra Benefits: Things like mentorship, real-world projects, and career support.
• Cost: The price of the course and any discounts available.

1. AWS Machine Learning Engineer– Udacity

Rating-	4.7/5
Time to Complete-	5 months
Cost:	$250/month (with Udacity All Access subscription)
What You’ll Learn:	How to use AWS SageMaker for machine learning, including model design and deployment.

In this Nanodegree Program, there are 4 courses and 5 Projects. The whole Nanodegree program is full of quizzes and projects. After each lesson, there is one project, which you have to finish.

Udacity Machine Learning Engineer Nanodegree focuses on the latest best practices and capabilities that are enabled by Amazon SageMaker, including new model design/deployment features and case studies to which they can be applied.

Projects Covered-

1. Predict Bike Sharing Demand with AutoGluon
2. Build an ML Workflow on SageMaker
3. Image Classification using AWS SageMaker
4. Operationalizing an AWS ML Project
5. Capstone Project- Inventory Monitoring at Distribution Centers

Extra Benefits-

• You will get a chance to work on real-world projects with industry experts.
• You will get Project feedback from experienced reviewers.
• You will also get Technical mentor support.

Pros:

• Hands-on projects with real-world applications.
• Feedback from experienced reviewers.
• Technical mentor support.

Cons:

• Can be expensive.
• Requires some prior knowledge in machine learning and Python.

Who Should Enroll?

• Those with a previous understanding of Machine Learning algorithms and Python Programming knowledge.

Interested in Enroll?

If yes, then check out the details here- AWS Machine Learning Engineer

2. Machine Learning Specialization– Coursera

Rating-	4.9/5
Time to Complete-	3 months(If you spend 9 hours/week)
Cost:	$49/month
What You’ll Learn:	Basics of machine learning, neural networks, and unsupervised learning techniques.

In this specialization program, there are 3 courses. In the first course, you will learn machine learning basics such as supervised learning, unsupervised learning, regression, and classification.

In the second course, you will learn about neural networks, how to train your model in TensorFlow, and the practical and very commonly used learning algorithm the decision tree.

In the last course, you will learn unsupervised learning algorithms such as clustering and anomaly detection, Recommender systems, and Reinforcement learning.

Extra Benefits-

• You will get a Shareable Certificate. Along with that, you will learn various case studies and applications. That will teach you how to apply machine learning algorithms to building smart robots.
• You will also learn text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and others.

Pros:

• Certificate you can share on LinkedIn.
• Covers a broad range of topics with practical case studies.

Cons:

• Requires a commitment of time.
• May be too basic if you already have some experience.

Who Should Enroll?

• This Course is Most Suitable for Complete Beginners. But people with a basic understanding of ML can also enroll.

Interested in Enroll?

If yes, then check out the details here- Machine Learning Specialization

3. Machine Learning Scientist with Python– DataCamp

Rating-	NA
Time to Complete-	93 hours
Cost:	$20/month (with DataCamp subscription)
What You’ll Learn:	Supervised and unsupervised learning, natural language processing, and image processing.

This is a career track offered by Datacamp. There are 23 courses in this career track and begin with supervised learning with scikit learn. In this course, you will learn supervised, unsupervised, and deep learning.

Along with this, you will learn natural language processing, image processing, and libraries such as Spark and Keras.

In this career track, you will also learn how to approach and win Kaggle competitions.

Pros:

• Comprehensive coverage of many ML topics.
• Includes tips for competing on Kaggle.

Cons:

• Can be pricey if you’re not a DataCamp subscriber.
• Limited information on the impact on career.

Who Should Enroll?

• Those who are a beginner in Machine learning and looking for step-by-step career guidance.

Interested in Enroll?

If yes, then check out the course details here- Machine Learning Scientist with Python

4. Intro to Machine Learning with TensorFlow– Udacity

Rating-	4.7/5
Time to Complete-	3 months (if you spend 10 hrs/week)
Cost:	$250/month (with Udacity All Access subscription)
What You’ll Learn:	Supervised and unsupervised learning, and how to use TensorFlow for machine learning.

This is a Nano-Degree Program. There are 3 courses in this program. In the first course, you will learn supervised learning and the algorithms of supervised learning such as Regression, Perceptron Algorithm, Decision Trees, Naive Bayes, SVM, etc. Along with the supervised algorithms, you will also understand the training and testing procedure and data visualization basics.

In the next course, you will understand neural network basics and learn how to implement gradient descent and backpropagation in Python.

The last course is all about unsupervised learning and covers the K-means algorithm, Single Linkage Clustering, Gaussian Mixture Models, etc.

All three courses have one project. Along with the projects, there are quizzes and practice sets throughout the program.

Extra Benefits-

• You will get a chance to work on Real-world projects.
• You will get Technical mentor support.
• Along with that, you will get Career services.

Who Should Enroll?

• Those who have Intermediate Python programming knowledge and familiar with data structures like dictionaries and lists.
• And those who have basic knowledge of probability and statistics.
• This program is especially good for those who have experience in Python but have not yet studied Machine Learning topics.

Pros:

• Real-world projects and career services.
• Technical mentor support.

Cons:

• High cost.
• Intermediate Python knowledge required.

Interested in Enroll?

If yes, then check out the course details here- Intro to Machine Learning with TensorFlow

5. Applied Machine Learning in Python– Coursera

Rating-	4.6/5
Time to Complete-	34 hours
Cost:	$49 (one-time payment)
What You’ll Learn:	Supervised learning algorithms, model evaluation, and advanced concepts like neural networks.

This is another machine learning course with Python. This course has a 4-week study plan. In the first week, you will learn machine learning basics such as tools used in Python for machine learning, K-Nearest Neighbors Classification, etc.

Next, you will learn supervised machine-learning algorithms and understand Overfitting and Underfitting, K-Nearest Neighbors, Linear Regression, Logistic Regression, Support Vector Machines, Cross-Validation, and Decision Trees.

Model evaluation is the essential step in machine learning and you will understand Confusion Matrices & Basic Evaluation Metrics, Precision-recall and ROC curves, Multi-Class Evaluation, etc.

The last part of this course covers some advanced concepts of supervised learning such as Naive Bayes Classifiers, Random Forest, Gradient Boosted Decision Trees, Neural Networks, Dimensionality Reduction, and Manifold Learning.

Extra Benefits-

• You will get a Shareable Certificate upon completion.
• Along with this, you will get Course Videos & Readings, Practice Quizzes, Graded Assignments with Peer Feedback, Graded Quizzes with Feedback, and Graded Programming Assignments.

Who Should Enroll?

• Those who have previous knowledge in Data Visualization using Python.

Pros:

• Certificate upon completion.
• Covers both basic and advanced machine learning concepts.

Cons:

• Shorter duration means less in-depth coverage.
• Focuses mainly on Python.

Interested in Enroll?

If yes, then check it out here– Applied Machine Learning in Python

6. Python for Data Science and Machine Learning Bootcamp– Udemy

Rating-	4.6/5
Time to Complete-	25 hours
Cost:	$109.99 (often discounted)
What You’ll Learn:	Implementing machine learning algorithms, data analysis with Pandas, and statistical plotting with Seaborn.

This is also one of the most popular courses available at Udemy. This course will teach you how to implement Machine Learning Algorithms. This course will also teach you how to use Pandas for Data Analysis, and Seaborn for statistical plots.

Extra Benefits-

• You will get a Certificate of Completion.
• You will also get 13 articles and 5 downloadable resources.
• Along with that, you will get lifetime access to the course material.

Who Should Enroll?-

• Those who have at least some programming experience.

Pros:

• Lifetime access to course material.
• Includes articles and downloadable resources.

Cons:

• May not cover advanced ML topics in depth.
• Focuses primarily on Python.

Interested in Enroll?

If yes, then check out the details here- Python for Data Science and Machine Learning Bootcamp

7. Machine Learning, Data Science, and Deep Learning with Python– Udemy

Rating-	4.6/5
Time to Complete-	14.5 hours
Cost:	$109.99 (often discounted)
What You’ll Learn:	Basics of statistics, machine learning algorithms, deep learning, and generative models.

This is another Python-oriented course for machine learning. In this course, first, you will learn statistics and probability basics. Next, you will learn machine learning algorithms such as K-Means Clustering, Decision Tress, SVM, etc.

The course also covers dimensionality reduction techniques, bias/variance tradeoffs, feature engineering, Apache Spark, Deep Learning, Neural Networks, and Generative models.

If you are a beginner in Python, then you will learn Python basics too. After completing this course, there is one final project, which you need to complete.

Extra Benefits-

• You will get a Certificate of Completion.
• You will also get 6 articles and 1 downloadable resource.
• Along with that, you will get lifetime access to the course material.

Who Should Enroll?-

• Those who know at least high school level math and have some prior coding experience.

Pros:

• Covers a broad range of topics.
• Includes basics for Python beginners.

Cons:

• Short course length.
• Requires some prior coding experience.

Interested in Enroll?

If yes, then check out the details here- Machine Learning, Data Science, and Deep Learning with Python

Course Comparison for Machine Learning Certifications

S/N	Certification	Rating	Duration	Cost	Main Topics
1	AWS Machine Learning Engineer – Udacity	4.7/5	5 months	$250/month (with Udacity All Access subscription)	AWS SageMaker, ML Workflow
2	Machine Learning Specialization – Coursera	4.9/5	3 months (9 hours/week)	$49/month	ML Basics, Neural Networks
3	Machine Learning Scientist with Python – DataCamp	NA	93 hours	$20/month (with DataCamp subscription)	Supervised/Unsupervised Learning, NLP
4	Intro to Machine Learning with TensorFlow – Udacity	4.7/5	3 months (10 hours/week)	$250/month (with Udacity All Access subscription)	TensorFlow, ML Algorithms
5	Applied Machine Learning in Python – Coursera	4.6/5	34 hours	$49	ML Algorithms, Model Evaluation
6	Python for Data Science and Machine Learning Bootcamp – Udemy	4.6/5	25 hours	$109.99	ML Algorithms, Data Analysis
7	Machine Learning, Data Science, and Deep Learning with Python – Udemy	4.6/5	14.5 hours	$109.99	ML Algorithms, Deep Learning

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Recommendations Based on Experience Level

For Beginners

If you’re new to machine learning, these courses are great for starting out:

1. Machine Learning Specialization – Coursera
   • Why: This course covers the basics of machine learning and how to use it in real-world situations. It’s perfect for beginners who want a solid introduction to the field.
2. Python for Data Science and Machine Learning Bootcamp – Udemy
   • Why: This course teaches the basics of machine learning and how to use Python tools like Pandas. It’s ideal if you already have some programming knowledge and want to learn machine learning.

For Intermediate Learners

If you have some experience and want to go deeper, try these:

1. Applied Machine Learning in Python – Coursera
   • Why: This course goes into more detail about machine learning algorithms and how to evaluate them. It’s great if you want to build on your basic knowledge and work on real projects.
3. Intro to Machine Learning with TensorFlow – Udacity
   • Why: This course covers advanced machine learning topics using TensorFlow. It’s good for those who are comfortable with Python and want to learn more complex techniques.

For Advanced Learners

If you’re experienced and want to explore advanced topics, consider these:

1. AWS Machine Learning Engineer – Udacity
   • Why: This program focuses on using AWS for machine learning. It’s perfect if you want to work on advanced projects and learn about cloud-based machine learning.
2. Machine Learning Scientist with Python – DataCamp
   • Why: This track covers a wide range of machine learning techniques, including natural language processing and image processing. It’s great if you want to refine your skills and compete in machine learning challenges.

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I hope these recommendations help you find the right course for your level and goals. If you have any questions or need more advice, feel free to ask in the comments!

FAQ

And here the list ends. I hope these Best Certifications for Machine Learning will help you. I would suggest you bookmark this article for future referrals. Now it’s time to wrap up these Best Certifications for Machine Learning.

Conclusion

In this article, I tried to cover the 7 Best Certifications for Machine Learning. If you have any doubts or questions, feel free to ask me in the comment section.

All the Best!

Enjoy Learning!

Thank YOU!

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Though of the Day…

‘ Anyone who stops learning is old, whether at twenty or eighty. Anyone who keeps learning stays young.

– Henry Ford