Datamation content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More.
Machine learning certification is a recognized accreditation of a data analyst or a data scientist’s machine learning skills and knowledge. Beginners and experienced professionals alike can acquire machine learning certifications to boost their knowledge and gain accreditation for their skills.
The demand for machine learning (ML) skills is on the rise, driven by the increasing importance of high-performance technologies like artificial intelligence (AI) across various sectors. Jobs in the machine learning field are booming due to its broad application in healthcare, education, marketing, retail, e-commerce, financial services, and other industries.
As organizations seek to make effective use of data, there’s a growing need for skilled professionals who can design, develop, and deploy ML models. Online learning platform Coursera features a deep collection of courses to build those skills—here are our picks for the best Coursera machine learning certifications to help you develop the expertise you need to succeed.
Table of Contents
Top 9 Coursera Machine Learning Course Comparison
The following table shows at a glance the salient details about each course, including its provider, duration, and cost.
| Course | Provider | Duration | Cost |
|---|---|---|---|
| Machine Learning Specialization |
|
|
$59/month |
| Post-Graduate Certificate, Data Science & Machine Learning | IIT Roorkee | Six months | $1,500 |
| Post-Graduate Certificate, Machine Learning for Finance | IIT Roorkee | Six months | $1,200 |
| Professional Certificate, Preparing for Google Cloud Certification: Machine Learning Engineer |
|
$59/month | |
| Professional Certificate, Machine Learning | IBM |
|
$59/month |
| Machine Learning with Python | IBM | 12 hours | $59/month |
| Machine Learning Specialization | University of Washington |
|
$59/month |
Machine Learning Specialization
Provider: Stanford University and DeepLearning.AI
Level: Beginner
Shareable Certificate: Yes
The Machine Learning Specialization is a collaboration between Stanford University Online and DeepLearning.AI. This beginner-friendly program teaches the fundamentals of machine learning and its application in real-world AI projects. It covers supervised and unsupervised learning techniques and best practices in AI and machine learning innovation, and provides practical skills to tackle real-world challenges.
Why We Picked It
This specialization stands out for its comprehensive approach to introducing machine learning concepts while providing hands-on experience in real-world projects, making it an ideal starting point for beginners.
Skills Acquired
Successful certification takers will be equipped to build ML models using NumPy & scikit-learn. They will learn to train supervised models for prediction and binary classification, apply best practices in ML development, use unsupervised learning techniques such as clustering and anomaly detection, create neural networks with TensorFlow for multi-class classification, and implement decision trees and tree ensemble methods. In addition, they will construct recommender systems with collaborative filtering and content-based deep learning and develop deep reinforcement learning models.
Best For
- Beginners who want to solidify their ML understanding
Pre-Requisites
- Basic coding
- High school-level math
Duration and Price
- Two months, 10 hours per week
- $59 per month for a Coursera subscription
Post-Graduate Certificate, Data Science and Machine Learning
Provider: Indian Institute of Technology, Roorkee
Level: Beginner
Shareable Certificate: Yes
IIT Roorkee’s post-graduate certificate in data science and machine learning provides a comprehensive program focusing on industry-standard tools and methodologies while covering basic topics such as data science, machine learning, mathematics, and data visualization. It is designed for people who have no prior coding expertise and begins with the fundamentals of data science and machine learning.
Why We Picked It
This certificate program provides a holistic approach to covering essential topics in data science and machine learning.
Skills Acquired
Certification takers will learn to analyze real world data, create analytical models, and derive actionable data insights, as well as the basics of data science, mathematics for data science, Python programming language, exploratory data analysis, data visualization, and machine learning.
Best For
- Beginners without prior coding experience to acquire foundational knowledge in data science and ML
Pre-Requisites
- Exposure to high school mathematics
Duration and Price
- Six months
- $1,500
Post-Graduate Certificate, Machine Learning For Finance
Provider: Indian Institute of Technology, Roorkee
Level: Beginner
Shareable Certificate: Yes
IIT Roorkee’s post-graduate certificate in machine learning for finance is designed for finance professionals who want to incorporate AI/ML and data science into their jobs. It highlights the use of AI-based models in finance to address real-world wealth management difficulties and improve investment decision-making.
Why We Picked It
The program specializes in focusing on applied ML techniques in the finance sector, making it ideal for finance professionals seeking to advance their skills in this area.
Skills Acquired
Students learn about ML, Python, and R programming, wealth management, financial risk management, algorithmic portfolio management, trading strategies, and security market prediction.
Best For
- Specializing in machine learning in finance
Pre-Requisites
- High school mathematics
Duration and Price
- Six months
- $1,200
Professional Certificate, Machine Learning Engineer
Provider: Google
Level: Intermediate
Shareable Certificate: Yes
This course teaches the necessary skills for success in a machine learning engineering role. It covers designing, building, and deploying ML models with Google Cloud technologies. It also prepares certification takers for the Google Cloud Professional Machine Learning Engineer certification exam, highlighting its significance in the context of other Google Cloud certifications.
Why We Picked It
This Google course is handpicked for its specialized focus on preparing individuals for a machine learning engineering role using Google Cloud Technologies, making it an excellent choice for those who are knowledgeable in the Google data space.
Skills Acquired
Upon successful completion of the course, students will acquire skills in Tensorflow, machine learning, feature engineering, Google Cloud, and cloud computing.
Best For
- Best for experienced data engineers and programmers
Pre-Requisites
- Data engineering or programming experience recommended
- Interest in learning machine learning
Duration and Price
- Two months, 10 hours per week
- $59 per month for a Coursera subscription
Professional Certificate, IBM Machine Learning
Provider: IBM
Level: Intermediate
Shareable Certificate: Yes
IBM’s Machine Learning Professional certification teaches practical skills that machine learning experts use, including comparing algorithms and creating recommender systems in Python. This certification will also help develop expertise in K-Nearest Neighbor (KNN) regression, Principal Component Analysis (PCA), and neural networks and learn how to predict course ratings using regression and classification models.
Why We Picked It
This program has a practical approach to teaching skills that are important for machine learning experts, making it an ideal choice for individuals looking to learn new skills and enhance their proficiency in this field.
Skills Acquired
After course completion, students will be able to acquire skills in data science, deep learning (DL), ML, AI, Python, statistical hypothesis testing, exploratory data analysis, supervised learning, linear regression, ridge regression.
Best For
- Best for those with experience in Python programming, statistics, and linear algebra
Pre-Requisites
- Math, statistics, and computer programming background
- Familiarity with Python and mathematical concepts
Duration and Price
- 3 months, 10 hours per week
- $59 per month for Coursera subscription
IBM Machine Learning with Python
Provider: IBM
Level: Intermediate
Shareable Certificate: Yes
IBM conducts machine learning with Python as part of its AI Engineering Professional Certificate and Data Science Professional Certificate. This introduction to machine learning using Python is suitable for those who want to enhance their data science career or get into machine learning and deep learning.
It covers topics such as supervised and unsupervised learning, regression classification algorithms such as KNN, decision trees, and logistic regression. It emphasizes hands-on learning with Python libraries such as SciPy and scikt-learn, providing job-ready skills and a machine learning certificate upon completion.
Why We Picked It
Python is one of the most popular programming languages and one of the go-to languages for handling data, making it an ideal choice for individuals looking to specialize in this area.
Skills Acquired
Students gain skills in sourcing, organizing, and managing data, descriptive analysis, binary classification, multivariate linear regressions, ML, statistical approaches to regression, and tools to better address ML tasks.
Best For
- Best for specializing in machine learning using Python
Pre-Requisites
- Knowledge of Python, data analysis and visualization techniques
- High school mathematics
Duration and Price
- 12 hours
- $59 per month for Coursera subscription
Machine Learning Specialization
Provider: University of Washington
Level: Intermediate
Shareable Certificate: Yes
The University of Washington’s machine learning specialization course helps individuals innovate and get into the in-demand field of machine learning. Participants receive practical experience in major areas of machine learning such as prediction, classification, clustering, and data retrieval through a series of case studies. They learn how to analyze vast and complicated datasets, design systems that adapt and improve over time, and develop intelligent applications that can make data-driven predictions.
Why We Picked It
This specialization emphasizes experience in essential areas of machine learning making it the best choice for individuals seeking to deepen their knowledge, understanding, and expertise in this field.
Skills Acquired
Students learn about data clustering algorithms, machine learning, classification algorithms, and decision trees.
Best For
- Best for specializing in non-parametric supervised learning algorithm
Pre-Requisites
- Related experience in data science, IT, and machine learning
Duration and Price
- Two months, 10 hours per week
- $59 per month for Coursera subscription
Master of Science, Machine Learning and Data Science
Provider: Imperial College London
Level: Advanced
Shareable Certificate: Yes
The Department of Mathematics at Imperial College London provides a prominent master’s degree in machine learning and data science, giving students a thorough understanding of the mathematical and statistical foundations of modern machine learning algorithms. This curriculum provides students with practical skills through hands-on experience in probabilistic modeling, deep learning, unstructured data processing, and anomaly detection by utilizing industry-standard technologies such as PySpark.
Why We Picked It
This master’s program offers a rigorous curriculum focused on practical application in machine learning. It is ideal for individuals with years of experience in machine learning looking to master their skills in machine learning and data science.
Skills Acquired
Students learn Ethics in Data Science and Artificial Intelligence, programming for data science, applicable mathematics, exploratory data analytics and visualization, supervised learning, big data, statistical scalability with PySpark, Bayesian methods, and computation, deep learning, unsupervised learning, and unstructured data analysis.
Best For
- Mastering machine learning and data science skills
Pre-Requisites
- Undergraduate degree in statistics, mathematics, engineering, physics, or computer science
- English language proficiency
Duration and Price
- 24 months, 12 courses
- $21,671 per year
Is a Coursera Machine Learning Course Worth The Investment?
Machine learning is a skill sought after by many organizations handling large datasets. Certifications are worth the investment to back up your skills and knowledge. Coursera provides a selected collection of machine learning courses that encompass fundamental ideas, specialized tasks, and practical applications, allowing you to broaden your knowledge while gaining real-world experience.
How To Choose The Right Coursera Machine Learning Course
Coursera has an extensive list of machine learning courses offered by prestigious universities and reputable online learning providers. Consider the following factors when selecting the right Coursera machine learning course for your learning needs and goals:
- Course content: Look for courses that cover topics relevant to your goals, such as supervised learning, unsupervised learning, deep learning, or specific applications of machine learning.
- Duration: Some courses may be shorter and more intensive, while others may be spaced out over a longer period with fewer weekly responsibilities. Choose a time frame that works best for your schedule and learning style.
- Outcome: Identify what you want to achieve by taking the course of your choice. Determine if you want to obtain core information, acquire practical skills, achieve a certification, or prepare for a specific career or certification exam.
- Cost: Some courses may provide financial help or scholarships, while others may need a subscription fee or a single payment. Consider any additional expenditures such as textbooks or software that may be required.
- Prerequisites: Make sure you have the necessary prior knowledge and abilities. Choose a course that reflects your current level of knowledge and experience in data.
3 Top Companies to Work For Post-Course Certification
Machine learning certifications build and demonstrate your skills and expertise, positioning you as a valuable candidate for a range of positions. Technology companies such as Apple, Amazon, and Microsoft value technical experience and appreciate creativity, problem-solving skills, and a passion for continuous learning.
Apple
Known for its innovative products and technology, Apple actively seeks machine learning specialists and experts to enhance their experience across its ecosystem. As a machine learning specialist at Apple, part of your responsibilities would be contributing to projects like Siri, Core ML, and personalized recommendations. The company provides platforms for natural language processing, computer vision, and deep learning where you can apply your skills and contribute.
Amazon
Amazon is an eCommerce giant that thrives on data-driven decision-making. Machine learning plays an important role in optimizing customer experience, supply chain management, and personalized recommendations. As an Amazon machine learning engineer, you will take part in projects such as product recommendations, fraud detection, and demand forecasting.
Microsoft
Microsoft is one of the tech giants that invests heavily in artificial intelligence and machine learning. As a data analyst or a machine learning engineer, you’ll collaborate on projects from natural language understanding computer vision and predictive analytics.
Bottom Line: Coursera Machine Learning Provides Skills and Certifications
Aspiring machine learning professionals can start their journey in Coursera’s long list of machine learning certifications, while experienced pros can advance their skills and further their professional development. The wide range of training provides the solid foundation required to navigate the complexities of the world of data. They also encourage critical thinking and problem-solving abilities. Organizations stand to greatly benefit from employees who receive such training, as they bring new perspectives, innovative approaches, and a thorough understanding of machine learning principles to the table.
