21 best machine learning courses online to become an engineer
Machine Learning (ML) is a branch of artificial intelligence (AI) that involves various methods of data analysis with the end goal of creating automatic analytical models. It refers to the science of equipping computers to perform complex functions with minimal human intervention and is now the gateway to the innermost domains of Data Science.
The concepts and practices of machine learning are not restricted to Data Science and ML experts per se. It can bring advantages to experts from other domains as well.
The rising demand for ML professionals has coincided with the rise of MOOCs and Machine Learning certification programs. These allow professionals to switch domains, advance their careers, and stay at the top of the game. Below, we give you a tour of the best machine learning courses online, including career paths, certifications and masters.
Machine Learning Courses Online – Overview
Bill Gates once stated that Artificial Intelligence, energy, and bioscience are some of the most relevant and lucrative career choices for the graduating generations of today. Many believe that fusing AI with energy will lead to solving some imminent questions of today related to production, sustainability, energy distribution, transportation, and quality living.
This has led to a stark interest in Machine Learning which is deemed as the key that unlocks crucial corporate and customer data to exact informed decision-making. At the heart of Machine Learning are common ML algorithms and tasks that are broadly grouped into Supervised, Unsupervised, and Enforcement learning.
Understanding the nature of these tasks and implementing the algorithms can require various levels of self-study depending on the learner’s experience and prior knowledge. So, if you are on the lookout for popular machine learning courses online, this round-up might help you make a more informed choice.
Best Machine Learning Courses Online 2023 – Top Picks
|ML on Udacity||ML on GetSmarter||ML on Coursera||ML on Udemy|
|$349/month||from $1,900||from$59/month||from $11.99|
|View Courses||View Courses||View Courses||View Courses|
*Disclaimer: This post contains affiliate links. Read the full disclosure at the end of this post.
The following list of best machine learning courses, specializations, and certifications cater to aspiring ML professionals of varying skill sets. You can match your own against these to figure out a curated program most suitable to your needs.
1. AWS Machine Learning Engineer – Udacity
Udacity’s nanodegree (visit website) is designed to help intermediate-level programmers upgrade their skills with advanced ML techniques and algorithms. Coming out of the program, you will have functional knowledge about packaging and deploying models to a production environment and related concepts.
In this course, you’ll learn how to use Amazon SageMaker for deploying trained models to a web application. In addition, learners will gain practical knowledge about evaluating the models that they train and deploy.
Starting with a class on Fundamentals in Software Engineering, Learners will move on to more complex topics. These relate to machine learning in production, applying advanced techniques to solve real-world tasks, and deploying built-in and custom-made models.
You’ll finish off with a capstone project centered on proposing a valid solution for a particular ML challenge. Overall, this is one of the best machine learning courses on Udacity and can be combined with other nanodegrees to advance skills.
Instructors: Cezanne Camacho, Mat Leonard, Luis Serrano | Certificate: Yes
Machine Learning Courses: 4 | Prerequisites: Intermediate Python, ML Algorithms
Info: View Course on Udacity. From $349/month. Try with a discount.
2. Machine Learning in Business – MIT Sloan, GetSmarter
MIT Sloan School of Management (visit website) offers a 6-week program for mid-to senior-level managers tasked with enabling their workforce with the full understanding of using machine learning for problem-solving within a business environment and industry.
This course aims to provide learners with an operational perspective of ML and its practical functions in business. Moreover, data-centric professionals and business executives can also enroll in the course to derive massive benefits in the ML space.
Learners will begin with an overview of problem-solving with machine learning in business before diving into the ethics involved. Next, they will move on to more technical concepts involving model evaluations, neural networks for business, and model productionalization.
During the program, participants will understand the technical elements of ML and how to enable them to leverage the technology without needing to code or program. You will finish this certification with a module on how to justify your organizational ML approach.
The skills gained in this class will help learners in building and leading high-performance teams and ensuring sound ML strategies that can be convincingly conveyed to stakeholders. One of the best machine learning courses online for business professionals.
Provider: MIT Sloan, GetSmarter | Duration: 6 weeks | Certificate: Yes.
Level: Professionals | Price: $3,200. | Discount 15%: GS-AF-LEARN15
Info: Visit course website. Get free prospectus. Browse all ML courses on GetSmarter.
3. Become a Machine Learning Engineer for Microsoft Azure – Udacity
Become a Machine Learning Engineer for Microsoft Azure (visit website) is the equivalent course to Udacity’s AWS ML engineer nanodegree. Participants will learn how to build, enhance and deploy machine learning solutions using the most common open-source tools. You should have basic knowledge of machine learning, Python, and statistics.
Consisting of two online machine learning courses and a capstone project, students will begin by configuring machine learning pipelines, identifying use cases for automated machine learning, and using the Azure ML SDK to manage ML pipelines.
The second module will teach several key concepts involved in operationalizing machine learning. Students will learn how to select appropriate targets to deploy models, enable application insights and identify problems in logs. This is among the best machine learning courses online if you wish to harness the power of Microsoft Azure’s Pipelines.
Instructors: Noah Gift, Alfredo Deza, Erick Galinkin | Certificate: Yes
Machine Learning Courses: 3 | Prerequisites: Intermediate Python, ML, Statistics
Info: View Course on Udacity. From $349/month. Try with a discount.
4. Machine Learning, Andrew Ng – Coursera
Stanford University Instructor Andrew Ng (visit website) help learners expand their skillset with techniques learned in artificial neural network, ML algorithms, and Logistic regression. This class spans over 18 modules, approximately requiring 60 hours of learning, and provides a shareable certificate towards the end.
As you enroll, brace yourself for an introduction to machine learning, data mining, and statistical pattern recognition. Course content can be broadly categorized into supervised learning, unsupervised learning, and the best practices in ML.
With several real-world case studies interwoven along the way, you are likely to develop an apt understanding of implementing ML algorithms in building smart robots, text understanding, computer vision, database mining, and other key areas. Overall, this is one of the most popular and best machine learning courses to get started.
5. Professional Certificate in Machine Learning + AI, Imperial College Business School, Emeritus
Professional Certificate in Machine Learning and Artificial Intelligence by the Imperial College Business School is a course that teaches IT, engineering, data, and analytics professionals, as well as STEM graduates and academics, advanced technical skills and business acumen. Its ultimate aim is to help you grow your career in ML and AI.
In terms of topics, you’ll learn the foundations of ML and AI, with an emphasis on honing your analytical skills and covering top-notch techniques for assessing ML models. You’ll also use decision trees and logistic regression to drive your problem-solving skills. The course ends with more advanced topics like deep learning and hyperparameter tuning.
Learn the ML methods currently dominating the industry, drawing from Netflix and DHL, and use your newfound knowledge to advance your ML/AI career. Towards the end, you’ll participate in a capstone project by developing and tuning a code base for a custom-designed ML competition, which you can then use to boost your resume.
As you’ll be heavily leaning on Python, Jupyter, and other tools, this best online machine learning course requires a background in programming or mathematics, with applicants holding a BA degree or higher.
At the end, you’ll adorn your resume with a certificate from the Imperial College Business School Executive Education and the Imperial College London Department of Computing.
Provider: Imperial College, Emeritus | Time: 25 weeks | Certificate: Yes.
Level: IT + Data Professionals | Pace: Instructor-lead | Price: $4,480 or £3,675.
Info: Visit course website. Get free brochure. Browse full course catalog on Emeritus.
6. Mathematics of Machine Learning Specialization – Imperial College London, Coursera
In this beginner-level, 3-course specialization (visit website), students will learn about the prerequisite mathematics for data science applications and machine learning. With this specialization, students will be able to bridge the gap between the way they learned mathematics in high school and the way it’s applied in the context of computer science.
You will start with an introductory course on Linear Algebra and the various ways it’s relevant to data before moving on to Multivariate Calculus. This is where you will learn how to optimize fitting functions for data. Applying the knowledge from the first classes, students will then perform dimensionality reduction with principal component analysis.
Before enrolling in the third course, learners would be required to possess a basic knowledge of Python and NumPy. By the end of this specialization, you will have the required knowledge needed to escalate to more advanced machine learning courses.
7. Machine Learning A-Z: Hands-On – Udemy
Udemy’s Machine Learning A-Z (visit website) is taught by two data science experts who will teach you how to create ML algorithms in Python and R. It provides 40 hours of on-demand video lectureship and successfully finishing off this machine learning course will land you with a certificate of completion for a course fee starting from $11.99.
The course content spans over 45 sections comprising 332 lectures in total that walk learners through some key concepts in ML. You will begin with mastering ML on Python and R. To do this, you’ll have to learn to make accurate predictions, handle advanced techniques such as dimensionality reduction, and create powerful ML models to solve complex real-world problems.
Other skills learners might acquire include training their intuition when dealing with crucial ML models, making analyses, and adding value to businesses. The class is meant for learners who possess the theoretical foundation but lack implementable skills. It is among the best machine learning courses on the Udemy platform.
Instructor: Hadelin de Ponteves, Kirill Eremenko | Level: Beginners
Platform: Udemy | Video: 45 hours | User Rating: 4.5/5 ★★★★☆
Info: View course. From $11.99. Up to 95% off. Browse all machine learning courses.
8. Machine Learning Literacy – Pluralsight
Pluralsight’s Machine Learning Literacy is a three-tiered project aimed at exploring the modeling techniques, workflows, and algorithms that drive ML-based solutions for a complex program. Designed for learners of all skillsets, the path’s content is distributed between beginner, intermediate and advanced levels.
At the beginner level, you will learn about feature engineering and use the phenomenon to create your first features from numerical data. Clearing this milestone will put you abreast of the intermediate-level course content. Here you will deal with nominal data such as names, types, and categories. Your primary task would be to transform this data into simplified features appropriate for ML.
At the Advanced level, students will implement what they have learned so far to extract features from texts and documents. Although the path caters to learners of all levels, it is still recommended to have a certain degree of familiarity with Statistics, Data Literacy, and Data Analytics Literacy. One of the best online machine learning courses on Pluralsight.
Machine Learning Courses: 5 | Level: beginners to Advanced
Instructors: Janani Ravi, Mohammed Osman | Pre-requisites: Data Literacy
Price: View course. $29/month. Includes certificate. Try with the 10-day trial.
9. Intro to Machine Learning with PyTorch – Udacity
Udacity’s third ML course on the list (visit website) is another intermediate nanodegree program aimed at learners with at least 40 hours of programming experience and functional knowledge of Python libraries and structures. Spanning over three online machine learning courses, the program can be completed in 3 months at 10 hrs/week.
Udacity’s Intro to Machine Learning is curated in collaboration with Kaggle and AWS. It specifically caters to programmers familiar with intricacies in Python but who are new to ML. Key areas of focus include foundational machine learning algorithms, data cleaning, and supervised models.
Your ML journey will begin with an introductory course on Supervised Learning, a class of methods to help you construct models. Subsequent courses deal with Deep Learning and Unsupervised Learning. At each of these touchpoints, learners will brace themselves for practical encounters with code exercises and projects.
Instructors: Cezanne Camacho, Mat Leonard, Luis Serrano | Certificate: Yes
ML Courses: 4 | Prerequisites: Intermediate Python
Price: View Course. From $349/month. Try with a discount.
10. Machine Learning – University of Washington, Coursera
Taught by the University of Washington, Machine Learning (visit website) is an in-depth specialization aimed at learners with an intermediate-level skill set. Spanning over four hands-on online machine learning courses, the specialization will walk you through the essentials of ML: linear regression, classification, clustering, and retrieval.
Learners will begin with a foundational introduction to ML using a series of case studies. Some of these include estimating house prices, analyzing sentiments from user ratings, recommending products, retrieving documents, and other implementable areas.
From here, you will move on to applying linear regression to create predictive models and learn how to handle large sets of features and perform analysis. Your final milestone would be to use similarity-based algorithms for information retrieval and recommendations.
To do this, learners will have to master essential ML tools and techniques, such as clustering documents using k-means, expectation-maximization (EM), latent Dirichlet Allocation (LDA), etc. One of the best machine learning courses on Coursera.
Machine Learning Courses: 4 | Duration: 7 months. 3 hours/week
Provider: University of Washington | Level: Intermediate | Certificate: Yes
Info: View Course. Browse: Search all machine learning courses on Coursera.
11. Intro to Machine Learning with TensorFlow – Udacity
Curated once again in collaboration with Kaggle and AWS, Intro to Machine Learning with TensorFlow helps students advance their skillset of key ML techniques and algorithms.
In this three-module nanodegree program you’ll touch upon key ML concepts, from data manipulation and supervised and unsupervised learning. Learners can easily complete this program in 3 months with a dedicated learning span of 10 hrs/week.
Beginning with a module on supervised learning that will teach you about the common class of methods for model construction, you will move on to explore more complex concepts in ML. In the second module, you will pick up some foundational concepts related to neural network design in TensorFlow.
Once past this milestone, learn to implement unsupervised learning to finish off this online machine learning course successfully. Udacity recommends prior experience with Python and some basic level command over probability and statistics to maximize success.
Instructors: Cezanne Camacho, Mat Leonard, Luis Serrano | Certificate: Yes
Machine Learning Courses: 3 | Prerequisites: Intermediate Python
Price: View Course. From $349/month. Try with a discount.
12. Machine Learning Course Masters Program – edureka
edureka’s Master’s Program in Machine learning (visit website) is an extensive project with nine specialized online machine learning courses, some 200+ hours of interactive learning, and a capstone assignment that offers valuable insight into ML implementation.
Key areas of focus include Supervised Learning, Unsupervised Learning, and Natural Language Processing. Moreover, this Masters program claims to have incorporated the most recent advancements in ML such as deep learning, reinforcement learning, and graphical models.
Coming out of the program, you’ll have expanded your skillset with techniques such as scripting, data handling, linear regression modeling, sampling techniques, and much more. Edureka’s ML Course is broadly divided into five sections with each containing a varying number of modules.
You’ll begin with Programming and Machine Learning Certification Training using Python. From here, the curriculum will shift to Natural Language Processing and Deep Learning Training using Tensorflow. The final milestone is a Spark Certification Training that is designed to help learners become successful Spark developers in Python.
Machine Learning Courses: 9 modules | Time: 2-4 months | Certificate: Yes
Interactive Hours: 200 hours | Capstone: Yes | Cost: $1,499. View website.
Tip: To meet some of the prerequisites of machine learning courses, browse our best Python courses or data science courses. If you have a different focus on AI, explore the best artificial intelligence courses or deep learning courses.
13. Data Science: Machine Learning – HarvardX, edX
edX ‘s machine learning course is part of its professional certificate program in Data Science. Enrolling in the course, learners will prepare to master ML as one of the predominant methodologies in Data Science and create a movie recommendation system. It is an 8-week program that can easily see completion with 2-4 hours of dedicated learning each week.
This class is designed to help learners explore, investigate and leverage ML’s predictive algorithms. Learn to implement these along with performing principal component analysis as well as regularization to create viable recommendation systems.
All of this will rely on engagement with large data sets, training data, and investigating these sets to generate predictive relationships. Coming out of the program, you will have developed a sufficient understanding of key ML features and algorithms as well as their implementation in a real-world environment.
Duration: 8 weeks. 2-4 hours/week | Certificate: Yes.
Provider: Harvard, edX | Price: Free. With certificate $99. Discount available.
14. Applied Machine Learning Program – Purdue University, Simplilearn
Simplilearn’s 3-month certification program ($1699) follows the online bootcamp format that can be successfully completed at a consistent pace of 8 hours/ week. It comes with some 48 hours of live online classes from top Purdue faculty and enrolment will land you a chance to join Purdue’s alumni association.
Some core concepts included in this track are supervised and unsupervised learning, data wrangling, feature engineering, and feature selection. By the end, you will have developed a working knowledge of the latest developments and skills in ML.
Be ready to evolve your skillset with features such as decision trees, exploratory data analysis, data wrangling, logistic regression and classification, and feature extraction. This is one of the best machine learning courses online and career tracks on Simplilearn.
Provider: Purdue University | Average salary: $113K | Projects: 4
Certification: Master’s Program | Price: $2,000. Pay in installments: $176
15. Machine Learning and Finance – New York University, edX
edX’s second program on the list is a professional certificate designed in partnership with the New York University. It is a self-paced four-month program that will easily see completion with 4-6 hours of dedicated learning per week.
This online ML course comprises two skill-building courses aimed at learners with varying levels of expertise. Upon enrolling, you will first encounter classical machine learning models that can be utilized to gain valuable data-related insights. In the process, you will also acquire hands-on experience with important ML tools.
In the second ML course, learners will expand their toolkit with deep learning techniques and by doing so familiarize themselves with its role in finance. Coming out of the ML course, you will have a sufficient understanding of ML and DL applications, artificial neural networks, and ML-based models that can solve problems related to finance.
Machine Learning Courses: 2 | Duration: 4 months. 4-6 hours/week
Certificate: Yes. | Provider: NYU, edX | Price: $1498. Discount available.
16. IBM AI Engineering, Professional Certificate – Coursera
Coursera’s professional certificate ($39 USD) in ML is designed to help individuals launch their careers in AI and related fields. Aimed at learners with an intermediate level skillset, this machine learning course will roughly span some 8 months at a minimal 3 hours/week.
In this self-paced path, you will learn key concepts in ML and DL along with essential ML algorithms such as regression, classification, clustering, etc. The track also focuses on implementing supervised and unsupervised ML models with SciPy and ScikitLearn.
In addition, learners will train themselves to deploy ML algorithms on Apache Spark and build DL-based models with the help of Tensorflow, PyTorch, and Keras. A final capstone project will allow you to implement all that you have learned to solve real-world challenges.
17. AI Machine Learning Engineering Career Track – Springboard
Springboard offers its six-month online career track to help learners successfully grab careers in ML. The platform claims to equip students with the skillset that can get them an ML engineering job within 6 months after completing the program.
In this engineering career track, the focus shifts from theoretical concepts in ML to the production and engineering skills that, according to the site are sought after the most in the industry. During some 120+ hours of content coverage, you will walk through some in-demand ML concepts.
Starting with a theoretical understanding of these concepts, learners will move on to the mathematical engineering behind their implementation and testing and training ML models. This will require individuals to learn about ML algorithms and related methodologies such as regression modeling, clustering, classification modeling, anomaly detection modeling, decision trees, and recommendation systems.
From here, you will move on to core concepts in Deep Learning, Computer Vision, the entire ML engineering stack, deployment of ML models, and working with data for a more thorough command. This is among the best machine learning courses on Springboard.
Duration: 6 months | Certificate: Yes. | Info: Hands-on experience. Career support.
1:1 Mentoring: Yes | Job Guarantee: Yes | Price: $8,940. $1,490/month.
18. Machine Learning: From Data To Decisions – MIT
MIT’s Machine Learning course is an 8-month online program designed to help learners with the practical and real-world applications of ML. Although this ML course is aimed at learners of all skillsets stretching from basic to advance, it still recommends individuals to have some prior knowledge of statistics.
Since the course is designed to help students with ML implementation, key areas of focus include ML algorithms that help with predictive analysis, a foundational understanding of ML applications that drive critical decision-making, and causal inferences to analyze the impact of important variables.
MIT encourages learners from various industries to enroll in the course for an upfront fee of $2,300. These industries include manufacturing, IT services, retail, media, finance, Business Intelligence, and healthcare. It’s one of the best machine learning courses online that is suitable for beginners, though some knowledge of statistics is required.
Duration: 8 weeks | CEUs: 6.4 CEUs | Certificate: Yes. | Price: $2,300.
19. Machine Learning – Stanford University
Stanford School University’s curated course on Machine Learning is leveled at students with intermediate expertise in linear algebra, basic probability, and statistics. Their program is a broad introduction to ML and statistical pattern recognition.
Key concepts that the course will shed light on include supervised learning, unsupervised learning, reinforcement learning, and control. Coming out of this machine learning course, students will have a working knowledge of the practical applications of ML algorithms in data mining, smart technology, bioinformatics, and autonomous navigation.
You will begin with basic concepts in ML and then move on to generative algorithms, evaluating and debugging algorithms, Bias trade-offs, Q-learning, and policy iteration.
Type: Online ML course | Part of the certificate program: AI Graduate Certificate
20. Machine Learning – Cornell Certificate Program
Cornell’s Machine learning Certificate Program ($565/month) is designed to help students understand the application of ML algorithms. Although it is somewhat of a machine learning course for beginners, students are still advised to enroll once they have gained some familiarity with Python, Probability Theory, multivariate calculus, and linear algebra.
Students will learn how to implement ML algorithms using Python and will complete their projects using Jupyter Notebook.
By the end of this ML course, you will have sufficient knowledge of investigating and framing ML algorithms using an intuitive and mathematical approach. The key idea is to help students create applicable mental models to solve problems programmatically.
In addition, individuals will have the opportunity of working with live data along with exploring and creating neural networks for different data types. Successfully completing the course will earn you a Machine Learning certificate and 126 Professional Development Hours (12.6 CEUs).
Duration: 3.5 months. 6-9 hours/week | Mode: Online. Instructor-led.
Class: Max. 35 students | Certificate: Yes. | Price: from $3,699. $565/month.
21. Machine Learning Crash Course – Google
Google offers its crash course on Machine Learning using TensorFlow APIs. It is an in-depth guide on the prerequisites that learners of varying skillsets (basic, intermediate, and advanced) must meet. Generally speaking, potential enrollees must be comfortable with linear equations, graphs of functions, variables, statistical means, and histograms.
Since the programming exercises included are performed in Python, students are ideally required to have a functional knowledge of this language.
Machine Learning Crash Course spans over a series of 25 lessons with some 30+ exercises that will cost learners around 15 hours of dedicated learning. By the end of these ML courses, you will have gained a practical understanding of ML algorithms and their implementation via case studies and interaction with algorithms in action.
Lessons: 25+ | Exercises: 30+ | Duration: self-paced | Price: Free.
22. Introduction To Machine Learning for Coders – Fast.ai
Taught by Jeremy Howard, Founder Enlitic, Introduction to ML for Coders is an interactive opportunity for individuals looking to create ML algorithms from scratch. You’ll also learn key ML concepts including data preparation, model training, testing, and building data-based products.
With some 24 hours of recorded lessons interwoven with the course content, learners are advised to dedicate around 8 hours of learning per week to finish the course in 3 months. Program prerequisites include one year of coding experience and familiarity with High school Math. This is one of the best free machine learning courses online.
Duration: 12 weeks. 8 hours/week | Price: Free | Prerequisites: Coding knowledge
Based on: Masters of Science in Data Science program, University of San Francisco
Choosing the Best Machine Learning Courses Online
Machine Learning is increasingly becoming a democratized field and calls for a similar learning approach. The universal availability of MOOCs and paid certifications have made learning more than accessible for aspiring ML professionals.
The catch will be to opt for the best machine learning courses online that match one’s skillset. Performing comparative research on these popular online machine learning courses will go a long way in helping you make the right choice.
As stated earlier, online machine learning courses are not only for AI professionals but can benefit persons from other domains. Anybody who is remotely connected to the field or aims for higher productivity can benefit from these.
But you would not want to waste your energy on courses that are not relevant to your domain. For this reason, it’s recommended to thoroughly take into account the following.
Current Skillset – ML will require coding, and working with Statistics, Calculus, and Linear Algebra at the least. If you are not confident, we suggest you practice these on the side.
Future Goals – Are you an ML professional looking for career advancement, aspiring for a career switch, or simply curious? Your choice of the best machine learning courses will depend on your current professional status.
Financial Circumstances – While some of the online machine learning courses listed above provide financial aid, many do not. Think about your range as well as the course outcome before deciding to invest in one.
Once you’ve thoroughly assessed the above-mentioned criteria as well as performed a comparative study around the best machine learning courses online, you will automatically be drawn to the program that aligns the best with your current and future needs.
Best Machine Learning Courses Online 2023 – Verdict
Wrapping up our tour of the best machine learning courses online. Investing your time and energy in a self-paced curated course requires both motivation and dedication. ML might have become very democratized, but it is also very intensive.
This makes the choice of an appropriate online machine learning course all the more critical. Whatever your end goal, so long as you manage to inflate your skillset in machine learning and artificial intelligence through enrolment, it is a win-win.
Best Machine Learning Courses Online 2023
- Become An AWS Machine Learning Engineer – Udacity
- Machine Learning in Business – MIT Sloan, GetSmarter
- Become A Machine Learning Engineer For Microsoft Azure – Udacity
- Machine Learning Course, Andrew Ng – Coursera
- Professional Certificate in Machine Learning and AI, Imperial College
- Machine Learning A-Z: Hands-on Course – Udemy
- Mathematics For Machine Learning Specialization – Coursera
- Machine Learning Literacy – Pluralsight
- Intro to Machine Learning with PyTorch – Udacity
- Machine Learning Course Masters Program – edureka
- Intro to Machine Learning with TensorFlow – Udacity
- Machine Learning – University of Washington, Coursera
- Data Science: Machine Learning – HarvardX, edX
- Applied Machine Learning Program – Purdue University, Simplilearn
- Machine Learning and Finance – New York University, edX
- IBM AI Engineering, Professional Certificate – Coursera
- AI Machine Learning Engineering Career Track – Springboard
- Machine Learning: From Data To Decisions – MIT
- Stanford University’s Machine Learning Course
- Cornell Certification Machine Learning Course
- Free Machine Learning Crash Course – Google
- Introduction To Machine Learning for Coders – Fast.ai
What are the best machine learning courses online? Have you taken any of the ML courses above? What is your learning experience? Let us know in the comments below.
Sources: What is data science? | What is machine learning? – Wikipedia | What is scipy? – 2 | What is AI? – IBM | Programming languages for ML – 4 | Self-Driving Cars – 5 | Matrix Factorization – 6 | What is K-means clustering? – 7 | What is Random Forest? – 8
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