Most Popular Online Courses of 2018 | Best-Selling MOOCs in 2018

Now in its seventh year, the modern MOOC movement crossed 100 million learners in 2018, to reach a total of 101 million. This represents somewhat slower year-over-year growth than was the case in 2017 but still amounts to a brisk 30% increase in total student numbers for 2018. More and more degrees are now being offered through MOOC platforms. Consequently, despite a continued slowdown in the growth of new users, MOOC platforms are seeing an increase in paying customers.


Best-Selling MOOCs 2018
Source: Class Central


We (Stoodnt, Inc.) are primarily a career guidance and college admissions platform. Additionally, we also list thousands of curated online courses offered by various MOOC providers like Coursera, EdX, Udemy, Edureka, Skillwise, Skillshare etc.


In 2018, we also observed a huge increase in the number of users who signed up for online courses (free trials and paid subscriptions) on our site. Apart from high school & college students and professionals, several study-abroad aspirants (the majority being the MS applicants) also sign up for multiple courses in order to improve their admission chances at the top universities.


We have got courses across various categories – software programming, data science, machine learning, digital marketing, design, soft skill training etc. We observed a huge interest in the online courses on data science, machine learning, artificial intelligence, cloud, and big data analytics. This trend does support the report by TNM last year – Artificial Intelligence (AI) and Machine Learning (ML) are the most widely chosen (25% of respondents) domains for reskilling among working professionals.


MOOCs in 2018


The industry is ever evolving due to advanced technologies and is enabling more and more professionals to take charge of their careers through certification courses and reskilling. With organizations around the world adapting to digital transformation, professionals want to proactively hone their technology skills.


Here is a snapshot of what the students and professionals were looking for in 2018 – based on keyword search, requesting info, free trials, and sign-ups.


best selling moocs 2018



Most Popular Online Courses of 2018


Learning Python for Data Analysis and Visualization


Percentage of Paid Learners who bought this Course on 2%


It’s a great course for the folks who want to learn Python for data analysis and data visualization. Learners will use the numpy library to create and manipulate arrays. It also provides the opportunity to work with various data formats within python, including JSON, HTML, and MS Excel Worksheets.


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Machine Learning Specialization by University of Washington


Percentage of Paid Learners who bought this Course on 3%


Although the Machine Learning course by Stanford is more popular among the best online courses for machine learning worldwide, Stoodnt users showed way more interest for the Washington one.


This course is suitable easier for the folks without strong technical backgrounds, in comparison to the courses by other top universities. Taught by Emily Fox and Carlos Guestrin, both Amazon Professors of Machine Learning, it is a comprehensive course spread over the period of 8 months.


The specialization introduces learners to the exciting, high-demand field of Machine Learning. Through a series of practical case studies, they will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. Students will also learn to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data.


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Complete Data Science Bootcamp


Percentage of Paid Learners who bought this Course on 3%


This is a great course for absolute beginners and provides complete training in Mathematics, Statistics, Python, Advanced Statistics in Python, Machine Learning, and Deep Learning.


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Strategic Business Analytics Specialization by ESSEC Business School


Percentage of Paid Learners who bought this Course on 4%


This specialization is designed for students, business analysts, and data scientists who want to apply statistical knowledge and techniques to business contexts. It’s recommended that learners have some background in statistics, R or another programming language, and familiarity with databases and data analysis techniques such as regression, classification, and clustering.


By the end of this course, students will be able to use statistical techniques in R to develop business intelligence insights and present them in a compelling way to enable smart and sustainable business decisions. It’s a great opportunity to learn from two of Europe’s leading professors in business analytics and marketing and earning a certificate from a top business school in the world.


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Applied Data Science with Python Specialization by University of Michigan


Percentage of Paid Learners who bought this Course on 5%


The 5 courses in this University of Michigan specialization introduce learners to data science through Python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistically, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data.


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Excel to MySQL: Analytic Techniques for Business Specialization by Duke University


Percentage of Paid Learners who bought this Course on 5%


In this Specialization, students will learn to frame business challenges as data questions. Learners will use powerful tools and methods such as Excel, Tableau, and MySQL to analyze data, create forecasts and models, design visualizations, and communicate your insights. In the final Capstone Project, students should apply skills to explore and justify improvements to a real-world business process.


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Statistics with R Specialization by Duke University


Percentage of Paid Learners who bought this Course on 5%


In this Specialization, users will learn to analyze and visualize data in R and create reproducible data analysis reports. They will demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena. This will help the learners to make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis.


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Mathematics for Machine Learning Specialization by Imperial College London


Percentage of Paid Learners who bought this Course on 7%


For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics – stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to how it’s used in Computer Science. This specialization aims to bridge that gap, getting you up to speed in the underlying mathematics, building an intuitive understanding, and relating it to Machine Learning and Data Science.


Courses include Linear Algebra, Multivariate Calculus, and Dimensionality Reduction with Principal Component Analysis. This course is of intermediate difficulty and will require basic Python and numpy knowledge. Instructors of this course come from the Departments of Computing, Design Engineering, and Metallurgy. At the end of this specialization, you will have gained the prerequisite mathematical knowledge to continue your journey and take more advanced courses in machine learning.


This course generated a lot of interest among our users. Though only 8% of users actually bought this course; that’s because we listed this towards the end of 2018. So, we expect that many more users will sign up for this course.


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IBM Data Science Professional Certificate


Percentage of Paid Learners who bought this Course on 8%


This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Data Science (or Machine Learning).


This program consists of 9 courses providing you with latest job-ready skills and techniques covering a wide array of data science topics including open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud using real data science tools and real-world data sets.


Similar to Imperial College London course, a majority of learners signed up for this one in the second half of 2018.


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Microsoft Excel: Beginner to Advanced


Percentage of Paid Learners who bought this Course on 11%


Irrespective of the industry and job profile, the working knowledge of MS Excel is a must these days. Excel is way beyond than just data entry. You can use it for a wide range of statistical analysis. According to LinkedIn, MS Excel is one of the top transferrable skills to stand out in the job market. So, personally, it’s heartening to see that students and professionals are taking up this course in huge numbers.


Users will learn the most common Excel functions used in the Office, maintaining large sets of Excel data in a list or table, and mastering dynamic formulas with IF, VLOOKUP, INDEX, MATCH functions and many more. Additionally, users will also learn to automate day to day tasks through Macros and VBA.


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Python for Everybody Specialization by University of Michigan


Percentage of Paid Learners who bought this Course on 12%


This Specialization will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In the Capstone Project, learners will use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization.


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Machine Learning A-Z: Hands-on Python & R in Data Science


Percentage of Paid Learners who bought this Course on 14%


We have been expecting this course on the best-selling list. It has been extremely popular among our users since 2017. Even worldwide, it’s among the top online courses on machine learning.


The course has been created by  Kirill Eremenko, Hadelin de Ponteves, SuperDataScience Team, and SuperDataScience Support. This course will help you Master Machine Learning on Python and R, make accurate predictions, build a great intuition of many machine learning models, handle specific tools like reinforcement learning, NLP, and Deep Learning. Most importantly it teaches you to choose the right model for each type of problem.


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Data Science Specialization by Johns Hopkins University


Percentage of Paid Learners who bought this Course on 15%


This Specialization covers the concepts and tools anyone will need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, learners will apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material.


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Deep Learning Specialization by


Percentage of Paid Learners who bought this Course on 19%


Here comes the 2nd best-selling online course of 2018.


Deep learning surrounds us every day, and this will only increase with time. Deep Learning is one of the most highly sought-after skills in tech. Deep learning is very effective in helping companies increase their chance to identify profitable opportunities and/or avoid unknown risks. So, I am not surprised to see this course at the top.


Deep learning, also known as the deep neural network, is one of the approaches to machine learning. Other major approaches include decision tree learning, inductive logic programming, clustering, reinforcement learning, and Bayesian networks. Read more on the differences among Neural Networks, Deep Learning, Machine Learning, and Artificial Intelligence.


If you want to break into AI, this Specialization will help you do so. This course is developed by Andrew Ng in association with Stanford Professors and NVIDIA & as industry partners.


In five courses, users will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. Learners will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. Students will practice all these ideas in Python and in TensorFlow, which we will teach. Last but not least, you will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice.


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Complete Python Bootcamp: Go from zero to hero in Python 3


Percentage of Paid Learners who bought this Course on 22%


Here comes the most popular online course of 2018. This proves 2018 as the year of Python. After all, Python has been one of the employer’s most requested skills of 2018.


This is the most comprehensive, yet straight-forward, course for the Python programming language on Udemy! Whether you have never programmed before, already know basic syntax, or want to learn about the advanced features of Python, this course is for you! In this course, you will learn Python 3. 


With over 100 lectures and more than 20 hours of video, this comprehensive course leaves no stone unturned! This course includes quizzes, tests, and homework assignments as well as 3 major projects to create a Python project portfolio!


This course will teach you Python in a practical manner, with every lecture comes to a full coding screencast and a corresponding code notebook! Learn in whatever manner is best for you!


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Special Offers for Stoodnt Users from Coursera and Udemy


  • 7-day Free Trial on Specializations by Coursera – so start learning for free!

  • Get 10% Off on Coursera – when you pay in advance for a specialization

  • Upto 90% Off on all Udemy Courses



Read: Are the Online Courses and MOOCs Worth It?


Other Top Selling Online Courses in 2018 on


Percentage of Paid Learners who bought this Course on 0.5 – 1%


Python 3 Programming Specialization (University of Michigan)

Cybersecurity Fundamentals (Rochester Institute of Technology)

R Programming A-Z: R for Data Science with Real Exercises

Analyzing and Visualizing Data with Power BI (Microsoft)

Java Programming and Software Engineering Fundamentals Specialization

Machine Learning (Stanford University)

Spark and Python for Big Data with PySpark

Data Analysis and Presentation Skills: the PwC Approach

Data Engineering on Google Cloud Platform Specialization

Machine Learning Specialization (University of Washington)

Machine Learning with TensorFlow on Google Cloud Platform Specialization

Biostatistics in Public Health Specialization (Johns Hopkins University)

Analytics Edge (MIT)


Featured Image Source: MoocLab


Disclosure: Stoodnt, Inc. is an affiliate partner of various MOOC providers. We get a small commission if you sign up for any course using our links. That allows us to cover the costs of maintaining this site and keep adding useful content. You can view all our listed online courses here.

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