Which of the 6 programs should you choose?
Updated 2021–03–14: The MicroMaster Artificial Intelligence from Columbia University is no longer available, and no further runs are planned.
Massive Open Online Courses (MOOCs) are today a valuable alternative for learning data science.
Not only beginners but also data science veterans are doing MOOCs — like myself.
I am a part-time lecturer on master’s level programs and familiar with many lectures worldwide, and I regularly assess online courses.
Not a few students do in parallel MOOCs in the data science field. These are mostly students from other disciplines that are moving into that area, and for them, it is a fast and flexible way to fill the gap in basics while attending lectures on the master’s level.
So, they often ask me for advice which MOOCs would be best suited for their individual situation.
There are pros and cons to each MOOC. The fact is that with MOOCs alone, you cannot become a data scientist. You need practical experience and exchange with and mentorship from veterans. But it is a convenient way to get access to high-quality education and a fast path to fill gaps.
My observation is that the MOOCs’ quality is increasing steadily, and you have a growing choice of online programs. So, it becomes essential to find the individually right program.
Another question is if you should get a certificate or not. My personal opinion is that when you anyway will get a degree on a graduate level, and it only serves as a possibility to fill gaps, it is not necessary to take a certificate. If it shows additional knowledge that you would otherwise not have, go for a certificate. Benjamin Obi Tayo, Ph.D. has an excellent summary of the consideration for certifications.
Comparing the many different platforms is not a simple task; even the comparison of the many various programs on one platform is tricky for a data science beginner.
Our university is part of the edX platform, so it is the choice of many of our students. For that reason, I am most familiar with the course offered there.
In this guide, I focus on the so-called MicroMasters programs on the edX platform.
A MicroMasters program consists of a series of graduate-level courses, including corresponding assignments, exams, and practical projects. The average length is about one year, with an effort of about 10 hours per week. It corresponds to around 25% of a full master’s program, and the earned credits can be transferred to designated online or on-campus master’s programs.
So, MicroMasters programs are not only a convenient way of gaining relevant and high-quality education but also a way of testing your delight in full graduate education.
The following six MicroMasters on edX programs have been assessed:
- Analytics: Essential Tools and Methods — The Georgia Institute of Technology
- Artificial Intelligence — Columbia University — no longer available (see below) [updated 2021–03–14]
- Big Data — The University of Adelaide
- Data Science — UC San Diego
- Predictive Analytics using Python — The University of Edinburgh
- Statistics and Data Science — MIT Massachusetts Institute of Technology
The programs are listed in alphabetical order.
- All information below is taken from the corresponding MicroMasters program description on edX, the individual course descriptions, and from the courses themselves only accessible when enrolled.
- The “Pros,” “Cons,” and “Who should take that program” represent my opinion based on my assessment of the programs and courses.
1. Analytics: Essential Tools and Methods — The Georgia Institute of Technology
What you will learn: You learn data preparation, regression, classification, clustering, time series models, prediction, optimization and model validation, preprocessing unstructured data, relational data, tidying data, visualization, numerical computing, customer analytics, measuring risk and returns, marketing analytics, statistical process control, and forecasting demand.
Courses: 3 courses:
- Introduction to Analytics Modeling (16 weeks, 8–10 hours per week)
- Computing for Data Analysis (15 weeks, 8–10 hours per week)
- Data Analytics for Business (16 weeks, 10–12 hours a week)
- Probability and statistics
- Basic programming proficiency
- Linear algebra
- Basic calculus
Lengths and effort: 1 year, 9–11 hours per week
Assessments and certification: A grade of 60% or higher is required to pass, from weekly homework/notebook, a project, and proctored exams.
Tools and programming language(s): SQL, R/RStudio, Python, Arena simulation software, PuLP optimization software, Simply, pandas, Numpy, Scipy
Costs: USD 1,500 (full program)
Pros: Gives a good introduction in the most important methods and tools, including the link to business data analytics problems.
Cons: Focuses on classical optimization with specialized tools rather than advances in machine learning and deep learning.
Credits: The MicroMaster counts with 25%, or 9 hours toward the total of 36 hours of the Online Master of Science in Analytics (OMS Analytics) degree of the Georgia Institute of Technology.
Who should take that program: People who want a sound introduction into data analytics with the goal to apply it in business and finance.
2. Artificial Intelligence — Columbia University
Remark: the program is no longer available and no further program runs are planned [updated 2021–03–14]
What you will learn: You learn AI applications of machine learning, reinforcement learning, natural language processing, regression, classification, boosting, unsupervised learning, Hidden Markov Models and State-space Models, principle component analysis, robotic movements and kinematics, robots motion planning, all aspects of computer-generated imagery programming and creation.
Level: Advanced (graduate-level course)
Courses: 4 courses:
- Artificial Intelligence (AI) (12 weeks, 8–10 hours per week)
- Machine Learning (12 weeks, 8–10 hours per week)
- Robotics (10 weeks, 8–10 hours per week)
- Animation and CGI Motion (12 weeks, 8–10 hours per week)
- Proficiency python programming skills
- Proficiency programming knowledge in C/C++
- Calculus incl. partial derivatives and linear algebra
- Introductory classical mechanics
- Probability and statistical concepts
Lengths and effort: 1 year, 8–10 hours per week
Assessments and certification: Grade of 60% or higher required to pass, of quizzes, (programming) projects, homework, and the final proctored exams per course.
Tools and programming language(s): Python, C/C++
Costs: USD 896.40 (full program)
Pros: One of the very few graduate-level MOOCs that also provides a more in-depth introduction to robots and computer-generated imagery.
Cons: Even though the course descriptions note a weekly effort of 8–10 hours, that only applies to people fulfilling the prerequisites on a proficient level. All others should consider 10–20 hours a week to complete the courses successfully.
Credits: It will count 25% or 7.5 credits toward the 30 credits of the Master of Computer Science program at Columbia University.
Who should take that program: People proficient in programming in Python and C/C++, and with an advanced knowledge in data science who want to deepen the AI skills on a graduate level.
3. Big Data — The University of Adelaide
What you will learn: You learn algorithm design, and fundamental programming concepts, manipulation, and transformation of data, as well as dimension reduction, directed and undirected graphs, hashing, big data fundamentals, stream processing, MapReduce, Google’s web search, and AdWords system, regression and classification, and deep learning algorithms.
Level: Introductory to advanced
Courses: 5 courses:
- Programming for Data Science (10 weeks, 8–10 hours per week)
- Computational Thinking and Big Data (10 weeks, 8–10 hours per week)
- Big Data Fundamentals (10 weeks, 8–10 hours per week)
- Big Data Analytics (10 weeks, 8–10 hours per week)
- Big Data Capstone Project (6 weeks, 4–5 hours per week)
Lengths and effort: 1 year, 8–10 hours per week
Assessments and certification: Grade of 60% or higher required to pass, based on all quizzes, assignments, and worked problems.
Tools and programming language(s): Processing.js, R/RStudio, Java/Eclipse IDE, Apache Spark, sparklyr, and H20.
Costs: USD 1,436.40 (full program)
Pros: It gives a broad and comprehensive introduction into the Big Data thinking and design, the various tools and programming languages, and integrates real-world examples from web search and web advertising.
Cons: It is less suited for a data science beginner; otherwise, the effort will be considerably higher.
Credits: The Big Data MicroMasters program certificate represents 25% or 12 units of the Master of Data Science program, which requires a total of 48 units of coursework to complete.
Who should take that program: People who already have a sound understanding of data science and are familiar with at least one programming language on an intermediate level and want to have an introduction into the Big Data area.
4. Data Science — UC San Diego
What you will learn: You will learn the necessary process of data science, Python and Jupyter notebooks, processing uncurated datasets, fundamental statistical analysis, basic machine learning methods, visualization, an overview of sets, counting principles, combinatorics, discrete probability, conditional probability, and Bayes’ Rule, random variables, expectation, variance, and correlation, joint distribution families, continuous distributions, probabilistic inequalities, concentration, and limit theorems, linear and logistic regression, sampling, parameter estimation, and confidence intervals, hypothesis testing, decision trees, and an introduction to deep learning, neural networks, and TensorFlow.
Courses: 4 courses:
- Python for Data Science (10 weeks, 8–10 hours per week)
- Probability and Statistics in Data Science using Python (10 weeks, 10–12 hours per week)
- Machine Learning Fundamentals (10 weeks, 8–10 hours per week)
- Big Data Analytics Using Spark (10 weeks, 9–12 hours per week)
- Programming experience on an undergraduate level
- Logic and set theory
- Multivariate calculus
- Linear algebra
Lengths and effort: 10 months, 9–11 hours per week
Assessments and certification: Grade of 70% or higher required to pass, from quizzes, projects, final exams in the first course, and 65% or higher in the second, third and fourth course.
Tools and programming language(s): Python, Jupyter notebooks, pandas, NumPy, Matplotlib, git, scikit-learn, NLTK, Spark, and PySpark
Costs: USD 1,260 (full program)
Pros: A fundamental introduction for all data science beginners covering many different topics, including a sound introduction into statistical concepts. Letter grading is offered.
Cons: The program gives a broad but not necessarily in-depth knowledge. Technical deepness must be studied by yourself and can take a lot of effort.
Credits: The MicroMaster will count as 30% of the full Master of Science degree in Data Science of the Rochester Institute of Technology. It also counts 25% (or 100 credits of the 400 credits) towards the Master of Predictive Analytics at Curtin University. Finally, completers will receive a favorable review of their application if you choose to apply to the Online Master’s Degree program in Data Science from UT Austin on edX.
Who should take that program: This course is designed for beginners in data science to get an overview from statistical concepts to the most used models and gives a flavor on deep learning and big data.
5. Predictive Analytics using Python — The University of Edinburgh
What you will learn: You learn basics of the predictive modeling life cycle, introduction to Python, preparation of data, data quality, under- and oversampling, training, validation, confidence intervals of estimators, linear and logistic regression, decision trees, random forest, neural networks, overfitting, and pruning.
Level: Advanced (graduate level)
Courses: 5 courses:
- Introduction to Predictive Analytics using Python (6 weeks, 8–10 hours per week)
- Successfully Evaluating Predictive Modelling (6 weeks, 8–10 hours per week)
- Statistical Predictive Modelling and Applications (6 weeks, 8–10 hours per week)
- Predictive Analytics using Machine Learning (6 weeks, 8–10 hours per week)
- Predictive Analytics Final Project (6 weeks, 8–10 hours per week)
- Undergraduate level of mathematics and statistics
- Some previous experience in programming like Python, Java, or C/C++
Lengths and effort: 8 months, 8–10 hours per week
Assessments and certification: A grade of 50% or above is required based on multiple choice and coding assessments; it requires a final project consisting of a theory-based written exam, a Jupyter notebook submission that reflects a real-life case study, and a 1,700-word reflective submission based upon the Jupyter notebook submission.
Tools and programming language(s): Python, NumPy, pandas, scikit-learn
Costs: USD 1,350 (full program)
Pros: A very sound technical introduction into modeling, model validation, sampling, and model comparison with a strong emphasis on data examples and programming.
Cons: The requirement of a grade of 50% seems low, but the effort especially, for absolute beginners in that field, will be higher as there is a strong emphasis on practical applications and programming.
Credits: When pursuing a corresponding master at the University of Edinburgh, 30 credits are awarded towards the 180 credits required for a full master.
Who should take that program: People who want to have technical depth in predictive analytics and develop strong programming skills than just a broad overview of many topics.
6. Statistics and Data Science — MIT Massachusetts Institute of Technology
What you will learn: You learn about probability models, Bayes’ rule, independence, discrete and continuous distributions, Bayesian inference, classical statistics, random processes, Markov chains, estimations, regressions, A/B testing, experimental design, data visualization, method of moments, and maximum likelihood, confidence interval, hypothesis testing, goodness of fit tests, predictive models, principal component analysis, overfitting, regularization and generalization, clustering, classifications, recommender problems, probabilistic models, EM algorithm, reinforcement learning, support vector machines, neural networks, and deep learning.
Courses: 5 courses:
- Probability — The Science of Uncertainty and Data (16 weeks, 10–14 hours per week)
- Data Analysis in Social Science — Assessing Your Knowledge (4 weeks, 10–14 hours per week) — prerequisite is first a passing grade in the course Data Analysis for Social Scientists by the MIT on edX (11 weeks, 12–14 hours per week)
- Fundamentals of Statistics (18 weeks, 10–14 hours per week)
- Machine Learning with Python: from Linear Models to Deep Learning (15 weeks, 10–14 hours per week)
- Capstone Exam in Statistics and Data Science (2 weeks, 10–14 hours per week)
- Single-variable and multivariable calculus
- Mathematical reasoning
- Familiarity with sequences, limits, infinite series, the chain rule, and ordinary or multiple integrals
- Vectors and matrices
- Proficiency in Python programming on a level covered by the course Introduction to Computer Science and Programming Using Python by the MIT on edX
Lengths and effort: 1 year and two months, 10–14 hours per week
Assessments and certification: Grade of 60% or higher is required based on lecture exercises, problem sets, homework, projects, and exams.
Tools and programming language(s): R, Python
Costs: USD 1,350 (full program)
Pros: It is a very comprehensive and rigorous program that teaches the mathematical and theoretical foundations of statistics and data science. Also, more than 20 universities around the globe count the credits towards their master’s programs.
Cons: The program is very academically driven, and there is less focus on the tools used in practice and the bridge to practical data science work. The prerequisites require additional courses not covered by this MicroMasters program.
Credits: Many universities around the world are transferring the credits of this program to their graduate programs. You can find the long list and all details on MIT’s dedicated webpage.
Who should take that program: People who aim for a rigorous mathematical and theoretical basis, and want to pursue a full master’s degree, are right with this program. Further, the credential of the name MIT opens the door for many other programs.
There are programs for any level of experience: for the data science beginner who either wants to have a broad or a profound technical introduction and the experienced veteran who wants to gain specialized knowledge.
The quality and the needed effort are comparable in all programs.
The purpose should guide your choice.
- Do you want to go for a full master’s program?
- Or, do you want to make your first steps in the data science field?
The program alone does not make you a data scientist. It provides you with a fundament. Then, it is upon you what you build on it.
Do you like my story? Here you can find more.
The Ultimate Guide on the AI Professional Certificates on edX 2021
Which of the six programs should you choose?
Are MicroMasters from edX worth it? ›
Yes, edX MicroMasters are worth it. This is because they are offered by top educational institutions and recognized by industry-leading companies. These industry leaders understand which talent gaps are in the workplace and what in-demand skills employers are looking to fill these gaps.Is MicroMasters in data science worth it? ›
The MITx MicroMasters Program in Statistics and Data Science is worth it. Designed for intermediate data science learners, the MITx MicroMasters program is worth getting for its Master's degree level of in-depth, instructor-led content, emphasis on statistics, structured schedule, and MIT branding for only USD $1500.Are MicroMasters worth anything? ›
Yes, MicroMasters® are definitely worth it. They offer great flexibility, come with official certifications and support from international corporations, and you can even try them without paying anything.How do you list edX MicroMasters on a resume? ›
You may add individual SCM Course Certificates and/or your SCM MicroMasters Program Credential to your resume or CV, listed in the Education, Certifications, or Accomplishments section. If you wish to add the MicroMasters Program Credential to your title styling, use the abbreviation "MM SCM".Can you fail a edX course? ›
If you did not pass the course with the grade required to earn a verified certificate, you can enroll in a future session if it's offered again. Most edX courses repeat in new sessions. Please note you will need to pay the verified certificate fee again.Do employers take edX courses seriously? ›
edX Certificates to Employers Mean A Lot
EdX's online courses and verified certificates are an excellent way to impress potential employers. The Massachusetts Institute of Technology and Harvard University established this online platform to provide optimal online learning solutions for adult learners.
EdX MicroMasters are recognized by employers because they are created by top universities and industry-leading companies like Walmart, GE, Ford, and IBM. These edX partners understand what in-demand skills workers need, so they have tailored these courses with that in mind.Is a MicroMasters a real degree? ›
MicroMasters programs are a series of graduate level courses from top universities designed to advance your career. They provide deep learning in a specific career field and are recognized by employers for their real job relevance.Is data science hard to master? ›
Because of the often technical requirements for Data Science jobs, it can be more challenging to learn than other fields in technology. Getting a firm handle on such a wide variety of languages and applications does present a rather steep learning curve.Are edX certificates valued? ›
Yes, an edX professional certificate is worth it. EdX courses and certificates provide students with the professional skills to advance their careers. Students take a self-paced course curated by prestigious universities.
Are edX certificates real? ›
Note: edX certificates are verified and recognized by future employers. edX doesn't only offer plans for individuals, it has plans for Businesses.Are edX degrees legit? ›
Is edX Legit? edX was founded by scientists from MIT and Harvard and has connections with universities across the globe, so there is no doubt that it is a legitimate company. It has a 4.5-star rating on TrustPilot, and 75% of students left 5-star reviews.Do edX certificates look good on resume? ›
The courses that are offered on edX are provided by the lecturers at the leading universities, so putting a certificate of completion from edX on your resume shows that you have what it takes to complete that course like those in the classroom and no one just glances over a Harvard certificate of completion.Does edX Harvard certificate have value? ›
Yes, it is worth it. Harvard online certificate programs will take you through high-quality education relevant to the interests you pursue. The online platform features highly interactive learning exercises, peer reviews, financial aid applications, and access to prestigious organizations.Are edX certificates verified? ›
A verified certificate from edX can provide proof for an employer, school, or other institution that you have successfully completed an online course.How do I get 90% off edX? ›
We encourage you to review the edX Honor Code.
- Step 1: Enroll in your desired course on edX.org. ...
- Step 2: Complete the Financial Assistance application. ...
- Step 3: Wait for the application decision.
If you can't find the answer to your question in our Help Center, you can contact the edX Learner Support team through our Contact Us form or click the Need Help button in the lower right hand corner of this page.What happens if I fail an edX exam? ›
If a student fails the onboarding exam, they will receive a notification listing the specific reasons for failure and they will be asked to retake the onboarding exam. They can also check their Onboarding status on the Proctortrack Dashboard.Can EdX certificate get me a job? ›
The essence of the certificate is to add value to the qualification or skills you claim to acquired. It will add to boost your closeness to getting the job. So employers at large care about these certificates.What is better EdX or Coursera? ›
Topics: Both platforms offer a diverse range of subjects. However, Coursera focuses more on professional training, for example computer science and business degrees. EdX offers numerous courses in the humanities and the natural sciences. Costs: Both portals offer audit versions free of charge.
Is EdX actually Harvard? ›
edX is an American massive open online course (MOOC) provider created by Harvard and MIT. It hosts online university-level courses in a wide range of disciplines to a worldwide student body, including some courses at no charge. It also conducts research into learning based on how people use its platform.Do employers really check certifications? ›
Many employers will ask you to do a test to see if you qualify for the job or even just for the next round of interviews. They are trying to filter out the unqualified applicants. Sometimes, if there are certain certificates or diplomas stated on the resume, they will ask you to present a copy of it too.Is MicroBachelors worth it? ›
edX MicroBachelors certificates are definitely worth it, considering they are for-credit, self-paced, and affordable. Most edX MicroBachelors go from $500 to $1,500, which is relatively low compared to other courses from this category.Do companies actually look up if you have a degree? ›
Only 53% of employers always check job candidates' education credentials. Slightly more than half of the employers surveyed, 53%, always verify the education credentials listed on a job applicant's resume. Among the rest, 24% sometimes check applicants' education records, while 23% never do.Are Online Masters respected? ›
Yes. Advanced degrees completed online have just the same value as if you were to attend class in person. Just look for one that's verified by one of the many accrediting agencies out there and backed up by U.S. News & World Report's highest level higher education rankings.How much is MIT MicroMasters data science? ›
Cost and Financial Aid.
|Our Tuition (2022–23 rate)||$3,100 per course ($775 per credit)|
|Average Tuition of Peer Institutions||$5,476 per course|
edX offers full online Master's degree programs which are top-ranked programs from the world's best universities. These Master's programs are affordable online graduate degrees with the same rigor as on campus programs, designed for easy, flexible learning for busy people.What is the hardest part of data science? ›
1) Finding the data
The first step of any data science project is unsurprisingly to find the data assets needed to start working. The surprising part is that the availability of the "right" data is still the most common challenge of data scientists, directly impacting their ability to build strong models.
If you have strong knowledge of algorithms, you can easily build data processing models. However, even if you don't have strong coding knowledge and a special degree in data science, you can still become a data scientist. With good learning capability, you can be a data scientist without a degree in it.Does data science require a lot of math? ›
Data science careers require mathematical study because machine learning algorithms, and performing analyses and discovering insights from data require math. While math will not be the only requirement for your educational and career path in data science, but it's often one of the most important.
Is edX accredited in USA? ›
No, edX is not accredited and does not have federal or state accreditation from the department of education. However, there are accredited degree programs on edX offered by many prestigious institutions such as: Harvard University. Massachusetts Institute of Technology (MIT)Can I get a 100% free certificate from edX? ›
edX courses do not award free certificates. Certificates are awarded only to passing students registered in the paid certificate track. The enrollment fee for this track varies by course. Most courses can be viewed in the audit track entirely free, but again will not award a certificate.Which is more valuable Coursera or edX? ›
If we compare edX vs Coursera, it's evident that edX has higher value for money than Coursera. Talking about the overall quality of content & learning material, if we compare edX vs Coursera, we can see that better content quality is offered by edX.Do edX courses repeat? ›
Most edX courses repeat usually at least once a year. Courses which are part of programs are expected to repeat more often. Please check our course catalog frequently for new course sessions. Also, for updates on new and repeat course runs, keep watching for our newsletter updates via email.Do edX courses affect GPA? ›
Admissions committee look at transcripts for cumulative GPA, standardized test scores, and how you answer the application questions. edX courses that do not have transcripts do not factor in the GPA, so the only way to introduce that you took these courses in your application answers.Can you put edX courses on LinkedIn? ›
You can add edX certificates to LinkedIn by saving them on your LinkedIn profile.Does edX provide hard copy certificate? ›
edX certificates are delivered online through edx.org. edX does not send physical copies of certificates by mail or email. Once the certificate is available, if you earned a certificate you will find a link to view this on your dashboard. A link will also appear in your profile and on the progress page in the course.Do employers consider Udemy seriously? ›
Yes, a Udemy certificate is valid for a job. Many students wonder if job recruiters value Udemy certifications, but this depends on the job you're looking for and your skills and experience.Is HarvardX part of Harvard? ›
HarvardX is a University-wide strategic initiative, overseen by the Office of the Vice Provost for Advances in Learning, to enable faculty to build and create open online learning experiences (free, low-touch, high-touch) for residential and online use, and to enable groundbreaking research in online pedagogies.Which is better edX or Udemy? ›
Accreditation: Udemy vs. edX. Udemy's competition certificates may look good on your resume, but they are not accredited. edX's completion certificates, on the other hand, are recognized, and you can take an online course from an accredited university.
How do I know if I passed edX? ›
Earning an edX certificate indicates that you completed the course with a passing grade. Your final course grade appears with other course information on your dashboard once the course has ended, and a complete record of your scores on all course assignments and exams appears on the course Progress page.Is an edX certificate worth anything? ›
Yes, an edX professional certificate is worth it. EdX courses and certificates provide students with the professional skills to advance their careers. Students take a self-paced course curated by prestigious universities.How credible are edX certificates? ›
Is edX Legit? edX was founded by scientists from MIT and Harvard and has connections with universities across the globe, so there is no doubt that it is a legitimate company. It has a 4.5-star rating on TrustPilot, and 75% of students left 5-star reviews.Are edX certificates legit? ›
edX is a credible platform for education and learning. It was actually founded by professors from Harvard and MIT and has more than 44+ million learners. Its courses are created and taught by some of the top-ranked universities and industry-leading companies in the world.Can edX certificate get me a job? ›
The essence of the certificate is to add value to the qualification or skills you claim to acquired. It will add to boost your closeness to getting the job. So employers at large care about these certificates.Is Harvardx the same as Harvard? ›
Harvard Edx is a branch of Harvard University dedicated to offering the university's highest quality courses to dedicated learners across the globe.Do colleges recognize edX certificates? ›
Most edX open courses do not directly award academic credit. Each educational institution makes its own decision regarding credit. Check with your university for its policy. Please note: edX open courses don't currently offer transcripts or proof of registration for the purpose of obtaining credit.Is edX or Coursera better? ›
Coursera would be a better choice, especially if you want to complete multiple courses and professional certificates through their Coursera plus package. If you are looking for university-level courses, you will do well on either platform, as both are university-backed platforms.Is edX actually Harvard? ›
edX is an American massive open online course (MOOC) provider created by Harvard and MIT. It hosts online university-level courses in a wide range of disciplines to a worldwide student body, including some courses at no charge. It also conducts research into learning based on how people use its platform.