Coursera has introduced two new types of credentials and has  Data Science offering for both of them. The new MasterTrack courses will be of interest to those looking to gain a Masters Degree while the Professional Certificates are more career-oriented.

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With online learning becoming widely accepted and data science so heavily in demand Coursera's new options are going to appeal to a lot of people.

Answering the question "What is a Master Track™  Certificate", Coursera's answer is:

With MasterTrack™ Certificates, portions of Master’s programs have been split into online modules, so you can earn a high quality university-issued career credential at a breakthrough price in a flexible, interactive format. Benefit from a deeply engaging learning experience with real-world projects and live, expert instruction. If you are accepted to the full Master's program, your MasterTrack coursework counts towards your degree.

The Arizona State University's Big Data MasterTrack Certificate can be seen as a stepping stone to the Master of Computer Science degree program which we have previously reported on. Students who gain a B or better on your their attempt in all three of the courses in the MasterTrack will be eligible for ASU’s Master of Computer Science degree program and will have gained 9 of its 30 required credits.

Students joining the Big Data MasterTrack Certificate, enrollment in which next closes December 12th, 2022 will choose three of four courses each of which includes: 

• Pre-recorded videos
• Live sessions and office hours
• Real-world projects
• Peer collaboration
• Web and mobile access

and requires 15-20 hrs effort per week. 

The courses are:

• CSE 511 Data Processing at Scale 
• CSE 572 Data Mining
• CSE 575 Statistical Machine Learning 
• CSE 578 Data Visualization

Each of these has an associated project to apply the knowledge being acquired.

The entire MasterTack Certificate takes 4-6 months to complete and costs a total of $4,500. By the end of it students can expect to be able to: 

• Develop exploratory data analysis and visualization tools using Python and Jupyter notebooks
• Apply design principles for a variety of statistical graphics and visualizations including scatterplots, line charts, histograms, and choropleth maps
• Apply common data mining algorithms to discover relationships and patterns in large datasets
• Implement more advanced learning algorithms such as deep learning and reinforcement learning
• Perform scalable data processing operations in cloud computing environments

Enrollment has also opened for the University of Chicago's Machine Learning for Analytics MasterTrack Certificate which costs $4,000 in total for 4 courses requiring 5 months of online study. According to its blurb:

You’ll learn to apply mathematical theory and decision making techniques that are vital to solving business problems through real-world projects designed by instructors from the University of Chicago. You’ll also benefit from graded instructor feedback and live sessions with groups of high-caliber peers.

While still subject to change, participants are expected to learn to:

• Build an analytical model and interpret the results
• Conduct exploratory analyses via single-mode and multi-mode cluster analyses
• Conduct predictive modeling via Logistic Regression, Multinomial Logit, Classification, and Regression trees
• Perform exploratory and confirmatory analyses using Python
• Recognize, describe, and apply a variety of statistical techniques for univariate and multivariate statistical analyses

The other new credential invites you to:  

Get Job-Ready with Professional Certificates

with programs costing from $39 USD per month, a limited time offer currently available,  and some of them involving companies as "hiring partners". 

The data science option for this credential is the IBM Data Science Professional Certificate and its blurb states:

It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. We start small, re-enforce applied learning, and build up to more complex topics.

Upon successfully completing these courses you will have done several hands-on assignments and built a portfolio of data science projects to provide you with the confidence to plunge into an exciting profession in Data Science. In addition to earning a Professional Certificate from Coursera, you will also receive a digital Badge from IBM recognizing your proficiency in Data Science.

IBM Data Science  has six courses at beginner level followed by two at intermediate level, each of which includes a project, and, as with a Coursera Specialization, the Professional Certificated is topped off a capstone project, specifically the Applied Data Science Capstone. The courses which are described as being designed to providing participants with the latest job-ready skills and techniques are:

1. What is Data Science? 6 hours
2. Open Source tools for Data Science 7hrs
3. Data Science Methodology 7hrs
4. Python for Data Science and AI 11hrs
5. Databases and SQL for Data Science 12 hrs
6. Data Analysis with Python 10 hrs
7. Data Visualization with Python 9hrs
8. Machine Learning with Python 15 hrs

Students get to have hands-on experience in the IBM Cloud using real data science tools and real-world data sets. 

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