It’s Like Comparing Apple Pie To Apples.


There is a reason why Massive Open Online Courses (MOOCs) have an average of less than 15% completion while NCLab has a completion rate of over 90%; NCLab’s in-depth training programs are fundamentally different from various online courses offered by MOOCs such as Coursera, Udemy, Udacity, Linkedin Learning (formerly, and others. Here is a brief overview of the main differences.

Different Objectives

NCLab provides comprehensive training programs, which were designed collaboratively by university and industry experts to meet several key objectives:

  • Thoroughly screen applicants to make sure they can learn and apply new knowledge and will be successful in completing the training.
  • Provide trainees with enough hands-on practical experience to make them job-ready, at a time when well over 95% of job openings require experience.
  • Prepare trainees for industry-recognized certifications including ACT Workkeys Applied Math and NCRC, TOSA, CompTIA Data+, and Python Institute PCEP and PCAP.
  • Make sure that trainees get noticed, succeed in the job interview, and get hired. This includes, among other things, creating a strong resume, Linkedin and Github pages, providing trainees with a portfolio of capstone projects designed to attract the interest of employers.
  • Provide trainees with important soft skills required by employers, to make sure they will be successful in the workplace after they are hired.

In contrast to that, MOOCs offer a large variety of stand-alone courses dedicated to bite-sized topics and allow students to make their own course selections, rather than making them complete all-encompassing training programs and they provide a negligible amount of hands-on practice compared to NCLab, even though practical experience is required by virtually all employers.

Finally, MOOCs do not teach soft skills, which require one-on-one interactions with people who oversee the trainee’s progress. 

Applicant Screening

MOOCs, including Coursera, do not screen incoming students in any way. They enroll anybody, using the “add to cart” method. This approach is fundamentally flawed, because not everybody has an aptitude to successfully complete the training. In contrast, NCLab uses a proprietary detailed Computational Thinking Assessment, which measures the applicant’s ability to absorb and apply new knowledge and skills. This minimizes the number of dropouts and is the secret behind NCLab’s greater than 90% completion rate.  

Knowledge vs. Skill

To fully appreciate the NCLab training method versus learning with MOOCs, one needs to understand the profound difference between theoretical knowledge and practical skill. Knowledge is intellectual understanding of information, allowing an individual to know the right answers. MOOCs teach knowledge, but knowledge alone is not sufficient to be job ready. There, the key success element is having the necessary skill and practical experience. By skill, we mean an individual’s ability to solve practical tasks and problems at hand, applying the methods learned, while using their prior practical experience in the process. For example, in both NCLab’s Data Analyst and Python Developer training programs, the trainee has to successfully complete over 300 mini-projects that demonstrate skill in applying the knowledge that has been acquired.

For illustration, understanding the notes in a music sheet is knowledge. But being able to play the music on the piano is a skill. MOOCs do not provide students with enough skill and practical experience to be job ready.

Different Approach to Training

Data Analytics and Python Programming require the knowledge of certain theoretical concepts, but for the most part, it is a skillset. One can’t become a job-ready Data Analyst or Python Programmer, just like one can’t become a skilled pianist, by watching instructional videos provided by MOOCs. For this, one needs lots of supervised practice, individual attention from an expert, and even some initial hand-holding.

Providing trainees with skills and practical experience is the key difference between NCLab training and MOOCs learning. NCLab training consists of 100% AI-assisted supervised practice, which is the only way to make trainees job-ready. NCLab trainees also receive lots of individual instructional support by live instructors, and individual 1:1 coaching. That’s something MOOCs simply do not do.

All MOOCs claim that they provide practical experience, but in reality the amount is negligible compared to NCLab. Furthermore, it is unsupervised, and utterly insufficient to make trainees job-ready. Without supervision, a large proportion of students get little or no benefit from assignments, and only a handful of the most persevering ones succeed in their MOOC learning. 

The Role Of Certification

While employers place significant value on industry-recognized certifications, passing a certification exam should not be a goal in itself, since taking a test is quite different from being job ready. Job readiness can only take place with practical experience, which can’t happen in a few dozen hours. Furthermore, most MOOCs issue their own certificates of completion, which are not industry-recognized and have questionable value:

“A Coursera certificate alone is unlikely to land you a job.” 

Soft Skills Are Essential for Trainee Success

In contrast to MOOCs, NCLab provides 1:1 coaching. Coaching is a necessity for trainees to stay on track and complete the training on time. Coaching is also essential in teaching the trainees important soft skills required by employers, including among others, problem solving, critical and logical thinking, perseverance, professional communication, time management, and adaptability. MOOCs do not teach any of those soft skills.