Let's face it, industry professionals, traditional programs can take years to catch up to the latest programming languages and frameworks employers are actively seeking. At Qwasar, we understand this struggle. One size doesn't always fit all when it comes to education. That's why we offer a range of flexible learning options designed to address your specific needs.

Qwasar announced a new Master's degree, new shorter learning courses, more flexible learning options, and longer pathways at Qwasar. The announcement comes as an adjustment to our traditional programs to better serve working learners and software professionals. 

We're excited for the launch of new, shorter courses in software engineering, data science, machine learning, and full stack development. Our new courses are specifically designed with the modern learner in mind, aligning perfectly with contemporary preferences for flexibility, personalization, and efficiency.

"The best way to predict the future is to create it," a timeless quote by Peter Drucker. Modern business is shifting, propelled by the engine of artificial intelligence and machine learning (AI/ML), particularly Generative AI. Companies hungry for the competitive edge offered by these technologies are facing a formidable roadblock: the acute scarcity of qualified AI/ML talent.

The demand for senior machine learning engineers, and other AI specialists is skyrocketing, but the pool of qualified candidates remains distressingly shallow. Traditionally relied-upon methods for attracting skilled individuals, including offering high salaries and recruiting from competitors, are proving to be unsustainable and may not yield desired results.

One of the reasons why companies are struggling to find qualified candidates is that there simply aren’t enough skilled professionals available. Senior ML engineers generally have 5+ years of experience. This means that 5 years ago, there should have been thousands of ML graduates going into thousands of entry-level ML jobs….those jobs didn’t exist and neither did the graduates. So, this is a problem with a physical limitation that can’t be remedied unless we invent a space and time machine! Therefore, companies have three choices: compete for talent and pay ridiculous salaries, wait to hire (which isn’t really a solution and can cost your company), or train talent that’s a “near neighbor” and ‘upskill’ them to be AI/ML engineers.

In today's competitive job market, the value of hands-on experience cannot be overstated. It's the bridge that connects theoretical knowledge to practical skills, and it often makes all the difference when it comes to employability and career success. This is especially true in the ever-evolving technology sector, where employers seek candidates who not only possess academic qualifications but also have the ability to apply their knowledge in real-world situations. “Entry-level jobs” in tech are renowned for demanding 3 years of experience - a chicken and egg problem at the core, but one that illustrates the value companies place on practice experience.

In today's ever-competitive job market, employers are continually seeking new and innovative ways to invest in the growth and development of their workforce. 

One approach that has gained significant attention is Qwasar’s groundbreaking initiative, the Dual Apprenticeship - Master’s of Computer Science Program, a two-year journey that not only transitions an apprentice into a full-time employee but also equips them with a master's degree. Combining an apprenticeship with a Master of Science in Computer Science (MSCS) degree is a unique opportunity to gain both the theoretical and practical knowledge needed for a successful career in the tech industry.

Qwasar's Master's Program is offering an innovative and intensive learning experience that bridges the gap between education and the real-world job environment.

Areas of apprenticeship specialization that can be integrated with a Master of Science in Computer Science (MSCS) include:

• Backend Software Engineering
• Embedded Engineering
• AI/Machine Learning Engineering
• Full Stack Development

In today's tech-driven world, the demand for skilled embedded engineers is skyrocketing as industries ranging from automotive to consumer electronics rely on embedded systems to power their innovations. However, the availability of qualified embedded engineers doesn't meet the growing demand, creating a significant talent pipeline problem. 

This use case explores the challenges of this shortage, the role of programming languages, and how advanced engineering apprenticeships can expand the talent pool, using Qwasar's Embedded Engineering Program as a prime example.