“Really? You graduated this year and most of your programming was in C++?” I replied in astonishment.
My young co-worker, with whom I was sharing lunch, shared with me that his college training was very different than his current assignment. I was flabbergasted to hear that his education at a major university employed a decades-old programming language. I’d graduated in the 1990’s and had also learned in C++. Why was his college training so dated?
This was not the first time I’d heard such a story.
“I don’t consider going to college evidence of exceptional ability.”
– Elon Musk
New Needs for Students
Increasing evidence suggests it’s flawed to assume that a 4-year degree is required, preferred or the best path for high-potential young minds. The skills in great demand today are often best learned in applied, real-world situations. These practical learnings remove the artificial reality of a classroom while introducing complexity and rewarding flexibility.
Often the “best” solution isn’t necessary. Further, technology and associated applied skills are advancing so rapidly that traditional higher education institutions are years (and sometimes decades) behind.
During a recent course development, we found that multiple tools had evolved over the course of a few weeks! Technology is moving fast and accelerating in nearly every industry.
I believe most college age learners would have a better, more enjoyable, more valuable learning experience if they considered a hybrid approach:
Find the best instructors in the world for skills you will build upon. If these aren’t available locally, look for online options. The unfortunate reality is that in-person introductory courses are often led by the least qualified faculty.
Seek out internships where you have an opportunity to stretch yourself under the real-world pressures of timelines, budget and quality constraints. Research measures nearly 50% more knowledge retention where learners are actively participating. The use of simulation, role playing, and projects are known to create deeper understanding. The applied learning format has an additional benefit of a mutual “test drive” where you can experience a role and working environment without having to make a long-term commitment.
Young learners and established professionals learn best when they form cohorts. The combination of collaboration and accountability is powerful. Not everyone is great at everything, understanding your relative strengths and weaknesses will help you find paths where you are most productive. Further, learners who develop early understanding of how to maximize the impact of their efforts within a team will be well positioned for future leadership.
Does this mean avoiding college altogether?
Does it suggest that spending four years studying a major that you’re not sure you even want to pursue is risky?
We suggest creating a couple of alternative paths to consider beyond a traditional 4-year experience. For example:
Four Plus One
Often, college programs will encourage summer internships as students approach graduation.
We suggest considering taking two additional semesters to fully immerse in a role as a junior team member or intern.
This “extra year” has financial benefits (you’ll earn income) and maximizes learning during the final semesters.
Two Plus Two
A slightly more unorthodox approach is to branch away from formal college after two foundational years.
With these two years, students can begin their career in earnest while considering additional training on the job or through alternative sources (online or night-school).
Our team offers world-class training to over 1,000 learners annually through our Statistics.com training platform. I am proud of how we are helping to train the next generation of data scientists and engineers. We serve the world’s largest organizations with customized learning programs developed to address specific business needs.
Evolution of Data Analytics Education
Higher education has struggled to keep up with the accelerated innovation required by businesses as well as the training required by a growing population of analysts. The pandemic has accelerated the need for high quality education delivered in a format which is at least as engaging as traditional classroom style, without the requirement for physical co-location.
By leveraging technology and our experience data science and statistics education, Statistics.com has remained flexible and able to meet the real-time needs of students, analytics teams, and organizations more broadly.
Real-World Education from Real-World Practitioners
The Statistics.com brand is the training platform of Elder Research. With over 100 data scientists and engineers, we leverage the wisdom gained by solving a wide variety of real-world problems over the last 25+ years to infuse our education programs on Statistics.com with the cutting-edge training that will advance students’ careers.
Creating Value for Students
From the start, the Statistics.com platform has created value for their students though being the first online education institution to be approved by the American Council on Education (ACE). We now offer over 90 analysis-focused courses and counting, including courses on topics such as MLOps, Data Literacy, AI Programming, Text Mining, Marketing Analytics, Operations Research, Healthcare Analytics, and much more.
Statistics.com continues to evolve to meet the changing needs of professionals and employers, developing diverse analytic skills that will equip students with in-demand capabilities that can be applied on day one. As a result, many of our students become life-long learners at Statistics.com.
Saul believes that training is a fundamental element of every successful consulting engagement. As Managing Director of Training Services, Saul helps clients realize the full value of engagements and to maximize team member potential.
Prior to Elder Research, he served as COO and co-founder of Metis Machine, a machine learning and deep learning platform company focused on helping clients use machine learning and AI to solve business problems. Saul has served at several start-ups including General Electric’s first cloud-based predictive analytics initiative. He is a frequent guest lecturer at the University of Virginia on topics such as operations, analytics, and strategy.
Saul earned an MBA at the University of Virginia and a BS in computer engineering from the University of Florida.
As a resident of Charlottesville, Saul enjoys exploring the Blue Ridge Mountains with his wife and children.