Udemy published an article on Wednesday outlining the key findings of its 2021 Workplace Learning Trends Report.

The report detailed training courses that have seen a surge in demand on Udemy for Business, the company’s online learning platform.

The company also analyzed organizational “learning behaviors” to identify six trends Udemy believes will “define the workplace in 2021.”

“While much of this year has been uncertain, one thing has become undoubtedly clear,” said Shelley Osborne, VP of learning at Udemy, via email. “The future of work many of us have been talking about is no longer an eventuality — it’s our current reality. Around the world and across industries, organizations are fundamentally rethinking every aspect of how we work. As we look ahead to what the workplace will look like in 2021 and beyond, our recent report shows that continued upskilling and learning agility will be required to keep pace with our ‘new normal.'”

Data scientists with the right combination of skills are in high demand.

But what are hiring teams on the lookout for?

As with many roles, both technical expertise and soft skills are important. As data scientist Vin Vashishta writes, data science without soft skills has “limited value to the business”.

An increasingly diverse skillset is proving essential to data science and its future. “Very non-typical skillsets” are getting more attention, says head of data science at Aon’s Centre for Innovation and Analytics (ACIA) Jennifer Cruise.

“These skills are drawn from across mathematics, statistics and computer science, but you don’t have to be a mathematician or a computer programmer to pursue careers in data science, artificial intelligence or any of the other STEM areas.”

This video features Scott Hunter who is the PM director for the .NET team.

We chat about the challenges that come with growing your scope, applying the lessons learned in startups and consulting to large corporations, and his early days working on BBS (bulletin board systems) for fun lead to meeting the people he’d need to know to grow his career.

Chapters:

  • 00:39 – Meet Scott Hunter, Director of Program Management for .NET
  • 01:46 – What does a director of program management do day to day?
  • 05:26 – How did Scott managed his transition to director of all of .NET from his previous role?
  • 08:41 – How did Scott get the role? Taking initiative to find the right place.
  • 12:31 – Growing scope and managing perceived identities, from ASP.NET to just .NET
  • 17:31 – Why team cultures differ and don’t align even when they ship in the same product
  • 19:14 – How did Scott learn and build the skills to make these transitions? Practicing integration in early startup days,
  • consulting.
  • 22:47 – Most important lesson from previous managers: Don’t surround yourself with people like yourself and building a team with diverse opinions
  • 25:13 – Deciding between going with a new project or continuing along on a journey not complete.  
  • 28:00 – Accidentally attending Microsoft’s conference and joining Microsoft
  • 31:55 – Moving from dev to PM and learning communication skills
  • 33:45 – Becoming a manager and intentionally stopping himself from coding
  • 37:20 – How did Scott into computers? Typing programs into the Commodore PET he stole from his dad.
  • 38:35 – Scott’s history of working on Wildcat BBS to avoid forklift driving
  • 41:52 – Turbo Pascal and hanging at Anders Hejlsberg’s house and serendipity
  • 43:58 – Failing his first Microsoft interview, knowing what you want.
  • 45:36 – Trust your internal sense of when to act fast

The pandemic has changed the world and the tech industry job market along with it.

Here’s an overview of the jobs that are thriving and the jobs that are waning in light of the pandemic.

Takeaway: Many tech careers are still in demand, even though the pandemic has wiped out millions of jobs across the board. Learn how to transition into these lucrative positions. The information technology (IT) industry led the 21 st century in job demand and often hovered around the top in […]

While jobs may be few and far between amid the ongoing economic downturn, some companies have leveled up their hiring to fill various positions in emerging technologies.

Top of this list is computer vision, which has emerged as one of the most promising technologies today.

Triggered by newer applications amid the Covid-19 pandemic, the potential of this technology has expanded within a very short space of time. This has given rise to numerous virtual conferences in recent times that explore the depth and breadth of this technology. To be held on August 13 and 14, Computer Vision DEVCON is one such conference that brings together practitioners and enthusiasts of computer vision on one platform.

As AI adoption increases across industries, new job roles are being created to actualize this technology. A

report by Indeed indicates that AI and ML related jobs increased almost a hundredfold between 2015 and 2018.

Other newer roles will certainly come up in the future as the field grows and matures.

Here’s a great compilation of resources to help you get started in this field.

You are probably already using AI without even knowing it! You must have scrolled through the recommended products while shopping from any online shopping site, or used Google, Alexa, or Siri voice assistants, or in fact, watched a suggested movie on Netflix. As such, you are already part of […]

This unprecedented lockdown is an opportunity to really dig in and work on data science projects. A lot of folks suddenly have time on their hands which they did not see coming.

Why not utilize this time and work on grooming yourself for your dream data science role?

Overview The ideal time to work on your data science portfolio with these open source projects From datasets on COVID-19 to a collection of AutoML libraries by Google Brain, there’s a lot of data science projects to learn from Introduction We are living in the midst of an unprecedented […]

Deep learning can be a complex and daunting field for newcomers.

Concepts like hidden layers, convolutional neural networks, backpropagation keep coming up as you try to grasp deep learning topics. Most people are put off of the math alone.

Despite what you have been led to believe, you don’t need an advanced degree or a Ph.D. to learn and master deep learning.

There are certain key concepts you should know (and be well versed in) before you plunge too far into the deep learning world.

The five essentials for starting your deep learning journey are:

  1. Getting your system ready
  2. Python programming
  3. Linear Algebra and Calculus
  4. Probability and Statistics
  5. Key Machine Learning Concepts

While the demand for data science skills continues to rise, the specific skillsets around that demand has remained fairly consistent, according to a Jeff Hale analysis.

TL;DR: You can’t go wrong by learning Python.

Given how fast technologies in the data science space seem to rise and fall (remember Hadoop?), even over the course of a year we might expect to see more variance in technology preferences. Instead we find a (somewhat) remarkable stasis, one that continues to remind us: It’s never a bad time to learn Python.