Relevance Is Not Random: AI Reskill Challenge

Tracy Levine, Forbes Coaches Council

As businesses rushed to pivot their business models to support remote work and embrace automation, many overlooked — or were simply unaware — that the pandemic presented a massive transformation in workforce skills alignment. Professionals at all levels have to reskill.

Understanding Artificial Intelligence is important for all professionals.

Global spending on artificial intelligence (AI) is forecast to double over the next four years, growing from $50.1 billion in 2020 to more than $110 billion in 2024, according to the IDC Worldwide Artificial Intelligence Spending Guide.

The Career Accelerator hosted by Advantage Talent, Inc. accepted the Global Challenge to Understand Artificial Intelligence, Machine Learning, and NLP. Together we took the free University of Helsinki Elements of AI Class which was originality created to reach 1% of the European population.

How long does the course take? The official site says, "We expect it will take approximately 5-10 hours to finish each part of the course. (Total Time: (30-60 hrs.)

We asked a some of the Career Accelerator members to share reviews of the course including how hard they found the course on a scale of 1- 10.

I enjoyed taking this class and creating the study guides for the Career Acclerator. Before taking the class, I had a basic understanding of Artificial Intelligence, Machine Learning, and Neuro Linguistic Networks. There are so many business use cases for improving business effectives by leveraging AI, ML, and MLP. I enjoyed doing the Unit Exercises. If you are someone who likes solving puzzles you will find this course enjoyable.

Difficulty Level: I have strong math skills and love to do puzzzles. The class difficulty level of the class was a 7 out of 10 and takes about 20 hours to finish.

Artificial Intelligence and Autonomous Vehicles

The problem solving problem

Recommended

Likelihood Ratio

Neural Network

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I really enjoyed the course. My role in the group was student and tutor. It was great getting to know everyone who dropped in to attending like tutoring sessions.

I quickly figured out that there are multiple ways to look at some of the exercises, and after the first few questions, I began to ask myself ‘what else’ could come into play when considering each new question. Bonus: I dusted off some algebra that I hadn’t needed for several years, and it felt great to complete the course. Tools that helped me keep track of the info – Excel, Mindmup, MS Word, and (believe it or not) pencil and paper .

Difficulty Level: I had a good high-level understanding of AI before I began the course, and this course allowed me to expand my understanding at a more detailed level. Overall, I think this course difficulty rating is about a 7 when comparing it to other 20-30 hour courses.

I loved the challenge that the AI course brought on. As expected the logical areas were quite ‘easy’ for me even the more complex areas. But I found the Neuro section impossible to understand and was challenged visualizing the movement of the small and medium plates from left to right. I like to draw these movements out. I had limited knowledge about AI so this was mostly new to me.

Difficulty Level: I rate it an 8 in terms of difficulty level. I loved the class and would love to do more these types of learnings.

Before starting my tech exposure has been minimal, usually learning and seeing what is new through my middle and high school kids. Taking this course is starting to give me an understanding of how much AI is already incorporated into our day to day life and how the definition is constantly evolving and changing. How yesterday’s AI may not be considered AI today. Playing games such as chess is no longer considered that impressive for AI. It is now pretty much considered simple computing. But teaching a Robot how to grasp and pick up something is a much more sophisticated and advanced AI. As I go through the course, I am seeing how quickly AI is advancing and how it is likely to have a large effect on work and jobs that will be available to my children.

Difficulty Level: I would rate this course’s difficulty at a 7-8 out of 10. The big concepts are easy to understand but implementing them to solve some of the problems can be difficult.

Loved the class! Very well thought-through and structured to smoothly bring in a learner who doesn’t know much about AI. I did have good working knowledge of it from my Econ-Tech-Humans research. But! The challenge I loved was the Bayes theorem’s chapter 3 – very key in “getting” AI. The rest was super logical and almost easy. Loved the peer-reviewed essays part of the testing, especially the finals.

Difficulty Level: If you’ve had some statistics training or practice, this would be a 6, 7 or 8. If you had none, this would be more of a 9 or even 10. If you had a lot, this is probably a level 3 and just a great investment of your time to learn about awesome ways your science is applied in 2020 and make yourself more relevant and marketable as a professional.

I liked this course a lot! It felt broad-based, covered some very tough topics in an easy way, and even had a bit of humor sprinkled in for good measure. I really enjoyed learning about recommendation (classification) algorithms. As a classically trained engineer, I’ve dealt with regression methods and plenty of statistics before, but never had a more “down to earth” example of how this it’s used in everyday life. While I enjoy the technical, methodical science behind engineering, engaging in practical solutions that actually help people is my passion. Fortunately, that’s what this course was all about so I loved it!

Difficulty Level: Overall, in terms of difficulty, I’d rate it a 6 out of 10. Just about everything can be understood by reading the text or referenced articles and there is no time limit so it wasn’t particularly difficult nor stressful.

AI has been a buzz word for a while now, but I was surprised to learn that it goes back to 1950s and was used in the games first. Today there are numerous applications and many more will be emerging. The course has a good mix of general information and explanation of the math and algorithms.

Difficulty Rating: Would rate it at a 7 in terms of difficulty level. I have been reading mostly at night while tending to my newborn and can say that the course is very engaging and definitely sparks interest to learn more about AI.

HIPAA: An Uncertain Foundation in a Big Data World

Karyn Mullins

As the use and value of technology in healthcare continues to rise, the number of interconnected devices grows as well. Data and Electronic Protected Health Information (ePHI) shared across these interconnected devices create more opportunities for bad actors to attack.

The Uncertain Future of the Traditional College

Tracy Levine, Forbes Coaches Council

As the college graduate hiring rate declines to the highest number in decades, colleges are in the midst of an existential crisis.

The 5 Most Important Real(ity) Trends in 2021

Tracy Levine, Forbes Coaches Council

2020 will be remembered as a tipping point for technology acceleration. Automation is projected to erase 85 million jobs globally in medium and large businesses across 15 industries and 26 economies by 2025. While many are quick to point out that news jobs will be created, they are not being created at a rate that is as quick as jobs are being eliminated.

2020 Lessons Learned That Prepare Us for 2021

Judy Romano - Big Thinks Managing Editor

Skills – like being nimble, agile, faster decision making – learned during the pandemic must not be forgotten. Applying the leadership lessons learned during 2020 will help leaders flourish in 2021 regardless of the circumstances!

It is time to make predictions for 2021!

Rashmi Verma

Businesses that are recovering from the pandemic and looking to achieve differentiation in 2021 must consider the unconventionally changing people, processes, products, and technology trends in their strategies.
-Rashmi Verma

Big Thinks December 2020 Michelle Galvani and Sophie Galvani

2021: The Weaponizing of Storytelling Will Continue

Michelle Galvani-Big Thinks Contributor

AI software that can manipulate data. Interestingly, AI is also used to combat the spreading of false information. It is essential to understand how conspiracies are created and the threat that they pose to people’s right to objective news.

Tracy Levine, Forbes Coaches Council -