Summary:
- It’s becoming increasingly important to learn how to think about implementing AI when building products
- Amazon recently open sourced over 30 internal ML/AI courses nicely structured into lessons and curriculums
- Product managers and business leaders will find only a few of them relevant, but it’s a great place to start
A little over a month ago Amazon made their internal AI and Machine Learning education available to everyone. This is the same training Amazon offers to their employees, and now it’s available to you at no cost.
Over the last few weeks, I took all of the Amazon AWS AI and ML courses which totaled about 25 hours over 31 lessons.
What I found is that there are only six courses which I would strongly recommend to product managers and business leaders. The rest are fairly deep into writing actual ML code or AI-related math. Scroll down if you already know how AWS Training works and want the course links.
When I started going through the courses, I had two objectives:
- Get a better understanding of AI terminology and considerations for building ML products
- Learn enough to build AI MVPs
As I worked through a few lessons and explored getting hands-on experience by creating a simple image classifier, the “hello world” of AI, it quickly became apparent that there’s a steeper learning curve here than I was willing to invest time into. The friction helped me take a step back and consider if learning how to do ML is valuable for product and business people.
A few days later during a great conversation with my friend and deep learning researcher at Preferred Networks, Kevin Connolly, he made a great point that for product and business leaders it’s far more critical to understand what’s possible with ML rather than how it’s done. The field is moving quickly enough that keeping up with the details of technical implementation is not only a full-time job but a full-time job and a hard one at that for a dedicated ML researcher. Product managers should have enough understanding of what’s feasible while avoiding limiting themselves by not thinking ambitiously enough.
It really does seem that AI product building is more akin to working with Agile or A/B testing frameworks in that AI is an approach along with being a tool. For each product, you will start asking an entirely new set of questions such as “Does this problem need to be solved with ML?”, “How difficult is it to get labeled data?”, “What are the most helpful inputs?”.
Learning how to apply this new framework for building products will put you ahead of many other folks in our industry. Just like you learned to consider statistical significance in multivariate testing, to write great user stories or look at burndown charts, so will AI terms like “precision” and “recall” enter your lexicon and become a part of daily conversations. You will consider the costs of cleaning and storing your data. You will get together with your ML-engineers and discuss how frequently you need to retrain your models.
There are many new things to learn.
Let’s look at how AWS Training and Certification can help.
What is AWS Training and Certification?
There are over 400 courses of free digital training from AWS experts across many subjects ranging from working with specific AWS services to broad concepts. Lessons vary from 10-minute videos to multi-hour lectures with quizzes and hands-on labs.
What do you get from completing the courses?
After completing each course, you will receive a Certificate of Completion with your name and the course taken. Please note, this just states that you have completed a specific training lesson. It’s different from AWS Machine Learning Certification for which you need to prepare and take in-person exams. At this time, I did not find any certificates that would fit a non-practitioner as all current certification is designed for data scientists or folks interested in selling Amazon products and services.
You will also have a Transcript where you can see all of your courses and access the Certificate of Completion for each of them.
How to enroll and start learning?
Go to www.aws.training and click on “Let’s Get Started.” Use your Amazon account to log in, and it will take you to your dashboard.
From there, jump into the Learning Library, and you’ll want to filter all the courses by clicking on “Domain” and selecting “Machine Learning.” You can also filter on Language to further reduce the list.
Content
There are different types of training:
- Videos — ranging from a couple of minutes to 20+minute lectures
- E-learning — multiple videos grouped by topics
- Curriculum — set of Videos & E-Learning courses. If you complete a video or e-learning independently, it will be marked as completed when you take a curriculum.
Training for Product and Business people
So which content should you check out? I think the courses below will provide the most value for Product Managers and Business Leaders (including execs). Completing these lessons will go a long way in changing how you think about incorporating AI into your products. The terminology you pick up will also improve your ability to communicate with Data Scientists and Machine Learning Engineers.
- What is Artificial Intelligence? (10 minutes)
- What is Machine Learning? (10 minutes)
- Machine Algorithms Explained (25 minutes)
- Machine Learning for Leaders (10 minutes)
- Machine Learning Terminology and Process (1 hour but excellent content)
- Intro to Deep learning (20 minutes)
The two courses below have some great content but also include in-depth coding which you can skip.
- Building Recommendation Systems with MXNet and GluOn (1 hour but some great use case examples)
- Data Science Capstone: Real World ML Decisions (50 minutes. You can stop when coding starts)
To wrap up
So there you have it, with just two and a half hours you can get up to speed on AI and be able to start intelligent conversations about taking your products to the next level. AI is evolving rapidly across many areas with what seems like daily advances across all subdomains (vision, audio, NLP, forecasting). It’s important not to delay and start applying these remarkable new capabilities by treating AI as both a tool and a framework for product development.
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Best Amazon AI & ML courses for Product Managers and Leaders. was originally published in iheartpm on Medium, where people are continuing the conversation by highlighting and responding to this story.
