Google launches online coding course to train workers for tech jobs

“The program, called the Google IT Automation With Python Professional Certificate, will be available through the online education service Coursera. It’ll be a six-course program in beginner-level Python, which will culminate in a final capstone project focused on programming for automation.”

Image credit: CEO Sundar Pichai announced Grow With Google three years ago by Andrew Federman

The Ultimate Guide to Getting Started in Data Science

“I recommend checking out:

Obviously, that’s what worked for my learning style and I chose to learn Python. If you have courses you’ve liked, share them in the comments!

If you want to start learning to code, you could check out:

Photo by Robert Anthony Carbone from Pexels

“I want to learn Artificial Intelligence and Machine Learning. Where can I start?”

“How did I get started?

I stumbled across Udacity’s Deep Learning Nanodegree.

My Self-Created AI Masters Degree

I’ve put together some of my favourite AI, machine learning and data science resources into a nice table (from the Trello board). You can see them here.

Getting a job

Nick, the CEO, Athon, lead machine learning engineer, and I went for coffee.

“How would you like to join the team?”

Sharing your work

Whether it be GitHub, Kaggle, LinkedIn or a blog, have somewhere where people can find you.

I’ve completed courses from (in order):

Daniel Bourke

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Wisdom for AI

I’ve reviewed our top performing posts over the previous 12 months, and they all revolve around the topics of: learning, training, education and wisdom.

With that in mind, here’s a quick summary of the most impactful content.

Udacity launches nontechnical AI product manager nanodegree

An executive’s guide to AI – McKinsey

Become an AI Company in 90 Days

“AI For Everyone”: Course Review & Key Takeaways

The 7 steps of machine learning

2019 AI eCommerce Spotlight Awards

“AI For Everyone”: Course Review & Key Takeaways

“Let’s recap what we have learnt in this course:

First week: AI technology, what is AI and what is machine learning? What’s supervised learning, that is learning inputs, outputs, or A to B mappings. As well as what is data science, and how data feeds into all of these technologies? What AI can and cannot do?

Second week: What it feels like to build an AI project? What is the workflow of machine learning projects, of collecting data, building a system and deploying it, as well as the workflow of data science projects? How to carry out technical diligence to make sure a project is feasible, together with business diligence to make sure that the project is valuable before you commit to taking on a specific AI project?

Third week: How such AI projects could fit in the context of our company? Examples of complex AI products, such as a smart speaker, a self-driving car. What are the roles and responsibilities of large AI teams? The AI transmission playbook, what are the five-steps for helping a company become a great AI company?

Last week: AI and Society. What are the limitations of AI beyond just technical ones? How AI is affecting developing economies and jobs worldwide?”