This course from Stanford University online was split into 10-modules over 5 months.

The material covered a lot of ground, including elements similar to things I learned at INSEAD under the guise of courses in Organizational Behaviour, but also in Strategy and even Decision Making.

Two things stuck out for me, from the whole course;

1. The criticailty of keeping people with the "dark triad" of personality characteristics OUT of your organization.

2. The reason so many people in so many organizations think change is difficult. When it really isn't. 😣

A wonderfully practical course from the University of Michigan, this course was split into 5-modules - one per month.

These covered machine learning, text mining, social network analysis and data representation/visualization using the modern Python libraries. It is amazing how much the availability of the libraries in Python now make complex data analysis and presentation tasks almost trivial. There are libraries of code that do almost everything.

Even without a data team, it's possible to do predictive analytics, etc, "easily". It is astonishing.

At the end of the day the question really is "What business insights do you need?"

Most companies can't answer that one. It's the starting point.

A beautifully taught course from the University of California, this course was split into 3-modules - one per month.

While the main topic is the Go language with its simple structure and its excellent handling of concurrency, one of the main features of this course was the quality of the instruction.

Even though he was only doing it in passing, the Professor explained many often-confused computer topics with great examples and clarity of expression.

Plus, he did a great job explaining how Go simplifies things that Java (or many other languages) makes complicated; how Go allows massive concurrency better than anything except (probably) Erlang; and how to do complicated things simply.

• Salesforce

  • Salesforce Trailhead, an ongoing activity, covering both Service Cloud and Marketing Cloud.

  • While I've never gotten formally certified on Salesforce, I've worked with it pretty extensively and am at the 5th of the 7 available levels on the Salesforce Trailhead system.

• VAEX

  • VAEX is a data analytics system that works within Python. It makes analysis of very large data sets actually easy, even on home PCs or laptops.

  • Its capabilities allow even large organizations to do arbitrarily large data analytics cheaply.

  • See here for an example

• Apache Superset

  • Superset is an open-source business intelligence tool. While it's easy to use Tableau or PowerBI or Spotfire, they can be VERY expensive in a large organization.

  • Open source tools can be powerful alternatives.

• Apache Airflow

  • Apache Airflow is an open-source workflow management platform. It allows automation of complex data flows and tasks. It's also now been launched as a service by Google.

  • This can be hugely important in complex enterprise contexts. And much safer than what many businesses do, which is to use Excel macros or to do things by hand. 😨 Airflow is ALMOST easy, at least for basic use cases.

• RPA (UI Path)

  • Robotic process automation has been around for a while, but has seen huge strides recently.

  • Systems like UI Path are leading the way in terms of functionality. It's in wide use in financial institutions. While I used robotic automation years ago at Google, I'm just getting started on this specific tool.