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I just finished up back-to-back six-month contracts at Target and Alexion. They were great because they allowed me to work with the BIG brands and learn the “enterprise” way of doing things. 

It also allowed me to add my second “$billion” dollar project to my resume, as I had a chance to build and manage the launch of their database to support their $2 Billion investment with Black-Owned Businesses. In 2005, I also had the opportunity to work directly with the Google team that invested $1 billion in AOL.

Next up, no more projects; I am looking for a full-time staff role. If I had one takeaway from these projects, it is that I want the chance to build, implement, and drive — the end-to-end process for my next role. The previous projects gave me great tech and team insights, but once I built my piece, then I handed it off, and they took over its future. For the next job, I want to be in it for the long run,

I was recently added to the team at eCornell as a Course Facilitator for their certificate programs in Product Management and Marketing A.I.

I’m very excited to work with the eCornell team and be able to work day-to-day with their certificate students. Being that I have relied on self-study certificate programs as an independent contractor (note – spending my own money betting on myself), I feel these are very valuable.

Certified. There were some late nights. Full weekends. But it’s done. I completed the 9 courses that comprise the IBM Data Science Professional Certificate.

I never took these courses to become a Data Scientist. That’s a different level. I just wanted to make it easier to work alongside the data team, but in a product or client solutions role.

The certification requires the completion of 9 courses and is administered at Coursea. While we’re here, here’s a line to get 50% off your next course (in fact, we both would get 50% off) .

Here are the 9 course that I have to pass:

• What is Data Science?
• Tools for Data Science
• Data Science Methodology
• Python for Data Science and AI
• Databases and SQL for Data Science
• Data Analysis with Python
• Data Visualization with Python
• Machine Learning with Python
• Applied Data Science Capstone

If for whatever reason that you might to see data analysis from Toronto about a fictional business, then here are my links:

• Project Report – PDF write-up with analysis clips

• Blog Post on LinkedIn

• Project Code -Jupyter Notebook

So it looks like this is for real – everyone is home. This means making a list to stay on focus.

1. Confirm my current projects are strong – One has already gone into a ghost status so I’m not sure how they are going to move ahead considering that they are a small, family real estate group.
2. Move ahead – There’s no vacation for someone in spot that can sit back and roll with it, so I still need to find new projects and maybe focus more on those things that I was going to look into — like training.
3. Training — Look at that. Thanks to a special deal through Coursea, I am looking at pursuing my IBM Data Science Professional Certificate. After quickly completing the first course and looking ahead at the syllabus, I feel good about the intro courses around the concepts and applications for Data Science and AI, so that should be fine. It’s the latter courses in Python that might take extra time. I’ve coded a bunch in PHP, so it won’t be foreign to learn to code, but I’ll need focus.

Why do this? First, I have no intention of being a data scientist. Those people are wicked smahhht. However, I have frequently found myself in the room with the Data and Engineering teams, and I want to be better at talking the details that are there in every project.

I’ve surprised people — especially when they only thought of me as a marketing person — by pulling some SQL to test new segments, but I’m only proficient up to a point, and I would like to take the next step.

Since my primary role involves working from home, this idea of remote working is nothing new to me. It just means that there are more people around the house and there is no more 7am bus.

I think the biggest adjustment is not about the work at home idea, but it’s the idea that I can’t go anywhere; all my usual places that I run out to that help break up my day – yes, I’m mostly talking pizza places – are closed.

Hopefully this won’t be going on too long but I’ll keep using the time to move ahead.