2 Hour Meta-Project: Project Manage Your Data Science Learning

Get a handle on your learning priorities.

Photo by Alvaro Reyes on Unsplash

Many of us are struggling to prioritize our learning as a working professional or aspiring data scientist. We’re told that we need to learn so many things that at times it can be overwhelming. Recently, I’ve felt like there could be a better way to organize my own learning path as a data professional. This weekend, I decided to create and finish a meta-project to guide my own professional development journey. Luckily, I rediscovered the project management tool Monday.com to help me.

monday.com is a project management tool that enables organizations to manage tasks, projects, and teamwork.

I was introduced to Monday.com when I worked as a project manager in the civil engineering industry. We used it to track leads and keep tabs on our project portfolio’s performance. Whenever we would gain a new lead, we’d add it to our “Leads” dashboard. When we won a contract, we’d add it to the “Ongoing Projects” dashboard. Even our CEO used it to track monthly and quarterly sales performance. It didn’t occur to me until recently that I could use it to project manage my own data science journey.

Note: I am in no way affiliated with Monday.com or Udacity.com.

Here’s my own learning management board that I created in 1.5 hours.

This has helped me lay everything out that I want to learn, set hard deadlines for when I need to complete projects, and visually assess what’s a high priority.

You can also see a Kanban table here that is commonly used by project managers in software development.

I challenge you to create your own free personal Monday.com dashboard. Ideally, this meta-project should take you less than 2 hours — if it takes more than that, your tasks are too granular and you need to step back and think about the big picture. By completing this meta-project, you’ll not only be organizing your own learning, but you’ll also be able to show employers that you have project management skills and soft skills that are often overlooked in traditional data science curriculums. Discussing your learning management dashboards will show that you’re organized, serious about learning, and forward-thinking.

There are a number of varying roles that data professionals can take on. However, the bulk of employers are looking for people who:

• Prioritize tasks
• Can coordinate work dependencies
• Have the ability to work on multiple concurrent projects and interface with all levels within the organization.
• Work with stakeholders who have competing priorities
• Can communicate clear milestones and deliverables

By creating your personal work dashboard, you can show that you’re prioritizing learning X over Y (prioritizing tasks). You’re also acknowledging that you may not be able to do X project before learning Z skill (work dependencies). Your own learning journey may present topics that have competing priorities (stakeholder management).

Should I learn this new machine learning algorithm before improving the existing work on my GitHub profile? Your answer: No, it’s a higher priority to improve the documentation of current projects in my repositories first.

Do I really need to complete this project before I apply for jobs? Your answer: According to my job search timeline, I need to have my work portfolio ready by September 25th. So yes, I do need to spend more time finishing this project because it will be crucial to discuss it in my application.

You can even create a board for applying to jobs, interviewing, and networking. I went from this:

To this:

Parting thoughts. I hope this project gives you some clarity on how to manage your learning. It definitely has helped me look back and celebrate my achievements, and to also envision the path ahead. This will be a project that I return to time and time again — I hope you return to it as well.