NILG.AI learning culture

What type of culture do we promote?

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Different companies have different principles and values which define themselves. One core value NILG.AI invests in is team knowledge, both at individual and team levels. We deeply believe that personal growth is a driver for keeping the company thriving.

In this blog post, we go through some of the processes we defined to promote Learning and Knowledge sharing within the team and with the public.

Feel free to integrate it into your company and give us feedback about our methodology and how we can improve it.

Learning Sessions

Our primary way to promote learning and knowledge sharing among team members is through our weekly learning sessions, which already have a fixed schedule, generally on Fridays. Each learning session focuses on a given topic or problem and typically has one person responsible for preparing that session.

In each learning session, the promoter presents the topic while the team, as a whole discusses how to apply it to our current and past projects. So, we have a direct feedback loop from peers to improve ongoing projects. Each client benefits from the overall learning and ideas of all team members.

In order to promote these sessions in a relevant and structured way, there are some key points we take into consideration:

 

Early planning

At the beginning of each quarter, we plan all sessions for the quarter, where we define the session day, the person responsible for each learning session of the quarter, as well as, the type of session that should be promoted.

In order to promote the learning of the entire team, we prepare the sessions in a rotative way among the group.

 

Diversity in the type of sessions

As we see it, team learning can be improved in different ways, whether it is by increasing knowledge on areas the team is not comfortable with, discussing how we would approach a given problem, or simply being specialized in the core areas we work on every day. 

Therefore, we saw a need to create different types of learning sessions to improve different aspects we think are important. With this goal in mind, we defined four types of learning sessions:

  • Use Case: session where we discuss how we would approach a given business problem using AI. These sessions provide the team further comfort and understanding of business aspects of AI challenges.
  • Relevant topic session: session where a topic or tool relevant for the team (based on the current projects) is presented. These sessions make the team more proficient in their daily activities.
  • New topic session: session where a tool or technology within an area not spoken yet during the quarter is presented. These sessions make the team members aware of the latest progress in AI.
  • Lower score topic session: session where a topic in which the team has less knowledge is presented. These sessions take the team out of their comfort zone, promoting learning on topics we haven’t worked on yet, and building a better toolset to handle our client’s requests.

We try to balance the number of sessions of the different types so that all four learning components can be improved.

 

Diversity of topics discussed

Besides types of session diversification, we also aim to diversify the topics of the sessions so that the learning is not focused on only a small set of topics.

 

Reporting the main insights from the learning sessions

Besides the session itself, we think it is essential to systematize the learning made. As such, after the session, we report the main insights, discussions, or conclusions taken from that session so we can revise them in the future.

Therefore, at the end of each session, the session promoter fills a reporting template with the details, context, and main conclusions so it can be accessed in the future.

All these aspects are applied to take the most out of our learning sessions, also thinking about the future.

 

Do you want to further discuss this idea?

Book a meeting with Francisca Morgado

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Individual Learning

Besides the learning sessions, each team member has four weekly hours available for personal learning, which they are advised to use. This gives each member the opportunity to explore a given tool or topic he thinks is relevant to learn and possibly share with the other team members in a future learning session.

 

Learning tracking

To have a broad idea of our knowledge of the different topics, we have a learning tracking system in which each team member has a knowledge score associated with the different topics and concepts relevant in the Data Science & AI domains.

This gives us an idea of which areas have a greater margin of progress both at an individual level and as a team.

 

Blog posts

NILG.AI also promotes the internal writing and sharing of blog posts about topics related to AI where we present and describe our point of view of a given problem and how we would approach it in a real-case scenario. Some cases already covered are: Privacy Preserving Machine Learning, Local vs. global optimization, Achieving diverse product recommendations and many more!

 

Take a look at the blogs we have already published. We want to have your feedback and opinion on those topics.

 

Online courses

A relatively recent investment NILG.AI has made in the knowledge sharing domain is the creation of online courses available on our website. The Machine Learning Spectrum, The ABCs of Machine Learning and Data Ignite are some of the courses available.

The final versions of the courses were a result of combining internal knowledge of our team in the different topics. Currently there are 5 courses available, but more content will be coming out soon…

Course, Templates

Data Ignite

Learn how to apply AI in your projects!

Learn More

 

Conclusion

NILG.AI believes that knowledge is the currency of the 21st century. As such, we continue to invest in knowledge sharing as one of our core values. 

Internally, we promote activities like learning sessions, trying to keep them diversified, interesting and relevant to the team, individual learning time, so we can dive a bit deep in areas or topics of interest and learning tracking to have some type of feedback on how the learning is affecting the team’s knowledge.

Externally, we will continue to invest in sharing knowledge through blog posts, our newsletter, and also our online courses.

Due to the value we see in learning, we are planning new initiatives where external people can have a more active participation on the team’s internal learning, so stay tuned for more updates through our social media channels!

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