As Lead at 6xD Academy Nairobi, part of DigitalQatalyst, my work covers curriculum, course bundles, marketing, partnerships, learner support and the learning platform. I also track the programme funnel from leads through to attendance. If you're comparing ai courses right now, you want to know whether a course will actually change how your team works once the trainer has left the room.
How to pick AI courses that fit your team
Look at what the sessions use as material. A course built from your team's own documents, emails and reports feels different from one built on generic slides. People see their own tasks in it straight away.
The training I offer for teams follows this shape: hands-on workshops using the team's own documents and reports. People also get prompt and workflow templates to keep, and follow-up sessions for whatever comes up once they are back at their desks. It helps to ask how the trainer adjusts the material once they see your team's own tasks. A course that teaches only the tool, without looking at your documents, leaves the harder judgment calls for your team to work out alone afterward.
Ask also what the course teaches about safe use: what to check before trusting an answer, what should never go into a prompt, and when a person still has to make the call. You can read more on the AI training for teams page.
Where this fits inside a bigger programme
That role also means coordinating stakeholders, institutions and partners. If your team includes several departments or outside partners, ask how the trainer plans to keep everyone aligned on timing and content. That kind of coordination matters whether you are running one course or planning a cohort, an academy or an internal upskilling programme.
Ask a prospective trainer what they measure beyond who turned up on the day, and who is responsible for learner support once the sessions are over. Ask too who they coordinate with beyond the person standing in the room: institutions, partners, or only a single account manager. If a trainer cannot answer those questions clearly, treat that as useful information in itself. You can see this role in more detail on my CV.
Why daily use matters more than a single workshop
Claude and DeepSeek draft and review articles in the eight AI content pipelines I run, which publish to separate client sites. Ask any course how it handles review: who checks the output, and what happens when a model sounds confident and is wrong. I wrote about this in AI Content Quality Control: Check the Reviewer Too and AI for business starts with who checks the AI's work. You can see the pipelines themselves in the case study on AI content pipelines.
From February 2024 to March 2025, I was Operations and Mentorship Programme Manager at Teach2Give. I ran a mentorship programme for 150 mentees, built Power BI dashboards to track progress and job placement, and wrote SOPs for mentor pairing and newsletters. If you want training that lasts, look for the same kind of structure: a written process your team can keep and follow after the sessions end.
If you are just starting out
If you are searching for ai courses for beginners, start with the tools your team already uses for email and documents, rather than something nobody has opened before. Look for a course that lets people practice on real tasks in the first session, with someone in the room to answer the specific questions your work raises. A short introduction is enough to start; depth can come later through follow-up sessions. I'm building AkiliCamp, an online school for practical AI and technology skills, opening soon with an early list.
If you want the prompt and workflow templates and the safe-use checklists I use in training, they go out in Signal, my weekly newsletter. If you'd rather talk through what your team needs, get in touch.