CareerCraft Labs
Training that changes what your team can build on Monday
Awareness sessions produce enthusiasm that fades in a fortnight. Our programmes are built around your own tools and data, so people leave with work they have actually done.
Why most AI training does not stick
The standard corporate AI workshop follows a familiar arc: an engaging speaker, a demonstration that impresses the room, a slide deck circulated afterwards, and no measurable change in how anyone works. The problem is not the content. It is that generic examples never survive contact with the specifics of somebody’s actual job.
CareerCraft Labs, the learning division of AI Wizard, is built around the opposite approach. Programmes are hands-on and use your context — your data shapes, your tools, your reporting problems. Participants spend most of the time building rather than listening, and they leave with something that works and that they can extend.
Because the same team also delivers AI systems in production, the material reflects what actually happens in real projects: where models fail, what data problems cost, and which shortcuts create trouble later. Trainers who ship systems teach a noticeably different course from trainers who only teach.
Programs we run
AI & GenAI
Artificial intelligence, generative AI, machine learning, deep learning and NLP, with hands-on projects rather than theory alone. Our most requested program.
Power BI
Interactive dashboards, DAX, data modeling and business intelligence practice, built on datasets that resemble your own.
Python for data
Data analytics with pandas, numpy and matplotlib, plus automation and practical data science workflows.
Excel & data tools
Advanced Excel, Power Query, macros and VBA for professionals whose real work environment is a spreadsheet.
Workshops & FDP
Faculty development programmes in AI and specialised workshops for academic institutions.
Custom corporate programs
Curricula assembled for a specific team and objective — for example, equipping analysts to use LLMs responsibly on internal data.
How we work
We design against a capability gap, not a catalogue.
Understand the gap
We talk to team leads about what people should be able to do afterwards, and assess current levels so the material lands at the right depth.
Tailor the curriculum
Exercises are rebuilt around your tools, data shapes and real problems. Generic datasets are the fastest way to lose a technical audience.
Deliver hands-on
Sessions are built around building. Participants work on their own machines, hit real errors and debug them with the trainer present.
Reinforce afterwards
Follow-up material, an optional project review and a clinic session a few weeks later, when people have tried to apply it and generated real questions.
Who these programs are for
We run programmes for corporate teams and academic institutions. Cohorts are grouped by role and current level so nobody is bored and nobody is lost.
- Analysts and reporting teams moving from spreadsheets to modelling and BI
- Developers and engineers adding AI and LLM capability to their toolkit
- Operations and business teams who need practical, safe day-to-day AI use
- Managers who must evaluate AI proposals without being technical specialists
- Faculty seeking current, industry-grounded material through FDP programmes
- Organisations rolling out an AI policy that needs to be understood, not just circulated
Frequently asked questions
Do you deliver online, in person, or both?
Both. In-person sessions work better for hands-on labs where a trainer can look over a shoulder, while online suits distributed teams and shorter modules. Many clients use a hybrid: an intensive in-person block followed by online reinforcement sessions.
What is the typical group size and duration?
Hands-on technical programmes work best with roughly fifteen to twenty-five participants, so everyone gets attention during labs. Duration ranges from a focused one-day workshop to a multi-week programme with projects between sessions. We recommend a shape once we understand the gap you are closing.
Do participants need prior programming experience?
It depends on the track. Excel, Power BI and AI-awareness programmes assume no programming background. Python, machine learning and LLM engineering tracks expect some coding familiarity, and we assess levels beforehand so cohorts are grouped sensibly rather than mixed.
Is there a certificate?
Yes, participants receive a certificate of completion from CareerCraft Labs. We would rather be judged on what people can do afterwards than on the certificate itself, which is why programmes are built around projects.
Can the training use our internal data?
Yes, and it makes the material considerably more effective. We can work with anonymised or sample extracts of your real data under a confidentiality agreement, so exercises reflect the systems people return to on Monday.
Related services
Planning an upskilling program?
Tell us the team, the current level and what they should be able to do afterwards. We will send back a proposed outline and format.