We diagnose first
No course starts before we know the gaps, the roles, and what success looks like.
Training built on what your team really needs.
First we find the skill gaps and the processes where AI pays off. Then we build the training around your work and tools.
Our approach
From your team's gaps to results you can measure.
Four steps, and at each one you know exactly what you get out of it.
DiagnoseWe talk to your managers, check skills by role, and identify high-impact AI opportunities aligned with your business goals.
DesignWe build the training on your cases, data, and tools. You see the plan and project proposal before you commit.
DeliverHands-on sessions run by practitioners, in person, remote, or blended. People work on their real tasks, not on examples.
ProveFinal projects solve real internal problems. We measure before and after, so you have results to show management.
Custom programs
Need something beyond our ready-made programs?
Explore the technologies we specialize in, then tell us what your team should learn. We can customize any course around your needs.
Why Nexademy
Most corporate training fails. Here's why ours doesn't.
Corporate training only pays off when it fits the people in the room. Generic e-learning gets clicked through and forgotten. We start from what your team does every day and what should change, so the training shows up in the work and not only in a certificate.
Tell us your team's problem
Your cases, your tools
Exercises use your processes, your data, and the software you already pay for.
Results you can show
Every participant finishes with a real use case they can apply in everyday work.
Led by practitioners
Instructors do this work every day, so the advice is real, not theory.
Capabilities
What your team will be able to do.
We pick the technology after we know what your people need to build, run, or lead.
Data & AI
Python, SQL, machine learning, generative AI, RAG, and responsible deployment.
Software engineering
JavaScript, TypeScript, React, Python, Django, APIs, and databases.
Infrastructure
Cloud foundations, Docker, CI/CD, monitoring, MLOps, and LLMOps.
Product & adoption
AI literacy, agile delivery, product strategy, and role-specific enablement.
A typical engagement
From problem to measured result.
Challenge
Teams across departments used AI randomly, with no shared rules and no clear view of where it really helped.
Approach
We interviewed managers, mapped the key processes, and built role-based workshops on their own cases, plus a team project.
Outcome
Several use cases went live, hours were saved every month, and the whole company now works with clear AI rules.
Programs
Start with one of our ready-made programs.
Each program is a starting point. We use it as a base and rebuild the content, cases, and pace for your team.
AI & DataBusiness
Forward Deployed Engineering
For professional engineers already fluent with AI tools: codify client work into reusable patterns and own AI systems in production.
10 weeks PT
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AI for Finance
Give finance teams practical AI fluency for analysis, reporting, automation, and governance.
27 hours · 9 modules
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Practical AI Training
Build company-wide AI confidence through hands-on workflows and responsible use.
9 hours · 3 sessions
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Data Science
Turn raw data into deployed machine-learning solutions through an applied team capstone.
12 weeks FT · 22 weeks PT
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AI Engineering
Ship, evaluate and operate production LLM systems: retrieval, agents, evaluation and cloud deployment.
9 weeks FT
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Mastering Generative AI
Build, evaluate, and deploy practical generative AI applications for real business use cases.
6 weeks · 3h/week
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Web Development
Build full-stack capability across modern web foundations, React, Python, and databases.
9 weeks FT
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Python Programming
Move from programming fundamentals to data analysis, APIs, and a working web application.
6 weeks · 3h/week
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