Bring a real workflow
Use a process you already understand: a QA loop, knowledge task, proposal, service request, or operations handoff.
Applied AI learning
Build AI capability around the work you already do.
MHGrad turns AI curiosity into useful working systems: intensive courses, live projects, and team training for software, data, product, finance, marketing, and business intelligence roles.
01Problem first
02Build live
03Review responsibly
The gap
Most AI training ends at the prompt. Your work does not.
Teams need more than tool tours. They need a focused problem, a build path, review checkpoints, and a way to take the result back to work.
Leave with a demonstrable project
Document what the system does, where it needs human review, and how someone else can use it.
Use responsible AI checkpoints
Separate useful automation from unsafe assumptions with clear data, quality, and escalation checks.
Build a repeatable habit
Turn one guided project into a practical method for discovering and improving the next workflow.
Course paths
Choose the skill path that matches your next useful build.
Eleven focused programmes for GenAI, data, BI, product, commercial, finance, and business intelligence roles.
5 days · Junior GenAI Developer
Generative AI Application Developer
LLM applications, RAG, tools, agents, MCP, and production engineering.
View programme → 5 days · RAG / GenAI EngineerRAG Engineer Sprint
Retrieval engineering, evaluation, multimodal RAG, and deployment.
View programme → 7 days · AI Agent DeveloperAgentic AI Developer
Tools, MCP, memory, multi-agent workflows, reasoning, and capstone.
View programme → 5 days · Workflow EngineerAI Automation Engineer
Python, LLM automation, enterprise knowledge, agents, and production workflows.
View programme → 7 days · Data Scientist / AnalystApplied Data Scientist
Python, EDA, ML, explainability, GenAI, MLOps, and capstone.
View programme → 7 days · BI SpecialistPower BI for BI
Data preparation, modeling, DAX, dashboard UX, security, AI, and capstone.
View programme → 5 days · NLP / AI DeveloperNLP & Text Intelligence
Text analytics, transformers, embeddings, LLMs, RAG, and production NLP.
View programme → 7 days · Associate AI PMAI Product Management
AI discovery, product patterns, evals, experimentation, responsible AI, and launch.
View programme → 5 days · Marketing AnalystAI for Marketing & Sales
Customer analytics, personalization, predictive AI, GenAI, forecasting, and optimization.
View programme → 7 days · FinTech / AI AnalystAI for Finance & FinTech
Financial analytics, credit, fraud, markets, GenAI, agents, and responsible AI.
View programme → 7 days · EntrepreneurWeb Scraping for Business Acceleration
Python scraping, business data extraction, analytics, AI, and automation.
View programme →
For organisations
Train around your team’s language, systems, and constraints.
Bring a workflow, choose a practical format, and leave with shared examples your team can discuss after the session.
Workshops that become working habits
- Role-specific examples for software, BFSI, HR, sales, or service teams
- Hands-on exercises with a live workflow or project brief
- Facilitated review of quality, privacy, and human handoffs
Explore the workflows MHGrad already covers
Projects and proof
Show the work. Do not just describe the tool.
Project demonstrations make the learning concrete. Testimonials are published only when the learner has given permission and the attribution is clear.
Guided build
AI coding and QA workflow
From issue brief to reviewed change, with documentation and test-quality checkpoints.
See project demonstrations → Guided buildKnowledge and support assistant
Turn trusted internal content into a structured support workflow with escalation paths.
See project demonstrations → Permission-basedVerified learner stories
No invented quotes. Read the feedback MHGrad is able to attribute, or request current references.
View the proof policy →Tell us what your learners or team need to build.
Choose a course, ask for a team conversation, or request a consultation when the right format is not obvious yet.