Name the learner problem
Start with the work that feels slow, repetitive, unclear, or difficult to scale.
Each MHGrad course turns one useful AI problem into a guided build. Pick the path closest to your work, review the project brief, and talk to us if you need a customised format.
Every course has a dedicated landing page with the learner problem, outcome, target job, curriculum, live project, trainer detail, schedule, fee route, FAQs, and refund terms.
LLM applications, RAG, tool calling, agents, MCP, production engineering, and capstone.
View programme → 02 · 5 days · RAG / GenAI EngineerRetrieval pipelines, advanced retrieval, evaluation, multimodal and agentic RAG, and deployment.
View programme → 03 · 7 days · AI Agent DeveloperTools, APIs, MCP, RAG, memory, multi-agent workflows, reasoning, deployment, and capstone.
View programme → 04 · 5 days · AI Automation / Workflow EngineerPython automation, LLM workflows, enterprise knowledge, agentic automation, and production engineering.
View programme → 05 · 7 days · Data Scientist / AnalystPython, EDA, statistics, feature engineering, ML, explainability, GenAI, MLOps, and capstone.
View programme → 06 · 7 days · BI SpecialistPower Query, data modeling, DAX, dashboard UX, Power BI Service, security, AI, and capstone.
View programme → 07 · 5 days · NLP / AI DeveloperText analytics, representations, transformers, embeddings, LLMs, RAG, advanced text intelligence, and production NLP.
View programme → 08 · 7 days · Associate AI PMAI discovery, data-to-ML products, GenAI, RAG, agents, evals, experimentation, responsible AI, and launch.
View programme → 09 · 5 days · AI-enabled Marketing AnalystCustomer analytics, segmentation, personalization, predictive AI, GenAI, forecasting, optimization, and capstone.
View programme → 10 · 7 days · FinTech / Data / AI AnalystFinancial analytics, credit, lending, fraud, AML, markets, GenAI, agents, and responsible AI.
View programme → 11 · 7 days · EntrepreneurPython scraping, business data extraction, dynamic websites, production scraping, analytics, AI, and automation.
View programme →The details vary by course, but the learning promise stays consistent.
Start with the work that feels slow, repetitive, unclear, or difficult to scale.
Map inputs, outputs, context, quality checks, and the human decisions that stay in the loop.
Apply the methods to a guided brief and leave with a project demonstration or documented prototype.
Discuss responsible use, privacy, quality, escalation, and what to improve next.
Use the course pages to compare outcomes, audience, curriculum, project, schedule, fees, and FAQs before you enrol.
Ask a course question →Adapt a path to your team’s roles, systems, data boundaries, and business workflow through a consultation.
Explore corporate training →Contact MHGrad for a course enrolment conversation or a team-training brief.