C1
8 h
4 modules
Foundation
Generative AI at work
Foundation workshop
A practical start for people who use AI occasionally or not at all. ChatGPT, Claude and Copilot applied to your own tasks — plus clear rules on what may and may not be uploaded to an AI tool.
Who it is for
Managers, specialists and analysts in any function. No prior knowledge needed, groups of up to 30.
Outcome
A personal library of 10+ prompts and a checklist for safe AI use.
Course programme
- How LLMs work and where they failContext windows, hallucinations; ChatGPT, Claude, Gemini, Copilot, AlemLLM. Confidential data, Kazakhstan's AI law, labelling AI content.
- Prompting for real workRequest structure: role, context, task, format, examples. Practice: emails, memos, minutes, replies to enquiries.
- Working with documentsSummaries, comparing contract versions, extracting requirements and deadlines. Translation into Russian, Kazakh and English; a knowledge base for your unit.
- Presentations, spreadsheets, productivityAI-built slides, Excel formulas and pivot tables. Wrap-up: everyone moves three of their own tasks onto AI.
Delivery formats
8 days × 1 hour
4 days × 2 hours
2 days × 4 hours on site
C2
8 h
4 modules
Foundation
AI for executives
Decisions, teams, transformation
For directors who need to manage AI rather than write prompts: where AI pays off, how to brief teams, how to quantify the business case and control risk. Half the time is personal hands-on practice.
Who it is for
Department directors, heads of units and branches, board members. Groups of 10–20.
Outcome
An AI opportunity map for your unit: 3–5 priority use cases with impact and risk assessment.
Course programme
- AI as an executive toolAgents, deep research, Copilot. A meeting briefing in 10 minutes, dissecting a report, verifying AI answers.
- Decision-making with AIPre-mortems, scenarios, devil's advocate, cognitive bias. Human in the loop; risk tiers under Kazakhstan's AI law.
- Where AI pays offProcess mapping, the value–complexity matrix. The economics of impact; why pilots fail to scale.
- Team and changeAI champions, KPIs, AI usage policy, the ADKAR model. Presenting your unit's AI use-case map.
Delivery formats
8 days × 1 hour
4 days × 2 hours
2 days × 4 hours on site
C3
12 h
6 modules
Intermediate
AI for strategy and research
From question to board materials
Strategic and market research several times faster with deep research tools — without losing quality. The full cycle from question to board-ready materials, with a strong focus on fact-checking.
Who it is for
Strategy and development directors, strategy and investment departments, transformation offices.
Outcome
A finished mini-study on a real topic and a template for an AI-supported strategy process.
Course programme
- Research toolsDeep research in ChatGPT, Claude, Gemini, Perplexity; NotebookLM; building a research plan.
- Gathering and verifying informationNational statistics, annual reports, foreign sources; a fact-checking protocol.
- Market and competitor analysisTAM/SAM/SOM, PESTEL, Porter's five forces, benchmarking, signal monitoring.
- Strategy toolsSWOT, scenarios, goal trees, KPIs and OKRs; red teaming a strategy.
- The strategy documentThe Minto pyramid, executive summaries, board materials.
- Capstone projectA team mini-study on your own company, with a presentation.
Delivery formats
12 days × 1 hour
6 days × 2 hours
3 days × 4 hours on site
C4
12 h
6 modules
Intermediate
LLMs for analysts
Data, SQL, reporting
For analysts working with extracts from SAP, 1C and data warehouses: AI cleans data, writes SQL and Python, finds anomalies and drafts conclusions — and the analyst learns how to verify all of it. No Python required.
Who it is for
Business and data analysts, controllers, procurement, operational reporting. Solid Excel skills needed.
Outcome
A set of working scenarios on your own data: cleaning, SQL queries, an analytical memo for management.
Course programme
- The analyst's toolkitData analysis in ChatGPT and Claude, Copilot in Excel, anonymising data.
- Data preparation and qualityDuplicates, gaps, formats; matching counterparty and material master data.
- SQL and databases with AIA plain-language question becomes SQL; reviewing queries and the mistakes AI typically makes.
- Analysis and patternsSegmentation, cohorts, anomalies, trend and seasonality forecasting.
- From analysis to conclusionAnalytical memos and charts; reviewing enquiries and tender documentation.
- Capstone projectFrom a raw extract to a memo for management; a verification checklist.
Delivery formats
12 days × 1 hour
6 days × 2 hours
3 days × 4 hours on site
C5
12 h
6 modules
Intermediate
LLMs for finance
Budgeting, reporting, financial models
For finance functions: budgeting, plan-versus-actual, consolidation, IFRS and investment project models. One rule throughout — AI computes with code or formulas, and every figure is verified.
Who it is for
Finance teams, economists, controlling, treasury, accounting, internal audit, CFOs.
Outcome
Templates for plan-versus-actual analysis, reporting commentary and AI-assisted model review.
Course programme
- AI in the finance functionWhere AI already works in finance; accuracy and confidentiality.
- Budgeting and plan-versus-actualBudget forms, reviewing requests, variance analysis and commentary.
- ReportingConsolidation and reconciliation, IFRS, explanatory notes, auditor requests.
- Financial modellingAuditing an Excel model, NPV and IRR, scenarios, stress tests.
- Contracts and counterpartiesExtracting terms and covenants; counterparty analysis from public reporting.
- Capstone projectA monthly management reporting pack with commentary.
Delivery formats
12 days × 1 hour
6 days × 2 hours
3 days × 4 hours on site
C6
16 h
8 modules
Intermediate
Power BI and AI
From raw data to an executive dashboard
Participants build a data model, DAX measures and an executive dashboard from scratch. ChatGPT, Claude and Copilot handle Power Query and DAX, while the human owns the model logic and checks the numbers.
Who it is for
Analysts and finance professionals who prepare reporting for management. No Power BI experience required, up to 16 people.
Outcome
A working Power BI report: a data model, 15+ DAX measures and an executive summary page.
Course programme
- Power BI and the role of AIDesktop, Service, Fabric, Copilot; sources: Excel, SQL, SAP, 1C.
- Power Query with AICleaning and merging data, writing M code with an LLM.
- The data modelStar schema, facts and dimensions, a date table, relationships.
- DAX with AI: fundamentalsFilter context, CALCULATE, period comparisons.
- DAX: management measuresPlan versus actual, variances, drivers; reconciling figures.
- VisualisationAn executive dashboard, Smart Narrative, Copilot.
- PublishingRefresh, gateways, RLS, subscriptions and alerts.
- Capstone projectA finance or investment-portfolio dashboard built from scratch.
Delivery formats
16 days × 1 hour
8 days × 2 hours
4 days × 4 hours on site
C7
12 h
6 modules
Intermediate
AI in project management
From charter to closure
AI at every project stage, from initiation to closure. Built on PMI standards and the instructor's own projects: SAP S/4 for the national railway, Wabtec KinetiX, KazTransOil.
Who it is for
Project and programme managers, PMOs, investment project sponsors.
Outcome
AI templates for the charter, WBS, schedule, risk register, status report and EVM, tested on your own project.
Course programme
- AI's role and initiationPMBOK 7 performance domains; business case, charter, stakeholders, requirements from an RFP.
- PlanningWBS, estimates, schedule and critical path, budget, RACI, communications plan.
- Risk and procurementRisk register, pre-mortem, Monte Carlo; technical specifications and bid comparison.
- Control and reportingStatus reports from notes, EVM, schedule and cost forecasts, change control.
- Portfolio and PMOConsolidated reporting, early warning, prioritisation, AI agents in the PMO.
- Closure and workshopLessons learned, handover to operations; running your own project through AI tools.
Delivery formats
12 days × 1 hour
6 days × 2 hours
3 days × 4 hours on site
C8
12 h
6 modules
Intermediate
AI in Agile and Scrum
Product, backlog, teamwork
How AI changes agile teams: product owners research and write backlogs faster, Scrum masters spot problems in the metrics, teams drop the busywork. Plus a hybrid approach for projects bound by public procurement.
Who it is for
Scrum masters, product owners, agile coaches and teams, IT leaders. Best taken as a whole team, up to 20 people.
Outcome
AI practices for every Scrum event, templates for stories and acceptance criteria, a team metrics dashboard.
Course programme
- Agile in the age of AIHow roles are shifting; Scrum, Kanban and waterfall hybrids in state-owned companies.
- The product owner with AIUser research, customer journey maps, roadmaps; WSJF, RICE, MoSCoW.
- The backlog with AIINVEST stories, Given–When–Then, DoR and DoD, estimation, finding gaps.
- Scrum events with AIPlanning, stand-ups with Jira summaries, sprint review, retrospective.
- Metrics and automationVelocity, cycle time, WIP, Monte Carlo forecasting, agents for Jira and Confluence.
- Scaling and workshopScrum of Scrums, SAFe, PI planning; a mini-sprint run with AI.
Delivery formats
12 days × 1 hour
6 days × 2 hours
3 days × 4 hours on site
C9
16 h
8 modules
Advanced
Automating routine work with Claude Code
Agents, skills, schedules
Claude Code does not just answer — it acts: works with files, runs scripts, connects to mail and databases, and runs on a schedule. Non-developers build personal agents for reporting and monitoring.
Who it is for
Analysts, managers and digital offices with repetitive work. Course C1 or chatbot experience needed; no coding required.
Outcome
2–3 working automations, at least one of them running on a schedule.
Course programme
- From chatbot to agentThe plan–act–verify loop, installation, permissions.
- Files and documentsBatch processing, generating documents from templates.
- Memory and skillsCLAUDE.md, skills and commands for your processes.
- Data and reportsExcel, CSV, SQL; a turnkey weekly report.
- External systems (MCP)Mail, calendar, SharePoint, Jira; triaging an inbox.
- Subagents and monitoringParallel work, hooks, tender and news monitoring.
- Scheduled workUnattended tasks, notifications, handling failures.
- Security and capstonePermissions, data leaks, prompt injection; presenting your work.
Delivery formats
16 days × 1 hour
8 days × 2 hours
4 days × 4 hours on site
C10
12 h
6 modules
Advanced
Vibe coding: internal tools and prototypes
Without a development team
Managers and analysts build web tools themselves by describing them in plain language: calculators, request forms, task trackers, service prototypes. And they learn when a prototype should be handed over to IT.
Who it is for
Product managers, analysts, process owners. No coding required, groups of up to 15.
Outcome
A working prototype of an internal tool and the technical specification for IT based on it.
Course programme
- What vibe coding isLovable, Bolt, v0, Replit, Claude Code; how a web application is put together.
- From idea to prototypeUsers, scenarios, screens; your first calculator or form.
- Data and databasesTables, relationships, importing from Excel; a task tracker with a database.
- Dashboards and built-in AICharts, connecting to APIs, classifying enquiries with an LLM.
- Quality and releaseTesting, roles, personal data, security requirements, the spec for IT.
- Capstone projectPolishing your prototype and a demo day.
Delivery formats
12 days × 1 hour
6 days × 2 hours
3 days × 4 hours on site
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