AI Skills in English — what you actually study
Three modules, 45 sessions, 45 hours in total. Every session pairs an AI topic with the English you need to work in it, and the language load rises as the content matures. Hours are bought in advance in batches of 3.
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Foundations
What agents are, how to build one, and the English you need to describe, prompt and test them.
Full module online 8 100 CZK · onsite 13 500 CZK (or start with 3 hours from 2 700 CZK)
- 1
What is an AI agent?
What agents are, how they differ from chatbots, and where they add value.
English focus: Core AI vocabulary; defining and comparing things in simple present.
Building Your First AI Agent
- 2
Choosing a persona and purpose
Define what your agent does, who it serves and what tone it uses.
English focus: Describing purpose and audience; register and tone words.
Building Your First AI Agent
- 3
Writing an effective system prompt
The system prompt is the brain of the agent — write one that produces consistent answers.
English focus: Imperatives and instruction language; ordering steps clearly.
Building Your First AI Agent
- 4
Adding knowledge to your agent
Give the agent the information it needs, from URLs to uploaded documents.
English focus: Talking about sources, files and formats; quantifiers.
Building Your First AI Agent
- 5
Testing and refining your agent
Build it, test it, improve it — the iterative loop that makes an agent good.
English focus: Giving feedback; comparatives and 'better / worse than' language.
Building Your First AI Agent
- 6
Deploying your agent
From the builder to the real world: deployment options and what comes next.
English focus: Future forms and plans; announcing a change to colleagues.
Building Your First AI Agent
- 7
The anatomy of a human-AI team
Roles, communication, and the balance between automation and human judgement.
English focus: Team and role vocabulary; describing responsibilities.
Orchestrating Human-AI Teams
- 8
Assigning roles and responsibilities
Who does what, who decides what, and when a task is escalated.
English focus: Modals of obligation and permission: must, should, may, can.
Orchestrating Human-AI Teams
- 9
Designing workflows that work
Turn team roles into a step-by-step workflow that moves work from start to finish.
English focus: Sequencing language; explaining a process end to end.
Orchestrating Human-AI Teams
Working with AI teams and data
Running AI work day to day — oversight, value cases and data fundamentals — in meeting and documentation English.
Full module online 13 500 CZK · onsite 22 500 CZK (or start with 3 hours from 2 700 CZK)
- 1
Human-in-the-loop: when to escalate
Knowing when AI handles it and when a human must step in.
English focus: Conditionals; hedging and cautious language.
Orchestrating Human-AI Teams
- 2
Monitoring and oversight
Keeping a running team healthy: quality checks, catching issues, improving over time.
English focus: Reporting language; describing trends and exceptions.
Orchestrating Human-AI Teams
- 3
Scaling your team operations
From pilot to production: multiple agents, volume and consistent quality.
English focus: Quantity and scale language; cause and effect.
Orchestrating Human-AI Teams
- 4
The dual role of the intelligent tech enterprise
Why technology companies are both providers and users of AI.
English focus: Contrast structures; presenting two sides of an argument.
Capabilities for AI-driven Transformation
- 5
Navigating market and technological battles
The interconnected trends and the battlegrounds shaping AI.
English focus: Trend vocabulary; describing competition and change.
Capabilities for AI-driven Transformation
- 6
Unlocking the ROI pool
Where the value of AI sits and which functions return the most.
English focus: Numbers, percentages and financial vocabulary.
Capabilities for AI-driven Transformation
- 7
Enable, Embed, Evolve
The three phases of AI adoption, from foundations to ecosystem change.
English focus: Stages and milestones; talking about progress over time.
Capabilities for AI-driven Transformation
- 8
A blueprint for future-ready architecture
The elements of an intelligent company and designing for adaptability.
English focus: Technical description; passive voice for systems.
Capabilities for AI-driven Transformation
- 9
Leading with strategy and trustworthy AI
Why strategy and trust, not technology, are the real bottlenecks.
English focus: Persuasive language; making and supporting a claim.
Capabilities for AI-driven Transformation
- 10
Foundations of AI and data modeling
How AI developed and the difference between symbolic and statistical models.
English focus: Defining and classifying; academic reading strategies.
AI & Data Analytics Fundamentals
- 11
The machine learning pipeline and MLOps
Building a model step by step and operationalising the process.
English focus: Process language; reading documentation and release notes.
AI & Data Analytics Fundamentals
- 12
Privacy, security and transparency
Encryption, privacy regulation and the 'black box' problem.
English focus: Risk and obligation vocabulary; formal written register.
AI & Data Analytics Fundamentals
- 13
Data as a strategic asset
Stewardship, ethics and quality frameworks for organisational data.
English focus: Abstract nouns; writing a short policy summary.
AI & Data Analytics Fundamentals
- 14
Human-machine interaction and design
Multidisciplinary teams and the double-diamond model in user-centred AI.
English focus: Design and user-research vocabulary; describing needs.
AI & Data Analytics Fundamentals
- 15
Change management and governance
The strategic steps and structures needed for a cultural shift.
English focus: Meeting language; agreeing, disagreeing and proposing.
AI & Data Analytics Fundamentals
Strategy, governance and leadership
The senior conversation: governance, workforce design, business strategy, leadership and regulated-industry risk.
Full module online 18 900 CZK · onsite 31 500 CZK (or start with 3 hours from 2 700 CZK)
- 1
The evolution of AI in modern banking
From static risk models to dynamic AI-driven ecosystems.
English focus: Narrating change; present perfect and past simple contrast.
Practical Governance & Oversight
- 2
Automating compliance and regulatory oversight
How RPA and NLP streamline compliance under GDPR and Basel III.
English focus: Regulatory register; reading dense legal-style text.
Practical Governance & Oversight
- 3
Precision in risk modeling and fraud detection
ML for credit scoring accuracy and anomaly-based fraud detection.
English focus: Precision language; describing accuracy and error.
Practical Governance & Oversight
- 4
Ethical risk and the 'black box' problem
Algorithmic bias, data privacy and opaque automated decisions.
English focus: Ethical argument; expressing concern and qualification.
Practical Governance & Oversight
- 5
Practical governance and future frameworks
Explainable AI in practice and formal governance structures.
English focus: Writing recommendations; executive summary style.
Practical Governance & Oversight
- 6
The dual role of the intelligent enterprise
Balancing internal AI adoption with external innovation. Paired with the market and technological battles that decide who leads.
English focus: Strategic vocabulary; structured comparison.
AI-enabled Workforce Design
- 7
The three phases of value creation
Enable, Embed and Evolve as a structured journey to industry-defining innovation.
English focus: Roadmap language; talking about sequence and dependency.
AI-enabled Workforce Design
- 8
Designing the collaborative human-agent workforce
Shared goals, metrics and workflows between people and agents. Paired with strategy, trust and product intelligence.
English focus: Job and skills vocabulary; describing future roles.
AI-enabled Workforce Design
- 9
Bridging AI and business strategy
How AI changes perception, generation and decision-making. Paired with the mechanics of machine learning for leaders.
English focus: Explaining technical ideas to a non-technical audience.
AI Business Strategies and Applications
- 10
Neural networks and deep learning
How neural networks solve complex problems. Paired with how machines see and talk: computer vision and NLP.
English focus: Analogy and metaphor; simplifying without distorting.
AI Business Strategies and Applications
- 11
Robotics and the automation ecosystem
From fixed robotic automation to robots that adapt and learn. Paired with building a robust AI strategy.
English focus: Describing capability and limitation.
AI Business Strategies and Applications
- 12
Building your team and transformation
Organisational design and embedding AI expertise across a company.
English focus: HR and change vocabulary; diplomatic disagreement.
AI Business Strategies and Applications
- 13
The future of AI: generative models and ethics
Multimodal models and agents, and the risks of hallucination and IP.
English focus: Speculation and probability; hedged predictions.
AI Business Strategies and Applications
- 14
Redefining leadership in the AI frontier
From hierarchical management to flexible, collaborative models. Paired with the perception gap between leaders and staff.
English focus: Leadership register; presenting a position.
Leadership's Role in an AI-ready Culture
- 15
Human-AI teaming and team dynamics
How AI augments human teams, and where collaboration breaks down.
English focus: Facilitation language; running a discussion in English.
Leadership's Role in an AI-ready Culture
- 16
Ethical leadership and governance
Leaders as guardians of data security and fairness. Paired with building an AI-ready culture.
English focus: Values language; writing an internal statement.
Leadership's Role in an AI-ready Culture
- 17
The future of AI-driven professional roles
How AI redefines existing jobs and creates new professions.
English focus: Career vocabulary; talking about your own development.
Leadership's Role in an AI-ready Culture
- 18
AI in banking operations
From manual processes to data-driven systems in a regulated sector.
English focus: Sector-specific terminology; formal summarising.
Risk, Ethics and Regulation for AI in Banking
- 19
Advanced risk assessment and machine learning
Where ML models outperform traditional credit and underwriting models.
English focus: Evaluative language; weighing evidence.
Risk, Ethics and Regulation for AI in Banking
- 20
Compliance, fraud detection and bias
KYC and AML automation, paired with the ethical risks of bias and opacity.
English focus: Compliance register; challenging a claim politely.
Risk, Ethics and Regulation for AI in Banking
- 21
Frameworks for responsible AI governance
Building governance that keeps AI transparent, fair and compliant.
English focus: Final presentation: your own position, defended in English.
Risk, Ethics and Regulation for AI in Banking
Completing all three modules qualifies you for the EU-sponsored Certificate of AI Achievement, delivered in cooperation with EIT Deep Tech Talent Initiative and Forge of Agents.