AI & Technology Course Catalog
Explore our comprehensive program catalog: Find the ideal course using advanced filters and level settings.
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Hands-on fundamentals for building an end-to-end RAG system over enterprise documents: ingestion, chunking, embeddings, vector retrieval, grounded prompting with citations and baseline evaluation.
- Live Course
- 6 modules
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Defining the real root problem instead of chasing symptoms; covers the Problem Statement Canvas, MECE issue trees, 5 Whys, scope boundaries and aligning stakeholders before jumping to solutions.
- Live Course
- 5 modules
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Build end-to-end workflow automations with n8n by mastering triggers, core nodes, data transformation, conditional branching and basic HTTP integrations in a visual builder.
- Live Course
- 5 modules
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Chart selection, visual perception principles, colour and hierarchy, and data storytelling for analysts and reporting teams who need decision-focused dashboards and presentations that cannot be misread.
- Live Course
- 6 modules
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For leaders tying AI to corporate strategy: AI vision and ambition level, strategic options, stakeholder alignment, transformation narrative and leadership behaviours, producing a one-page AI strategy canvas.
- Live Course
- 5 modules
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Hypothesis-driven analysis, argument mapping (claim-evidence-warrant), deductive and inductive reasoning, spotting logical fallacies and assumption mapping; participants solve business cases systematically.
- Live Course
- 5 modules
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Design production-grade n8n systems using modular sub-workflows, JavaScript/Python Code nodes, resilient error handling, batch processing, queue mode and scaling patterns.
- Live Course
- 5 modules
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Advanced DAX patterns, calculation groups, row-level security, incremental refresh, composite models and performance tuning for experienced Power BI users building enterprise-scale reporting solutions.
- Live Course
- 6 modules
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Deep dive into dense, sparse (SPLADE/BM25), Matryoshka and late-interaction (ColBERT) embeddings, Turkish/multilingual retrieval quality, domain adaptation and semantic search engineering.
- Live Course
- 6 modules
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Hands-on programme measuring AI readiness across strategy, data, technology, talent, governance and culture with a maturity model, producing a scored maturity profile, gap analysis and improvement roadmap.
- Live Course
- 6 modules
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Engineering deep dive into ANN indexing (HNSW, IVF, DiskANN, PQ) and vector databases (pgvector, Milvus, Weaviate, FAISS, Pinecone), covering filtered search, multi-tenancy and capacity planning.
- Live Course
- 6 modules
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Star schema design, fact and dimension tables, relationships and filter direction, date tables and core-to-intermediate DAX measures, so analysts build Power BI models that return correct, maintainable results.
- Live Course
- 6 modules
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Build autonomous AI workflows in n8n using AI Agents, LangChain nodes, vector stores, RAG pipelines, conversational memory and tool calling connected to business apps.
- Live Course
- 5 modules
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Kahneman's System 1/System 2 thinking, confirmation bias, sunk cost fallacy, anchoring, groupthink and decision noise; teams design practical debiasing checklists and decision hygiene routines.
- Live Course
- 5 modules
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Design dynamic, schema-safe and production-ready prompts inside n8n workflows using prompt chaining, automated evaluation datasets, guardrails and versioned prompt management.
- Live Course
- 5 modules
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Importing from multiple sources, cleaning, merging, unpivoting, parameters, custom functions and M language basics in Power Query, so Excel and Power BI users automate manual data preparation.
- Live Course
- 6 modules
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Parsing complex PDFs, tables and scanned enterprise documents with Docling, Unstructured and VLMs, and applying structural, semantic, parent-child and contextual chunking for high-recall RAG.
- Live Course
- 6 modules
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Testing the quality of evidence across reports, market studies, internal metrics and AI outputs; covers correlation vs causation, survivorship bias, base rates and source triangulation.
- Live Course
- 5 modules
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For managers running AI initiatives: the experimental, data-dependent nature of AI projects, CRISP-DM and PoC–pilot–production stages, success criteria, team roles, AI-specific risks and vendor management.
- Live Course
- 5 modules
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Engineering RAG systems for strict grounding, verifiable inline citations, conflict resolution across sources, calibrated abstention when evidence is missing and automated faithfulness verification.
- Live Course
- 6 modules
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Model and automate end-to-end business processes across sales, marketing, finance, HR and operations using n8n workflows spanning CRM, ERP, approvals and reporting.
- Live Course
- 5 modules
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Defining weighted decision criteria (MCDA) before evaluating options, separating knockout must-haves from scored trade-offs and building decision matrices on a real organisational choice.
- Live Course
- 5 modules
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OneLake, Lakehouse, Data Warehouse, Data Factory pipelines, Dataflow Gen2, notebooks and Direct Lake Power BI, giving data and BI teams an end-to-end introduction to Microsoft Fabric components.
- Live Course
- 6 modules
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What managers need to know about MLOps and LLMOps to move models from pilot to reliable service: lifecycle, monitoring and drift, evals, cost, platform options (MLflow, Azure AI Foundry, Bedrock, Vertex AI) and team structure.
- Live Course
- 5 modules
Complete Training Catalogue Directory
Browse all training programs directly across our 7 core tracks and 60 specialized categories.
Non-Technical AI Training 8 categories · 129 courses
AI Literacy & Generative AI (17) →
- AI in Business Processes: Future AI Workflows (12 hours)
- AI Literacy for Organizations (12 hours)
- Generative AI in Business (12 hours)
- Generative AI Fundamentals (12 hours)
- Mastering Everyday AI Productivity Tools (12 hours)
- AI-Powered Research and Knowledge Synthesis (12 hours)
- AI-Assisted Document and Report Writing (12 hours)
- AI-Powered Data Analysis and Business Insights (12 hours)
- AI-Powered Presentations and Visual Content Creation (12 hours)
- AI Horizons (2 hours)
- AI for Meeting Productivity and Action Management (12 hours)
- Verifying and Auditing AI Outputs (12 hours)
- Preventing AI Hallucinations and Source Grounding (12 hours)
- Data Privacy and Safe AI Usage (12 hours)
- Human-in-the-Loop Governance and AI Accountability (12 hours)
- Deepfake and AI-Powered Fraud Awareness (12 hours)
- EU AI Act Article 4 AI Literacy and Compliance (12 hours)
Prompt & Context Engineering (14) →
- Prompt Engineering Fundamentals (18 hours)
- Applied Prompt Engineering for Business Workflows (18 hours)
- Advanced Prompt Engineering and Reasoning Architectures (18 hours)
- Persona, Instruction, and Structured Output Templates (12 hours)
- Multi-Step Prompt Chaining and AI Workflows (12 hours)
- Context Engineering for Enterprise AI (18 hours)
- Enterprise Knowledge Curation and Context Management for AI (12 hours)
- Working with Long Documents and Large Context Windows (12 hours)
- Structured Research and Analytical Prompting Frameworks (12 hours)
- Prompt Testing, Evaluation (Evals), and Quality Assurance (12 hours)
- Building and Governing Reusable Corporate Prompt Libraries (12 hours)
- Prompt Security, Injection Defense, and Guardrails (12 hours)
- Confidentiality, IP Protection, and Data Sharing Rules in AI Prompting (12 hours)
- Prompt Engineering (18 hours)
AI for Executives & Strategic Leadership (18) →
- AI for Executives
- Executive AI Leadership Program (Advanced) (18 hours)
- AI Strategy and Transformation Leadership (12 hours)
- AI Readiness and Organisational Maturity Assessment (24 hours)
- AI Project Management for Managers (12 hours)
- MLOps and LLMOps for Managers (12 hours)
- AI Use Case Portfolio Management and Discovery (12 hours)
- KPI and ROI Measurement for AI Investments (12 hours)
- AI Build, Buy or Partner Decision Framework (12 hours)
- AI Roadmapping and Strategic Prioritisation (12 hours)
- Cloud LLM APIs vs. On-Premise Models: Cost, Risk and Regulation (12 hours)
- Executive AI Decision Workshop (6 hours)
- AI FinOps: Token Economics, Budgeting and Unit Cost Management (12 hours)
- AI Operating Model Design (12 hours)
- Building and Running an AI Center of Excellence (AI CoE) (12 hours)
- Change Management in AI Transformation (12 hours)
- AI Steering Committee Governance and Decision Support (12 hours)
- AI Project Management with PMI-CPMAI Methodology (12 hours)
AI Adoption & Workforce Transformation (12) →
- AI Champions Enablement Programme (18 hours)
- Enterprise AI Assistant Rollout and Adoption Programme (12 hours)
- Building and Managing an Internal AI Community of Practice (12 hours)
- AI Adoption Metrics and Usage Analytics (12 hours)
- Strategic Workforce Transformation in the Age of AI (12 hours)
- Task-Level AI Impact Analysis and Role Redesign (12 hours)
- AI Competency Mapping and Skills Taxonomy Design (12 hours)
- AI Reskilling and Upskilling Roadmap Design (12 hours)
- Managing Human–Agent Hybrid Teams (12 hours)
- Task Delegation to AI Agents, Output Auditing and Escalation (12 hours)
- Performance Management and Accountability in the Age of AI (12 hours)
- Preventing Skill Atrophy and Fostering Critical Thinking with AI (12 hours)
Role-Specific AI Training (17) →
- AI for Project Managers (18 hours)
- AI for Project Team Members (12 hours)
- AI for Business Analysts (12 hours)
- AI for Product Managers (18 hours)
- AI for Sales Teams (12 hours)
- AI for Marketing Teams (12 hours)
- AI for Customer Experience (CX) Teams (12 hours)
- AI for Finance Professionals (12 hours)
- Generative Engine Optimization (GEO) and AI Search Visibility (12 hours)
- AI for HR and Learning & Development (L&D) Teams (12 hours)
- AI for Operations and Supply Chain Teams (12 hours)
- AI for Legal and Compliance Teams (12 hours)
- AI for Procurement Teams (12 hours)
- AI for Corporate Trainers and Facilitators (12 hours)
- AI for IT Operations and Service Management Teams (12 hours)
- AI for Internal Audit, Risk and Internal Control Teams (12 hours)
- AI for Field Operations and Technical Service Teams (12 hours)
Industry-Specific AI Programmes (18) →
- Generative AI in Banking and Finance: Regulation-Compliant Use Cases (12 hours)
- AI in Insurance: Underwriting, Claims and Distribution (12 hours)
- AI for Payment Institutions and FinTech Companies (12 hours)
- AI Governance and Compliance Under BDDK, SPK, MASAK and KVKK (12 hours)
- AI in Manufacturing and Industrial Operations (12 hours)
- AI in Retail and E-Commerce (12 hours)
- AI in Logistics, Freight and Supply Chain Operations (12 hours)
- AI in the Energy Sector: Generation, Trading and Distribution (12 hours)
- AI in Telecommunications: Network, CVM and Contact Centre (12 hours)
- AI in Healthcare, Hospital Operations and Life Sciences (12 hours)
- AI in Tourism, Hospitality and Travel Operations (12 hours)
- AI in Banking and Financial Services: Strategy, Analytics and Operations (12 hours)
- AI in Manufacturing: Quality Control, Predictive Maintenance and Optimization (12 hours)
- AI in Automotive, OEM/Tier-1 Supply Chain and Mobility (12 hours)
- AI in Energy Grids, Utilities and Critical Infrastructure (12 hours)
- AI in Parcel Delivery, Courier and Last-Mile Operations (12 hours)
- AI in Retail and Commerce: Demand Forecasting, Inventory and CX Use Cases (12 hours)
- AI in Professional Services, Consulting and Advisory Firms (12 hours)
AI Use Cases & Business Transformation (13) →
- AI Use Case Discovery: Finding High-Value Business Opportunities (12 hours)
- Identifying AI Opportunities in Business Processes (12 hours)
- Problem Framing and Decision Point Mapping for AI Projects (12 hours)
- Data Readiness and Dependency Analysis for AI Use Cases (12 hours)
- AI Business Value and Feasibility Assessment (12 hours)
- AI Use Case Risk and Compliance Screening (12 hours)
- AI Use Case Prioritisation Matrix and Portfolio Sequencing (12 hours)
- Designing KPIs and Success Criteria for AI Initiatives (12 hours)
- AI PoC and Pilot Design: From Hypothesis to Field Validation (12 hours)
- AI Project Lifecycle Management: From Discovery to Production Operations (12 hours)
- AI-Powered Business Process Redesign and Target Operating Model (12 hours)
- Post-Pilot AI Scaling Decisions: From Pilot to Enterprise Rollout (12 hours)
- Enterprise AI Readiness Assessment and Maturity Roadmap (12 hours)
Responsible AI & AI Governance (20) →
- Responsible AI Principles and Operational Practice (12 hours)
- AI Ethics, Safety and Security Risk Awareness for Leaders (12 hours)
- Enterprise AI Governance Framework and Operating Mechanisms (12 hours)
- Drafting and Implementing Corporate AI Policies (12 hours)
- AI Governance Roles, RACI and Three Lines of Defence (12 hours)
- AI Risk Classification and Tiered Control Mapping (12 hours)
- EU AI Act Compliance and Corporate AI Literacy (Article 4) (12 hours)
- Data Privacy (KVKK/GDPR) and Intellectual Property in AI Projects (12 hours)
- Third-Party AI Vendor, Foundation Model and Agent Risk Management (12 hours)
- Human-in-the-Loop Process Design and Effective AI Oversight (12 hours)
- Algorithmic Bias, Fairness and Explainability (XAI) for Governance (12 hours)
- AI Audit and Internal Control Framework (12 hours)
- AI Traceability, Audit Logging and Incident Response Management (12 hours)
- ISO/IEC 42001 AI Management System (AIMS) Implementation (12 hours)
- ISO/IEC 42001 Internal Auditor Training for AI Management Systems (12 hours)
- AI Risk Management with the NIST AI RMF (Govern, Map, Measure, Manage) (12 hours)
- Integrating ISO/IEC 42001 (AIMS) with ISO/IEC 27001 (ISMS) (12 hours)
- ISO/IEC 42005 AI System Impact Assessment and FRIA Practice (12 hours)
- Governing Generative AI Risks with NIST AI RMF and NIST AI 600-1 (12 hours)
- Shadow AI Discovery, SaaS AI Controls and Safe Enablement (12 hours)
Applied AI Training 8 categories · 110 courses
AI-Powered Productivity (14) →
- AI-Assisted Document and Report Writing (12 hours)
- AI-Powered Business Research and Deep Research Tools (12 hours)
- AI-Powered Presentation Design (12 hours)
- AI for Excel, Spreadsheet and KPI Analysis (12 hours)
- AI for Decision Support and Scenario Analysis (12 hours)
- Canva AI and Magic Studio for Business Content (12 hours)
- AI for Corporate Communications and PR (12 hours)
- AI-Driven Content Creation and Repurposing (12 hours)
- No-Code AI Applications for Business Teams (12 hours)
- From Prompt to Live Website and Web App with Lovable (12 hours)
- Productivity with Microsoft 365 Copilot (Word, Excel, Outlook, Teams) (12 hours)
- Enterprise AI Assistants for Productivity (ChatGPT, Gemini, Claude) (12 hours)
- Role-Based Enterprise AI Playbooks and Prompt Libraries (12 hours)
- AI for Meeting Management, Action Tracking and Project Coordination (12 hours)
AI Automation & Intelligent Workflows (16) →
- Introduction to Workflow Automation (12 hours)
- Process Mapping and Optimisation for Automation (12 hours)
- AI-Powered Workflow Automation (12 hours)
- Intelligent Workflows with Large Language Models (LLMs) (12 hours)
- Intelligent Document Processing (IDP) and Workflow Automation (12 hours)
- Automated Email and Ticket Triage with AI (12 hours)
- AI Workflow Automation for Marketing and Sales Teams (12 hours)
- AI Workflow Automation for HR and Internal Operations (12 hours)
- API and Webhook-Driven Automation Workflows (12 hours)
- CRM, ERP and Enterprise System Integrations (12 hours)
- Automated Reporting and AI Executive Narratives (12 hours)
- Enterprise Knowledge Workflows and Information Routing (12 hours)
- Human-in-the-Loop (HITL) Workflow Design (12 hours)
- Error Handling, Retries and Resilient Workflow Design (12 hours)
- Logging, Tracing and Observability for AI Workflows (12 hours)
- Secure Architecture for AI and Workflow Automation (12 hours)
Automation Platforms: n8n, Power Platform & Copilot Studio (15) →
- Introduction to n8n (12 hours)
- Advanced n8n (12 hours)
- AI Automations with n8n (12 hours)
- Applied Prompt Engineering with n8n (18 hours)
- Business Process Automation with n8n (12 hours)
- n8n for IT Operations (12 hours)
- n8n for DevOps (12 hours)
- Microsoft Power Platform Fundamentals (12 hours)
- Building Canvas Apps with Power Apps (12 hours)
- Building External Portals with Power Pages (12 hours)
- Power Automate for Analysts and Developers (12 hours)
- Integrating Azure with Microsoft Power Platform (12 hours)
- Microsoft Copilot Studio Fundamentals (12 hours)
- Copilot Studio: Generative AI and Autonomous Agents (12 hours)
- Fast and Practical Automations with Zapier (12 hours)
AI Agent Systems & Autonomous Workflows (13) →
- AI Agent Fundamentals (12 hours)
- Agentic AI for Business Leaders (12 hours)
- Tool-Using AI Agents: Function Calling in Practice (12 hours)
- Agentic Workflow Design (12 hours)
- Building Autonomous AI Agents with LangGraph and Agent SDKs (12 hours)
- Agent Planning and Execution Loops (12 hours)
- Agent Memory and Context Engineering (12 hours)
- Multi-Agent Systems Architecture and Orchestration (12 hours)
- Human-in-the-Loop AI Agents (12 hours)
- Enterprise System Integration with Model Context Protocol (MCP) (12 hours)
- Designing Reusable AI Agent Skills and Playbooks (12 hours)
- AI Agent Evaluation, Benchmarking and Quality Assurance (12 hours)
- AI Agent Security, Identity and Authorization (12 hours)
Multimodal & Conversational AI (19) →
- Multimodal AI Models: Text, Vision, Audio and Video (12 hours)
- Designing and Building Multimodal AI Applications (12 hours)
- Visual Document Intelligence and Extraction with AI (12 hours)
- Multimodal RAG: Indexing and Retrieval Across Text, Tables and Visuals (12 hours)
- Conversation Design for AI Assistants and Voice Agents (12 hours)
- AI Customer Service Agents and Contact Centre Transformation (18 hours)
- Voice AI Systems: STT, TTS and Conversational Audio Pipelines (12 hours)
- Building Real-Time Multimodal and Voice Assistants (12 hours)
- Computer Use Systems: Screen-Based AI Agent Architecture (12 hours)
- UI-Using Agents and Browser Automation (12 hours)
- Human Confirmation, Agency and UI Safety in AI Agents (12 hours)
- User Experience, Trust and Safety Testing for Interactive AI Agents (12 hours)
- Multimodal Model Architecture, Fusion and Fine-Tuning (12 hours)
- Vision-Language Model (VLM) Applications for Enterprise (12 hours)
- Speech-to-Speech Models and Autonomous Voice Agents (12 hours)
- Realtime AI APIs, WebRTC and Low-Latency Streaming Architecture (12 hours)
- Turn-Taking, Endpointing and Sub-Second Latency Engineering (12 hours)
- Document and Screen Understanding with Vision-Language Models (12 hours)
- Multimodal AI Evaluation: Vision, Audio, Document and Video Benchmarks (12 hours)
AI Product Management & User Experience (15) →
- AI Product Strategy and Business Models (12 hours)
- AI Product Discovery, Prototyping and Validation (12 hours)
- AI Product Roadmap and Portfolio Management (12 hours)
- AI Feature Design and Specification (12 hours)
- Generative AI UX and Interaction Design Patterns (12 hours)
- Designing for Trust, Safety and User Control in AI Products (12 hours)
- Explainable AI (XAI) UX: Citations, Provenance and Reasoning Design (12 hours)
- Human-AI Interaction (HAI) and Collaborative Intelligence Design (12 hours)
- AI Product Metrics, Analytics and Outcome Measurement (12 hours)
- Experimentation and A/B Testing for AI Products (12 hours)
- Shaping AI Model Behaviour, Quality Rubrics and Error Analysis (12 hours)
- Optimising Cost, Latency and Quality in AI Products (12 hours)
- AI-Native Digital Product Management (12 hours)
- Agent Experience (AX) and Task Delegation UX (12 hours)
- Model, Prompt and Tool Change Management in Production AI (12 hours)
AI for Designers (13) →
- AI for Designers (12 hours)
- AI-Powered Creative Research and Moodboards (12 hours)
- AI-Assisted Ideation and Concept Development (12 hours)
- Art Direction with Prompts and Reference Images (12 hours)
- AI Image Generation for Visual Content Production (12 hours)
- AI Image Editing and Variation Development (12 hours)
- Brand-Consistent AI Visual Systems (12 hours)
- Typography, Composition and Fine Style Control in Generative AI (12 hours)
- AI-Assisted UI/UX Design (12 hours)
- Rapid Prototyping and Design Iteration with AI (12 hours)
- Canva, Figma and Generative Design Tools in Daily Workflows (12 hours)
- Copyright, Ethics and Safe Use of Generative AI in Design (12 hours)
- Generative AI for Video Production (12 hours)
Technical AI Training 17 categories · 333 courses
AI-Assisted Software Development (26) →
- AI Coding Assistants for Software Engineers (12 hours)
- Disciplined Vibe Coding: From Idea to Working Software (12 hours)
- Agentic Coding for Software Engineering Teams (12 hours)
- From Requirements to Code: AI-Assisted Delivery Workflows (12 hours)
- Harness Engineering for Reliable Coding Agents (18 hours)
- Loop Engineering: Autonomous Generate-Verify-Repair Cycles (18 hours)
- AI-Assisted Code Analysis, Refactoring and Quality Improvement (12 hours)
- AI-Assisted Software Test Generation for Developers (12 hours)
- Evidence-Based Debugging with AI (12 hours)
- AI-Assisted Technical Documentation and Docs-as-Code (12 hours)
- Repository Context Engineering for Large Codebases (18 hours)
- Secure Code Review in the Age of AI-Generated Code (12 hours)
- Enterprise AI Coding Governance, Policies and Standards (12 hours)
- Designing an AI-Native Software Development Life Cycle (SDLC) (12 hours)
- AI-Assisted Legacy Code Modernisation (COBOL, PL/SQL, Monolith to Modern Architecture) (12 hours)
- Testing AI and LLM Applications for QA and Test Engineers (12 hours)
- AIOps: LLM-Assisted Incident Management for SRE and IT Operations (12 hours)
- AI Coding Assistants: From IDE Autocomplete to Agentic Coding (12 hours)
- Designing Repository Instructions, Rules and AGENTS.md (12 hours)
- Spec-Driven Development (SDD) with Coding Agents (12 hours)
- Feature Delivery, Refactoring and Migrations with Coding Agents (12 hours)
- Agentic Testing and Autonomous QA Workflows (12 hours)
- AI-Assisted Code Review and Human Approval Workflows (12 hours)
- Sandboxing, Tool Permissions and Safe Execution for Coding Agents (12 hours)
- Team Workflows, Reusable Agent Skills and Context Handoffs (12 hours)
- Headless Coding Agents in CI/CD Pipelines (12 hours)
LLM Application Engineering (20) →
- Large Language Model (LLM) Fundamentals (12 hours)
- Large Language Models and the Transformer Architecture (12 hours)
- Building Applications with LLM APIs (12 hours)
- Structured Outputs with LLMs: JSON Schema, Pydantic and Constrained Decoding (12 hours)
- LLM Tool Use and Function Calling (12 hours)
- Prompt and Context Architecture for LLM Applications (12 hours)
- Long-Context LLM Engineering and Context Window Management (12 hours)
- Model Routing and Multi-Model Architecture Design (12 hours)
- Building Multimodal LLM Applications: Vision, Documents and Audio (12 hours)
- Mixture of Experts (MoE) LLMs: Architecture, Serving and Fine-Tuning (12 hours)
- Streaming and Real-Time AI Application Engineering (12 hours)
- Small Language Models (SLMs) for Enterprise Applications (12 hours)
- Open-Weight LLM Integration and Self-Hosted Serving (12 hours)
- LLM Cost and Latency Optimisation: Prompt Caching, Batching and FinOps (12 hours)
- LangChain Fundamentals for LLM Application Development (12 hours)
- LLM Engineering for Java & .NET (Spring AI, LangChain4j, Semantic Kernel) (12 hours)
- Building Enterprise LLM Applications on Amazon Bedrock (12 hours)
- Enterprise LLM Development with Azure OpenAI and Azure AI Foundry (12 hours)
- Building Enterprise LLM Applications on Google Cloud Vertex AI (12 hours)
- Production Architecture Patterns for Enterprise LLM Systems (12 hours)
RAG & Enterprise Knowledge Systems (20) →
- RAG with LangChain (3 hours)
- Multimodal RAG (3 hours)
- Retrieval-Augmented Generation (RAG) Fundamentals (12 hours)
- Embeddings and Semantic Search Engineering (12 hours)
- Vector Database Architectures: pgvector, Milvus, FAISS, Weaviate and Pinecone (18 hours)
- Data Preparation, Document Parsing and Chunking for RAG (12 hours)
- Advanced RAG (12 hours)
- Citations, Grounding and Hallucination Control in RAG Systems (12 hours)
- Hybrid Search and Reranking for High-Precision RAG (12 hours)
- Metadata Architecture and Permission-Aware Retrieval in RAG (12 hours)
- Agentic RAG: Multi-Step, Corrective and Adaptive Retrieval Architectures (12 hours)
- GraphRAG and Knowledge-Graph-Enhanced Retrieval Systems (12 hours)
- RAG Evaluation and Quality Assurance: Golden Datasets, LLM-as-a-Judge and CI/CD (12 hours)
- Retrieval and Generation Metrics for RAG Systems (12 hours)
- Production RAG Architecture: Scaling, Freshness, Security and Operations (12 hours)
- Building an Enterprise Knowledge Assistant: Architecture and Implementation (12 hours)
- Text-to-SQL and Conversational Analytics over Enterprise Databases (12 hours)
- Semantic Layers and Governed Metric Definitions for Text-to-SQL and AI Analytics (12 hours)
- SQL Query Validation, Guardrails and Access Control for Text-to-SQL (12 hours)
- Text-to-SQL Accuracy Evaluation and Enterprise Benchmarking (12 hours)
AI Agent Engineering (18) →
- ReAct Pattern for LLM Agents: Reasoning and Acting (12 hours)
- Plan-and-Execute Agents: Planning, Execution and Replanning (12 hours)
- State and Workflow Management for AI Agents (12 hours)
- Tool Design and Tool Contracts for LLM Agents (12 hours)
- Building Agent Systems with LangGraph (12 hours)
- OpenAI Agents SDK and Tool-Based Agent Systems (12 hours)
- Building MCP Servers and Clients (Model Context Protocol) (12 hours)
- Multi-Agent Orchestration: Supervisor, Hierarchical and Swarm Patterns (12 hours)
- Agent Memory: Short-Term and Long-Term Memory Architectures (12 hours)
- Sandboxing and Secure Code Execution for AI Agents (12 hours)
- Agent Evaluation, Tracing and Production Monitoring (12 hours)
- Resilience, Error Recovery and Durable Execution in Agent Systems (12 hours)
- Agent Architecture and Agentic Workflow Patterns (12 hours)
- ReAct, Plan-and-Execute and State Management: Integrated Agent Control (12 hours)
- Handoffs and Agent-as-Tool: Delegation Patterns in Agent Systems (12 hours)
- Agent Skills and Capability Design: Modular Agent Architecture (12 hours)
- Agent Interoperability and A2A (Agent2Agent) Protocols (12 hours)
- Human Approval and Escalation: Human-in-the-Loop Agent Workflows (12 hours)
LLM Customisation & Model Adaptation (19) →
- Prompting, RAG or Fine-Tuning: LLM Adaptation Decision Framework (18 hours)
- Model and Data Readiness: Base Model Selection and Data Suitability (12 hours)
- Quality, Cost and Risk Analysis in LLM Adaptation (12 hours)
- Baselines and Success Metrics: Pre-Adaptation Benchmarking for LLMs (12 hours)
- Fine-Tuning Fundamentals: Introduction to Customising LLMs (18 hours)
- Advanced Fine-Tuning: Continual Pre-Training, Long Context and Model Merging (18 hours)
- Supervised Fine-Tuning (SFT): Engineering and Optimisation (18 hours)
- Parameter-Efficient Fine-Tuning (PEFT): Architectures and Multi-Adapter Serving (18 hours)
- Practical LLM Fine-Tuning with LoRA and QLoRA (12 hours)
- Instruction Tuning: Following Complex Instructions, Schemas and Domain Constraints (12 hours)
- Preference Optimization: DPO, ORPO, KTO and LLM Alignment (12 hours)
- Synthetic Data Generation: Data Synthesis and Distillation for LLM Training (12 hours)
- Training Data Design: Dataset Architecture for LLM Fine-Tuning (12 hours)
- Model Evaluation and Fine-Tuning Evals for Custom LLMs (12 hours)
- Open-Weight Model Adaptation: Customising Llama, Qwen, Mistral and Gemma (12 hours)
- Turkish Language Models: Tokenization, Evaluation and Adaptation (12 hours)
- Distributed LLM Training with PyTorch FSDP and DeepSpeed (24 hours)
- Reinforcement Learning for Reasoning Models (GRPO and RLVR) (24 hours)
- Dataset Quality and Decontamination for LLM Training (12 hours)
Local & On-Premise LLM Platforms (20) →
- LLM Model Serving and Deployment Fundamentals (12 hours)
- LLM Serving with vLLM: Production Inference Deployment (12 hours)
- Hugging Face Text Generation Inference (TGI) for LLM Serving (12 hours)
- Running Local LLMs with Ollama (12 hours)
- LLM Serving Stack Mastery: FastAPI, vLLM, KServe and Triton (18 hours)
- LLM Quantization: INT8, INT4, FP8, FP16 and BF16 in Practice (12 hours)
- Dynamic Quantization for Neural Networks and LLMs (12 hours)
- Quantization-Aware Training, QLoRA Fine-Tuning and Quantized Serving (12 hours)
- GPU Capacity Planning and Hardware Sizing for LLM Inference (12 hours)
- In-House LLM Platform Architecture: From Hardware Sizing to Air-Gapped Production (12 hours)
- Air-Gapped LLM Deployment, Offline Registry Mirroring and Update Operations (12 hours)
- Running Local LLMs on Desktop and Workstations: llama.cpp, GGUF and LM Studio (12 hours)
- Self-Hosted AI Coding Assistants with Local LLMs (12 hours)
- Open-Weight LLM Selection, Licensing and Benchmarking for Enterprise Use (12 hours)
- Enterprise Model Serving with NVIDIA Triton Inference Server and KServe (12 hours)
- KV Cache Management and Continuous Batching Optimization for LLM Inference (12 hours)
- LLM Inference Throughput and Latency Optimization (12 hours)
- Running AI and LLM Workloads on Kubernetes (18 hours)
- Deploying Small Language Models on Edge and On-Device Hardware (12 hours)
- LLM Unit Economics: Cost per Request and Token Optimization (12 hours)
LLMOps & AI in Production (21) →
- LLMOps Fundamentals: Operating LLM Applications in Production (12 hours)
- End-to-End LLMOps: Production Architecture and Implementation (12 hours)
- Versioning Prompts, Models, Tools and Datasets in LLM Systems (12 hours)
- AI Model Gateways and Intelligent LLM Routing (12 hours)
- CI/CD Pipelines and Automated Quality Gates for AI and LLM Applications (12 hours)
- LLM Evaluation Methodology, Metrics and Frameworks (12 hours)
- Engineering Automated and Scalable LLM Evaluation Pipelines (12 hours)
- Continuous Online Evaluation and Drift Detection for Production LLMs (12 hours)
- Regression Testing for LLM, RAG and Agent Applications (12 hours)
- LLM Tracing and Observability with OpenTelemetry, Langfuse and Arize Phoenix (12 hours)
- Runtime Guardrails and Safety Layers for Production LLM Applications (12 hours)
- LLM Caching Strategies: Prompt Caching, Semantic Caching and Runtime Cost Control (12 hours)
- Application-Level Performance and Latency Engineering for LLM Systems (12 hours)
- AI Incident Management, Runbooks and Production Failure Response (12 hours)
- Hybrid Cloud and On-Premises AI Deployment Architectures (12 hours)
- LLM Evaluations (Evals) Fundamentals: A Practical Introduction (12 hours)
- Golden Dataset Curation and Test Case Design for LLM Applications (12 hours)
- Rule-Based Assertions and Model-Graded (LLM-as-a-Judge) Evaluators (12 hours)
- Evaluating RAG Pipelines and Autonomous AI Agents (12 hours)
- Bridging Offline Benchmarks and Online Production Evaluation for LLMs (12 hours)
- User Feedback Loops and Data Flywheels for Production LLM Products (12 hours)
AI Security & Red Teaming (20) →
- Prompt Injection Attacks and Defenses for LLM Applications (12 hours)
- Indirect Prompt Injection in RAG and Agent Systems (12 hours)
- Sensitive Data Exposure in LLM Applications (12 hours)
- Tool Misuse and Excessive Agency in AI Agents (12 hours)
- RAG Poisoning and Knowledge Base Security (12 hours)
- AI Model and Supply Chain Security Risks (12 hours)
- AI Agent Authentication, Authorization and Identity Security (12 hours)
- AI Threat Modeling for LLM, RAG and Agent Systems (12 hours)
- AI Red Teaming for LLM, RAG and Agent Applications (12 hours)
- LLM Guardrails and Multi-Layer Defense Design (12 hours)
- Automated AI Security Testing and CI/CD Security Evaluations (12 hours)
- Secure Enterprise AI Reference Architecture (12 hours)
- Privacy-Preserving LLM Architectures: PII Masking, Anonymization and Data Residency (18 hours)
- Building PII Detection and Masking Gateways for LLMs (12 hours)
- Data Anonymization and Synthetic Test Data Generation for AI (12 hours)
- Data Minimization and KVKK Compliance in AI Logging and Observability (12 hours)
- Agent Goal Hijacking: Detection and Defense in Autonomous AI (12 hours)
- Agentic AI Supply Chain and Model Context Protocol (MCP) Security (12 hours)
- Preventing Unexpected Code Execution in LLM and Agent Systems (12 hours)
- Sandboxing and Isolated Execution Environments for AI Agents (12 hours)
Model Security & AI in Cybersecurity (11) →
- AI and Machine Learning Model Security Fundamentals (12 hours)
- Adversarial Machine Learning: Evasion Attacks and Robustness Defenses (12 hours)
- AI Data Poisoning and Backdoor Attacks in Training and Fine-Tuning (12 hours)
- Deep Learning Model Security: Architectures, Weights and Inference Protection (18 hours)
- MLOps Security and DevSecOps for Machine Learning Pipelines (12 hours)
- LLM Application Security: OWASP Top 10 and Prompt Injection Defense (12 hours)
- AI Red Teaming and Machine Learning Model Penetration Testing (12 hours)
- AI Applications in Cybersecurity Operations and Defense (12 hours)
- AI-Driven Cyber Threat Detection for Endpoint, Network and Cloud (12 hours)
- Anomaly Detection with Machine Learning for Security and Operations (12 hours)
- AI-Powered SIEM and Modern SOC Operations (12 hours)
Machine Learning & Applied Data Science (25) →
- Machine Learning Fundamentals (12 hours)
- Advanced Machine Learning (12 hours)
- Machine Learning for Data Analysis (12 hours)
- Feature Engineering for Machine Learning (18 hours)
- Model Evaluation and Explainability (12 hours)
- Model Validation and Model Risk Management (12 hours)
- Time Series Forecasting (12 hours)
- Applied Machine Learning (24 hours)
- Anomaly Detection with Machine Learning (12 hours)
- Fraud Detection with Machine Learning (12 hours)
- Risk Scoring and Credit Scorecard Modelling (12 hours)
- Customer Churn and Propensity Modelling (12 hours)
- Recommendation Systems (12 hours)
- Predictive Maintenance with Machine Learning (12 hours)
- Demand Forecasting for Supply Chain and Retail (12 hours)
- Optimization and Decision Systems (12 hours)
- Model Development with XGBoost and LightGBM (12 hours)
- Automated Machine Learning (AutoML) (12 hours)
- Explainable AI (XAI) (12 hours)
- Causal Inference and Uplift Analytics (12 hours)
- Introduction to Machine Learning - Regression Models (2 hours)
- Federated Learning and Privacy-Preserving ML (12 hours)
- Online Machine Learning and Streaming Analytics (12 hours)
- Graph Analytics and Graph Machine Learning (12 hours)
- Tabular and Time-Series Foundation Models (TabPFN, Chronos, TimesFM) (12 hours)
Deep Learning & Natural Language Processing (19) →
- Deep Learning with PyTorch (42 hours)
- Deep Learning Fundamentals (18 hours)
- Advanced Deep Learning (18 hours)
- Modern Neural Network Architectures (18 hours)
- Transformer Architectures in Depth (18 hours)
- Deep Learning with TensorFlow and Keras (18 hours)
- Model Compression and Edge AI Deployment (12 hours)
- Deep Generative Models and Architectures (12 hours)
- Reinforcement Learning and Sequential Decision Making (12 hours)
- Deep Learning for Fraud Detection (18 hours)
- Deep Learning for Defect and Fault Detection (18 hours)
- Deep Learning for Time Series Forecasting (18 hours)
- Deep Learning for Recommendation Systems (18 hours)
- Natural Language Processing (NLP) Fundamentals (12 hours)
- Advanced Natural Language Processing (NLP) (12 hours)
- Deep Learning for Natural Language Processing (18 hours)
- Production NLP Engineering (18 hours)
- Text Classification and Information Extraction (12 hours)
- Semantic Search and Neural Information Retrieval (12 hours)
Computer Vision (18) →
- Computer Vision (36 hours)
- Computer Vision Fundamentals (12 hours)
- Deep Learning for Computer Vision (18 hours)
- Advanced Computer Vision (12 hours)
- Computer Vision Bootcamp (120 hours)
- Object Detection and Segmentation (12 hours)
- Image Segmentation Models (12 hours)
- Vision Transformers (ViT) in Practice (12 hours)
- Document AI and OCR Systems (12 hours)
- Video Analytics and Multi-Camera Tracking (12 hours)
- Human Action Recognition and Spatio-Temporal Models (12 hours)
- Multimodal Learning and Vision-Language Models (VLMs) (12 hours)
- Automated Visual Inspection and Quality Control Systems (12 hours)
- Computer Vision for Hospitals: Clinical Operations and Patient Safety (12 hours)
- Medical Image Analysis and Computer Vision in Healthcare (12 hours)
- Computer Vision for Hotels and Hospitality Operations (12 hours)
- Deploying Computer Vision Models on Edge Devices (12 hours)
- Model Compression and Optimization for Computer Vision (12 hours)
MLOps & AI Platform Engineering (21) →
- MLOps – Fundamentals (30 hours)
- Practical MLOps: End-to-End ML Pipelines (12 hours)
- MLOps – Advanced Level (30 hours)
- Experiment Tracking and Hyperparameter Management in ML (12 hours)
- Model Tracking and Experiment Management with MLflow (12 hours)
- Experiment, Data and Model Lifecycle Management with Weights & Biases (W&B) (12 hours)
- Data and Model Versioning with DVC and LakeFS (12 hours)
- Enterprise Model Registry and Model Lifecycle Governance (12 hours)
- Model Serving and High-Performance Inference Architectures (12 hours)
- CI/CD and Continuous Training (CT) for Machine Learning (12 hours)
- Container and Kubernetes Deployment for AI and ML Workloads (18 hours)
- GPU Acceleration and Inference Optimization (12 hours)
- Enterprise MLOps and Model Deployment on Amazon SageMaker (12 hours)
- Production Model Monitoring and ML Observability (12 hours)
- Data and Concept Drift Detection and Continuous Adaptation (12 hours)
- Feature Store Architectures and Feature Engineering Platforms (18 hours)
- Responsible and Safe ML Deployment (12 hours)
- Enterprise AI Platform Architecture and Platform Engineering (12 hours)
- Self-Service AI Platforms and Internal Developer Experience (Golden Paths) (12 hours)
- Policy, Secrets and Access Control for Enterprise AI Platforms (12 hours)
- AI FinOps: Cost and GPU Capacity Management (12 hours)
Model Serving & Deployment (23) →
- Introduction to Model Deployment (12 hours)
- REST API and gRPC Fundamentals for Model Serving (12 hours)
- Synchronous vs Asynchronous Inference (12 hours)
- Batch, Real-Time and Streaming Inference Fundamentals (12 hours)
- Model Serialization and Model File Formats (12 hours)
- Model Serving Architectures (18 hours)
- Latency, Throughput and Cost Trade-offs in Model Serving (12 hours)
- Security for Model Serving and Inference APIs (12 hours)
- TensorFlow Model Serving Fundamentals (12 hours)
- Advanced TensorFlow Model Serving and Optimisation (12 hours)
- Deploying TensorFlow Serving on Docker and Kubernetes (18 hours)
- TorchServe Fundamentals for PyTorch Model Serving (12 hours)
- Advanced TorchServe: Workflows, Optimization and Scaling (12 hours)
- Dynamic and Offline Batch Inference with TorchServe (12 hours)
- ONNX and ONNX Runtime Fundamentals (12 hours)
- NVIDIA Triton Inference Server Fundamentals (12 hours)
- Advanced NVIDIA Triton: Ensembles, BLS, LLMs and Tuning (12 hours)
- Integrating Multi-Framework Models with NVIDIA Triton (12 hours)
- Serving Machine Learning and LLM Models with FastAPI (12 hours)
- Serving Machine Learning Models with Flask (12 hours)
- Distributed Model and LLM Serving with Ray Serve (12 hours)
- Model Versioning, Rollout Strategies and Safe Replacement (12 hours)
- Scaling Deployed Machine Learning and LLM Services (12 hours)
Programming for AI (9) →
- Advanced Python for AI and Data Engineering (12 hours)
- API Integration and Development with Python for AI Projects (12 hours)
- Building Modern Backend and AI APIs with FastAPI (12 hours)
- PyTorch Fundamentals for Deep Learning (12 hours)
- TensorFlow and Keras Fundamentals for Deep Learning (12 hours)
- Python for Data Science (18 hours)
- R Programming for Data Science and Statistical Modelling (12 hours)
- Python Programming (24 hours)
- Modern C++ Fundamentals and High-Performance AI Applications (12 hours)
Data Science & AI-Ready Data Engineering (27) →
- Web Scraping (36 hours)
- Data Science (48 hours)
- Introduction to Data Science (12 hours)
- Python Fundamentals for Data Science (12 hours)
- Statistics for Data Science (12 hours)
- Advanced Data Science (12 hours)
- Data Modeling and Data Science (TDWI Body of Knowledge Topics) (12 hours)
- Data Analyst Training: From Business Question to Insight (12 hours)
- SQL Fundamentals for Data Analysis (12 hours)
- Advanced SQL for Analytics and Query Optimization (12 hours)
- AI-Ready Data Engineering (18 hours)
- Data Quality Testing and Data Contracts (12 hours)
- Data Lineage, Catalogs and Data Observability (12 hours)
- Unstructured Data Pipelines for Documents, Audio and Images (12 hours)
- The Modern Data Stack: dbt, Apache Airflow and Apache Iceberg (12 hours)
- AI-Ready Data Architecture (12 hours)
- Automated Data Quality Testing for Analytics and AI (12 hours)
- Data Contracts: Producer-Consumer Agreements and Schema Governance (12 hours)
- Data Lineage and Enterprise Data Catalogs (12 hours)
- Data Observability: Monitoring, Drift Detection and Incident Management (12 hours)
- Multimodal Data Ingestion: Document, Audio and Image Parsing (12 hours)
- dbt and Analytics Engineering Transformation Workflows (12 hours)
- Dirty Data, Clean CV: Real-World ML, Interviews & Career (3 hours)
- Data and AI Pipeline Orchestration with Apache Airflow (12 hours)
- Data Lakehouse Architecture with Apache Iceberg (12 hours)
- Semantic Layer Design for BI, Text-to-SQL and AI Agents (12 hours)
- Metadata Engineering for RAG and Autonomous Agents (12 hours)
Enterprise AI Platforms & Agent Cloud Ecosystem (16) →
- Enterprise AI Development with Microsoft Azure AI Foundry (12 hours)
- Building Multi-Agent Systems with Microsoft Agent Framework (12 hours)
- GitHub Copilot and Autonomous Coding Agents for Engineering Teams (12 hours)
- Enterprise Agent Infrastructure with Amazon Bedrock AgentCore (12 hours)
- Developing Production AI Agents with AWS Strands Agents SDK (12 hours)
- Amazon Bedrock Knowledge Bases and Guardrails (12 hours)
- Amazon SageMaker AI and Enterprise ML Platform Services (12 hours)
- Google Cloud Vertex AI and Gemini Enterprise Agent Platform (12 hours)
- Building Multi-Agent Applications with Google Agent Development Kit (ADK) (12 hours)
- Enterprise Agent Development with Google Cloud Vertex AI Agent Engine (12 hours)
- Vertex AI Model Garden: Enterprise Model Selection and Endpoint Management (12 hours)
- Governance and Observability in Cloud-Based Agent Systems (12 hours)
- Enterprise AI Lifecycle with the IBM watsonx Platform (12 hours)
- Enterprise Digital Workers and Automation with IBM watsonx Orchestrate (12 hours)
- Stateful Multi-Agent Architectures and Production Orchestration with LangGraph (12 hours)
- Open-Source Model and Agent Ecosystem: Self-Hosted Enterprise AI Stack (12 hours)
Software, Data, Process & Technology Training 17 categories · 170 courses
Microsoft Power Platform & Copilot Studio (7) →
- Enterprise Canvas and Model-Driven App Development with Microsoft Power Apps (12 hours)
- Cloud and Desktop Process Automation with Microsoft Power Automate (12 hours)
- MS Power Platform (30 hours)
- Microsoft Dataverse: Enterprise Data Modeling, Security, and Business Rules (12 hours)
- Azure and Power Platform Integration: Fusion Development Architecture (12 hours)
- Copilot Studio Agent and Power Automate Workflow Integration (12 hours)
- Power Platform Governance, DLP, CoE, and Environment Strategy (12 hours)
Business Intelligence & Analytics (12) →
- Data Visualization for Business Reporting (12 hours)
- Advanced Power BI (12 hours)
- Data Modeling and DAX for Power BI (12 hours)
- Power Query for Data Preparation and Transformation (12 hours)
- Microsoft Fabric Fundamentals (12 hours)
- Migrating from Power BI to Microsoft Fabric (12 hours)
- Data Analysis with Excel (12 hours)
- Python in Excel: Automating Analysis with pandas (12 hours)
- SQL and Power BI for Business Analysts (12 hours)
- Tableau for Data Analysis and Dashboards (12 hours)
- AI-Assisted Data Analysis and Reporting (12 hours)
- Microsoft Power BI Fundamentals (12 hours)
Cybersecurity (15) →
- Cybersecurity Fundamentals (12 hours)
- Zero Trust Architecture and Implementation (12 hours)
- Application Security (AppSec) and Secure SDLC (12 hours)
- API Security: OWASP API Top 10, OAuth 2.0 and Gateway Controls (12 hours)
- Software Supply Chain Security: SBOM, SLSA and CI/CD Hardening (12 hours)
- Red Team, Blue Team and Purple Team Cyber Defense Exercises (12 hours)
- Cybersecurity Incident Response and Digital Forensics Triage (12 hours)
- SIEM Operations and Security Operations Center (SOC) Analyst Training (12 hours)
- Agentic SOC, SOAR and AI-Driven Security Automation (12 hours)
- Adversarial Machine Learning: Evasion, Poisoning and Model Robustness (12 hours)
- LLM, RAG and AI Agent Security (12 hours)
- ISO/IEC 27001 Information Security Management System (ISMS) (12 hours)
- Linux Network Administration and Security Hardening (12 hours)
- Malware Analysis and Reverse Engineering Fundamentals (12 hours)
- CISSP Exam Preparation: 8 Security Domains (24 hours)
Business Analysis (9) →
- Agile Business Analysis (12 hours)
- CBAP / CCBA Exam Preparation (24 hours)
- Advanced Business Analysis (12 hours)
- Applied Business and Systems Analysis (12 hours)
- AI-Assisted Business Analysis (12 hours)
- Software Requirements Analysis (12 hours)
- Business Process Analysis and Design (12 hours)
- Business Process Management (BPM) (12 hours)
- Business Analysis Fundamentals (12 hours)
Web Development – Frontend (6) →
- TypeScript for Modern Application Development (12 hours)
- Modern Web Development with React and Next.js (12 hours)
- Modern Single Page Application (SPA) Architecture and Libraries (12 hours)
- Enterprise Frontend Development with Angular (12 hours)
- Micro Frontend and Monorepo Architecture (12 hours)
- State Management with Redux Toolkit (12 hours)
Web Development – Backend (20) →
- Java and Spring Boot Backend Development (12 hours)
- .NET and ASP.NET Core Web API Development (12 hours)
- Node.js and NestJS Backend Development (12 hours)
- REST API Design Best Practices (12 hours)
- Event-Driven Architecture with Kafka and Messaging (12 hours)
- Microservices Architecture (12 hours)
- Secure Software Development (SSDLC & OWASP) (12 hours)
- Legacy System Modernization and Refactoring Strategies (12 hours)
- Web Development with ASP.NET MVC (.NET Framework) (12 hours)
- Web Application Development with ASP.NET Core MVC (12 hours)
- SharePoint Server and SharePoint Framework (SPFx) Development (12 hours)
- Software Design Patterns and Clean Architecture (12 hours)
- Enterprise Application Architecture and Integration Patterns (18 hours)
- Microservices with .NET, MassTransit and .NET Aspire (12 hours)
- Microservices with Java, Spring Boot and Spring Cloud (12 hours)
- API Development with GraphQL (12 hours)
- Software Modelling with Domain-Driven Design (DDD) (12 hours)
- Inter-Service Communication with gRPC and Protocol Buffers (12 hours)
- Data Structures and Algorithms for Software Engineers (12 hours)
- Modern Web and API Development with PHP 8 and Laravel (12 hours)
Software Testing & Quality (12) →
- Software Testing and Modern Quality Engineering (18 hours)
- A/B Testing and Online Controlled Experiments (12 hours)
- Clean Code, Refactoring and Unit Testing Practices (12 hours)
- Practical Software Testing (Manual, API & Exploratory) (12 hours)
- Test Analysis, Requirements Engineering and Test Design Techniques (12 hours)
- ISTQB Foundation Level (CTFL v4.0) Software Testing (24 hours)
- Web UI Test Automation with Selenium WebDriver (12 hours)
- Modern Web and Component Testing with Cypress (12 hours)
- Test Automation Architecture and Sustainable Quality Processes (12 hours)
- End-to-End Web and API Testing with Playwright (12 hours)
- Mobile Application Test Automation with Appium 2 (12 hours)
- Performance and Load Testing with Apache JMeter (12 hours)
Databases (18) →
- Big Data Querying and Analytics with Apache Spark SQL (12 hours)
- PostgreSQL for Developers: From Fundamentals to Advanced SQL (12 hours)
- PostgreSQL Database Administration, High Availability and Operations (12 hours)
- MySQL and MariaDB Development, Tuning and Administration (12 hours)
- Oracle Database Architecture, SQL Tuning and Administration (12 hours)
- MongoDB Document Data Modelling, Aggregation and Operations (12 hours)
- In-Memory Data Structures, Caching and Messaging with Redis (12 hours)
- Distributed NoSQL Databases with Apache Cassandra (12 hours)
- Search and Real-Time Analytics with Elasticsearch and OpenSearch (12 hours)
- Graph Databases, Data Modelling and Cypher with Neo4j (12 hours)
- Time-Series Databases with TimescaleDB and InfluxDB (12 hours)
- Vector Databases, ANN Indexing and Hybrid Search Architecture (12 hours)
- Practical Vector Search with pgvector, Milvus, Weaviate and Pinecone (12 hours)
- Database Performance Tuning and SQL Query Optimization (12 hours)
- Oracle PL/SQL Database Programming and Performance (12 hours)
- Relational Data Modelling, SQL Normalization and Schema Optimization (12 hours)
- SQL Server Database Querying Fundamentals (18 hours)
- T-SQL Querying with SQL Server (30 hours)
Big Data (11) →
- Big Data (48 hours)
- Apache Spark (30 hours)
- Streaming Analytics: Real-Time Data Processing and Analysis (12 hours)
- Hadoop, Hive and HBase: The Hadoop Ecosystem in Practice (12 hours)
- Data Engineering Fundamentals (18 hours)
- Python for Data Engineering (18 hours)
- PySpark: Distributed Data Processing with Python (12 hours)
- Apache Kafka for Event Streaming (12 hours)
- Apache Airflow: Workflow Orchestration for Data Pipelines (12 hours)
- Data Quality and Data Contracts for Reliable Data Platforms (12 hours)
- Observability for Data Platforms and Distributed Systems (12 hours)
Infrastructure & Systems Administration (7) →
- Windows Server Installation, Configuration and Storage Management (12 hours)
- Microsoft SharePoint: Intranet, Document Management and Governance (12 hours)
- Linux System Administration for Enterprise Environments (12 hours)
- VMware vSphere: Virtualisation, Cluster Management and Operations (12 hours)
- Cisco CCNA: Enterprise Networking Fundamentals and Configuration (12 hours)
- Cisco CCNP Enterprise: Advanced Routing, Switching and SD-WAN (24 hours)
- Active Directory Domain Services (AD DS) Configuration and Hardening (12 hours)
Docker & Kubernetes (6) →
- Docker: Containerisation and Multi-Container Application Delivery (12 hours)
- Kubernetes: Container Orchestration, Deployment and Operations (18 hours)
- Helm: Packaging, Templating and Managing Kubernetes Applications (12 hours)
- Managed Kubernetes in the Cloud: Amazon EKS, Azure AKS and Google GKE (12 hours)
- Kubernetes Security and Cluster Troubleshooting (18 hours)
- Container and Kubernetes Security: Hardening, Policy and Runtime Defence (18 hours)
DevOps & MLOps (8) →
- DevSecOps: Automated Security in CI/CD and Cloud-Native Delivery (12 hours)
- GitOps for Kubernetes with Argo CD and Flux (12 hours)
- Infrastructure as Code (IaC) with Terraform, OpenTofu and Ansible (12 hours)
- CI/CD Pipelines: Continuous Integration and Continuous Delivery (12 hours)
- Platform Engineering: Designing Internal Developer Platforms (IDP) (18 hours)
- Site Reliability Engineering (SRE) Fundamentals (12 hours)
- Microsoft PowerShell for System Administration and Automation (12 hours)
- AIOps Foundation: AI-Driven IT Operations and Incident Intelligence (12 hours)
Cloud Technologies (5) →
- AWS Fundamentals: Core Services, Security and Cloud Operations (12 hours)
- Microsoft Azure Fundamentals: Core Services, Governance and Operations (12 hours)
- Google Cloud (GCP) Fundamentals: Core Infrastructure, Data and Services (12 hours)
- Cloud Architecture: Designing Scalable, Resilient and Cost-Effective Systems (12 hours)
- Cloud Security: Identity, Data Protection, CSPM and Threat Detection (12 hours)
MS Office (8) →
- Microsoft Word, PowerPoint and Project for Business Professionals (12 hours)
- Microsoft Excel Fundamentals (12 hours)
- Microsoft Excel Intermediate (12 hours)
- Microsoft Excel Advanced (12 hours)
- Microsoft Project Fundamentals (12 hours)
- Microsoft Project Advanced (18 hours)
- Microsoft Excel Macros (VBA) Training (24 hours)
- Microsoft Excel Advanced – Expert Level (30 hours)
UX/UI & Digital Marketing (13) →
- UX/UI Design Fundamentals: User-Centred Digital Product Design (12 hours)
- Figma for UI/UX Teams: Auto Layout, Components, Variables and Dev Mode (12 hours)
- Design Systems: Tokens, Component Libraries, Governance and Code Sync (12 hours)
- Interactive Prototyping: From Rapid Flows to High-Fidelity Validation (12 hours)
- User Research: Qualitative, Quantitative and Usability Testing Methods (12 hours)
- AI-Powered UI/UX: Designing with AI Tools and Building AI-Native Interfaces (12 hours)
- Digital Marketing Strategy and Full-Funnel Execution (12 hours)
- Content Marketing Strategy: Topic Authority, Production and Distribution (12 hours)
- Lead Generation: B2B Demand Generation, ABM and Funnel Conversion (12 hours)
- Marketing Analytics: GA4, Attribution, Funnel Analysis and ROI Dashboards (12 hours)
- AI-Powered Content and Marketing Campaign Production (12 hours)
- E-Commerce Fundamentals: Storefront, Merchandising, Operations and Growth (12 hours)
- GEO (Generative Engine Optimization) (6 hours)
Project Management (12) →
- Project Management Fundamentals (12 hours)
- PMP / CAPM Exam Preparation (24 hours)
- Agile, Scrum and Kanban in Practice (12 hours)
- Project Risk Management (12 hours)
- AI-Powered Project Management (12 hours)
- TOGAF Enterprise Architecture (24 hours)
- Project and Agile Work Management with Jira (12 hours)
- Product Management (12 hours)
- Agile Coaching (12 hours)
- Product Owner Training (12 hours)
- Agile Project Manager (12 hours)
- IT Service Management with ITIL (12 hours)
Technology Leadership & Management Skills 8 categories · 59 courses
Leadership & People Management in the Age of AI (7) →
- Leading with Clarity (12 hours)
- Situational Leadership (12 hours)
- Delegation Across Humans and AI Agents (12 hours)
- Accountability and Decision Rights (12 hours)
- Psychological Safety for High-Performing Teams (12 hours)
- Performance and Development Conversations (12 hours)
- Effective 1:1s and Team Rituals (12 hours)
Strategic Communication, Storytelling & Executive Presence (7) →
- Strategic Communication (12 hours)
- Executive Communication (12 hours)
- Storytelling for Business (12 hours)
- Data Storytelling (12 hours)
- Executive Presence (12 hours)
- High-Impact Presentations and Q&A Mastery (12 hours)
- AI-Powered Presentations and Business Communication (12 hours)
Critical Thinking, Problem Solving & Decision Quality (7) →
- Problem Framing (12 hours)
- Critical and Analytical Thinking (12 hours)
- Cognitive Biases in Decision-Making (12 hours)
- Evaluating Evidence and Source Quality (12 hours)
- Decision Criteria and Trade-Off Design (12 hours)
- Scenario Planning and Pre-Mortem Analysis (12 hours)
- Counter-Argumentation and Red-Team Thinking with AI (12 hours)
Creative Problem Solving, Systems Thinking & Innovation (7) →
- Creative Problem Solving (12 hours)
- Systems Thinking (12 hours)
- Design Thinking (12 hours)
- Problem Reframing (12 hours)
- Ideation and Prioritization (12 hours)
- Rapid Experimentation and Prototype Design (12 hours)
- Creative Thinking with AI (12 hours)
Negotiation, Influence & Stakeholder Management (7) →
- Stakeholder Mapping (12 hours)
- Influencing Without Authority (12 hours)
- BATNA and ZOPA (12 hours)
- Value Creation and Concession Architecture (12 hours)
- Objection and Conflict Management (12 hours)
- Coalition Building and Mobilizing Support (12 hours)
- Communicating with Difficult Stakeholders (12 hours)
Collaboration, Facilitation & High-Performing Teams (7) →
- Cross-Functional Collaboration for Managers and Team Leads (12 hours)
- Facilitation Skills for Managers and Workshop Leaders (12 hours)
- Effective Meeting and Workshop Design (6 hours)
- Decision Clarity and Action Accountability (12 hours)
- Productive Conflict: Turning Disagreement into Better Decisions (12 hours)
- Team Norms and Working Agreements (12 hours)
- Hybrid and Asynchronous Collaboration for Distributed Teams (12 hours)
Adaptability, Resilience & Navigating Change (7) →
- Adaptability and Learning Agility in Changing Environments (12 hours)
- Resilience: Sustaining Performance Under Pressure and Uncertainty (12 hours)
- Psychology of Change: Navigating Transitions and Resistance (12 hours)
- Prioritisation and Decision-Making Under Uncertainty (12 hours)
- Growth Mindset and Experimental Learning Culture (12 hours)
- Change Communication: Building Alignment and Trust in Uncertainty (12 hours)
- Employee Experience and Adoption in AI Transformation (12 hours)
Coaching, Feedback, Mentoring & Learning Culture (10) →
- Coaching Mindset: Leader as Coach and Powerful Questioning (12 hours)
- Effective Feedback: Radical Candor and Actionable Conversations (12 hours)
- Corporate Mentoring: Structured Experience Sharing and Mentoring Skills (12 hours)
- Development Conversations: Career and Capability Dialogues (12 hours)
- Learning Objective Design and Competency Mapping (12 hours)
- Peer Learning: Collaborative Learning Circles and Peer Coaching (12 hours)
- Learning Culture and Knowledge Sharing in Organisations (12 hours)
- AI-Powered Personalised Learning Support and L&D Design (12 hours)
- Train the Trainer: Internal Facilitation and Learning Experience Design (12 hours)
- PRINCE2 Foundation Preparation and Structured Project Management (24 hours)
Corporate Academies 1 categories · 8 courses
Corporate Academies & Programme Models (8) →
- Executive AI Leadership Academy (30 hours)
- AI Fluency and Business Productivity Academy (30 hours)
- Agentic Automation Academy (30 hours)
- Generative AI Engineering Bootcamp (30 hours)
- AI-Native Software Engineering Academy (30 hours)
- AI Governance, Risk and Assurance Academy (30 hours)
- Data and AI Platform Engineering Academy (30 hours)
- Human Skills for the AI Era Academy (30 hours)
Hands-on Workshops 1 categories · 12 courses
Hands-on Workshops (12) →
- AI Use Case Discovery and Prioritization Workshop (12 hours)
- Prompt, Context and Workflow Design Lab (12 hours)
- From Idea to Working Product with No-Code and Low-Code (12 hours)
- Agentic Process Redesign Workshop (6 hours)
- Copilot Studio Agent Builder Day (12 hours)
- AI-Native Software Engineering Lab (18 hours)
- RAG and Enterprise Knowledge Assistant Lab (12 hours)
- AI Governance Tabletop Simulation (12 hours)
- Customer Feedback and Contact Center AI Workshop (6 hours)
- AI and Automation in Logistics and Last-Mile Operations (12 hours)
- KPI, Dashboard and Decision Visibility Workshop (6 hours)
- Human Skills Simulation Lab (12 hours)
Career Paths
Unsure where to start? Our Career Path programs combine multiple courses to prepare you for high-demand industry roles.
🎯 Data Scientist
Duration: 6 months | Level: Beginner-Intermediate
Become an expert in data analysis, machine learning, and statistical modeling. Master Python, SQL, ML algorithms, and data visualization tools.
Salary Range: 35.000₺ - 80.000₺
Inquire🤖 ML Engineer
Duration: 6-8 months | Level: Medium
Develop production-ready ML systems. Specialize in model training, optimization, deployment, and monitoring.
Salary Range: 40.000₺ - 90.000₺
Inquire👁️ Computer Vision Engineer
Duration: 5 months | Level: Medium-Advanced
Develop image processing, object detection, segmentation, and video analysis systems. Be an expert in OpenCV, TensorFlow, and PyTorch.
Salary Range: 45.000₺ - 100.000₺
Job Opportunities:High demand, particularly in autonomous vehicles and security
Inquire💬 NLP Engineer
Duration: 5 months | Level: Medium-Advanced
Develop language models, chatbots, and text analysis systems. Become an expert in Transformer models and Large Language Models (LLMs).
Salary Range: 45.000₺ - 110.000₺
Job Opportunities:Peak demand in the post-ChatGPT era
Inquire🚀 AI Product Manager
Duration: 4 months | Level: Medium
Design and manage AI products. Combine technical knowledge + business strategy + product management skills.
Salary Range: 50.000₺ - 120.000₺
Job Opportunities:Peak demand in the post-ChatGPT era
Inquire* Explore the catalog above to discover all career paths.
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