1:1 personal tutoring
Learn directly from industry experts in 1:1 sessions. Highly personalized paths starting from tech roots up to advanced AI Agentic workflows and MCP architectures.
Available mentorship courses
Select the course that matches your skill level and professional objectives.
Course 0: Full Stack Web with .NET 10 & Angular
10 - 12 sessions (20 - 24 hours)
Developers wanting to master the enterprise .NET + Angular stack from basic setup to high-performance advanced features on any OS (Windows/macOS).
- Module 1: Enterprise backend with .NET 10
- Module 2: High-performance frontend with Angular
- Module 3: Cross-platform deployment & Docker
Course 1: System Architecture (SA) foundations
4 sessions (8 - 10 hours)
Aspiring Tech Leads and Senior Developers looking to master Microservices design, Multi-Tenant architectures, and service discovery load balancing with Consul.
- Module 1: Microservices & Multi-Tenant foundations
- Module 2: Service discovery & load balancing with Consul
- Module 3: SaaS enterprise resilience
Course 2: DevOps foundations
4 sessions (8 hours)
Developers wanting to learn modern infrastructure, containerization, web server configurations, and automated deployments.
- Module 1: Containerization with Docker
- Module 2: Web server configuration & SSL
- Module 3: Automated CI/CD pipelines
Course 3: AI for IT professionals
4 sessions (8 - 10 hours)
Experienced coders wishing to integrate AI deep into their workspace, build custom MCP servers, and host local models offline.
- Module 1: Terminal Agents & AI CLI
- Module 2: Model Context Protocol (MCP) setup
- Module 3: Self-hosted local AI
Course 4: Advanced Vibe coding & agentic workflows
4 sessions (8 hours)
Tech leads and architects wanting to master Context & Harness Engineering, write custom Agent SKILLs, and build self-healing automation loops.
- Module 1: Context engineering & planning mindset
- Module 2: Custom agent SKILLs & troubleshooting mindset
- Module 3: Harness engineering & self-healing loops
Course 5: Vibe coding & rapid prototyping
3 sessions (6 hours)
Non-tech individuals, PMs, and beginners wanting to configure AI IDE workspaces, learn Prompt Engineering, and deploy real SaaS MVPs with custom domains.
- Module 1: Environment & AI IDE setup
- Module 2: Foundational prompt engineering
- Module 3: Custom domains & production deploy
Course 6: AI productivity in the workplace
3 sessions (6 hours)
Office employees, HR, Marketing, Sales, and managers seeking to leverage standard AI tools to automate office workflows and document processing.
- Module 1: Advanced prompting & document analysis
- Module 2: Multi-channel customer chatbots
- Module 3: Office automation & app integrations
Course 7: Python for data science & automation
5 sessions (10 hours)
Analysts, PMs, BAs, and operations managers wanting to learn Python for big data analysis, automated reporting, and web scraping.
- Module 1: Python basics & Pandas DataFrames
- Module 2: Data visualization & interactive dashboards
- Module 3: Web scraping & automated tasks
Course 8: Applying AI for Business Analysts (BA)
6 live sessions (15.5 hours) + 4 hours self-study
Business Analysts (IT BAs), Product Owners (POs), and Product Managers (PMs) looking to apply AI effectively to automate wireframing, document drafting (SRS/PRD), diagrams, and maximize productivity.
- Module 1: AI Era BA Mindset & Foundations
- Module 2: AI Requirements Elicitation & Automated Diagrams
- Module 3: AI Document Generation & Change Management (CR)
- +1 more module(s)
Course 9: AI for QC & Automation Testing
6 live sessions (15 hours) + 4 hours self-study
Testers, Quality Control (QC) analysts, and Automation Test Engineers wanting to leverage AI to generate test cases, write automated scripts, and optimize software testing workflows.
- Module 1: AI & Modern Testing Mindset
- Module 2: Automated Test Case & Data Generation
- Module 3: AI Copilots for Automation Scripting
- +1 more module(s)
Course 10: Advanced DevOps & Kubernetes
5 sessions (10 - 12 hours)
DevOps engineers and backend developers who already know Docker/CI-CD basics and want to run production-grade Kubernetes clusters, infrastructure as code, and full observability stacks.
- Module 1: Kubernetes in production
- Module 2: Infrastructure as Code with Terraform
- Module 3: GitOps & progressive delivery
- +1 more module(s)
Course 11: MLOps foundations
4 sessions (8 hours)
Data scientists and backend developers wanting to move machine learning models from a notebook into a reliable, versioned, and monitored production pipeline.
- Module 1: Experiment tracking & model versioning
- Module 2: Packaging & serving models
- Module 3: CI/CD for ML pipelines
- +1 more module(s)
Target audience
Developers wanting to master the enterprise .NET + Angular stack from basic setup to high-performance advanced features on any OS (Windows/macOS).
Detailed modules
Module 1: Enterprise backend with .NET 10
Minimal APIs, Entity Framework Core, SQL Server/Postgres, secure JWT authentication & Role-based authorization. Leveraging Copilot to generate boilerplate 3x faster.
Module 2: High-performance frontend with Angular
Standalone components, Reactive Forms, HttpClient API integration, Route Guards, state management, and modern Tailwind CSS setup. Custom prompt crafting for UI components.
Module 3: Cross-platform deployment & Docker
Multi-stage Dockerfiles for Angular & .NET, docker-compose configuration, volume persistence, internal network bridging, and deploy-readiness for VPS.
Graduation project
A complete Web Application system (Dashboard/E-commerce) containerized and ready to deploy on any VPS.
Target audience
Aspiring Tech Leads and Senior Developers looking to master Microservices design, Multi-Tenant architectures, and service discovery load balancing with Consul.
Detailed modules
Module 1: Microservices & Multi-Tenant foundations
Transitioning from Monolith to Microservices, service boundary mapping, and designing robust Multi-Tenant databases (isolated database-per-tenant, schema-per-tenant, and shared databases).
Module 2: Service discovery & load balancing with Consul
Installing and configuring HashiCorp Consul for automatic Service Discovery, dynamic load balancing, health checks, and secure microservice network communications.
Module 3: SaaS enterprise resilience
Implementing circuit breakers, API Gateway routing, dynamic reverse proxies, token bucket rate limiting, and robust failover architectures in production.
Graduation project
A complete multi-tenant microservices architecture model using HashiCorp Consul for service discovery and dynamic routing.
Target audience
Developers wanting to learn modern infrastructure, containerization, web server configurations, and automated deployments.
Detailed modules
Module 1: Containerization with Docker
Writing efficient Dockerfiles, optimizing image sizes, multi-stage builds, docker-compose orchestration, volume mounts, and network bridges.
Module 2: Web server configuration & SSL
Setting up Nginx as a reverse proxy, configuring gzip compression, routing static vs dynamic assets, and automated Let's Encrypt SSL certificate generation.
Module 3: Automated CI/CD pipelines
Creating GitHub Actions workflows, running automated unit tests, building Docker images, pushing to Docker Hub, and triggering secure SSH auto-deployments.
Graduation project
A fully automated CI/CD pipeline that automatically builds, tests, and deploys a web application to a VPS upon git push.
Target audience
Experienced coders wishing to integrate AI deep into their workspace, build custom MCP servers, and host local models offline.
Detailed modules
Module 1: Terminal Agents & AI CLI
Mastering Claude Code, Aider, and GitHub Copilot Workspace directly inside the shell for automated code generation, refactoring, and test fixes.
Module 2: Model Context Protocol (MCP) setup
Deep integration with local systems. Writing custom MCP Servers in Node.js/Python to securely bridge LLMs with internal databases and filesystems.
Module 3: Self-hosted local AI
Setting up Ollama to run DeepSeek-R1, Llama-3, or Qwen models locally for offline code review, security assessments, and prompt fine-tuning.
Graduation project
A custom Model Context Protocol (MCP) server allowing an AI agent to securely query and inspect a local enterprise SQL database.
Target audience
Tech leads and architects wanting to master Context & Harness Engineering, write custom Agent SKILLs, and build self-healing automation loops.
Detailed modules
Module 1: Context engineering & planning mindset
Standardizing project plans and step-by-step code execution. Sifting, sanitizing, and compressing large codebases to fit inside the AI's Context Window without information dilution.
Module 2: Custom agent SKILLs & troubleshooting mindset
Developing a deep mindset for AI collaboration and debugging. Writing custom AI agent SKILL files (.json / .md specifications) to automate multi-file refactoring tasks and run custom tool commands.
Module 3: Harness engineering & self-healing loops
Building a fully automated closed-loop pipeline: Gather codebase errors => Act (AI parses context and implements code fixes) => Verify (run automated test harness). Triggering self-healing agent loops.
Graduation project
An automated multi-agent code refactoring harness that reads codebase logs, writes bug fixes using custom SKILL specifications, tests them, and commits to Git.
Target audience
Non-tech individuals, PMs, and beginners wanting to configure AI IDE workspaces, learn Prompt Engineering, and deploy real SaaS MVPs with custom domains.
Detailed modules
Module 1: Environment & AI IDE setup
Installing and configuring AI CLI tools, optimizing modern IDE environments (VS Code, Cursor, Windsurf) and preparing workspaces for natural language code collaboration.
Module 2: Foundational prompt engineering
Mastering the basic Level 1 Prompt Engineering: setting clear Roles, providing rich context, providing detailed step instructions, and enforcing strict format restraints for reliable AI replies.
Module 3: Custom domains & production deploy
Guide to purchasing custom web domains, configuring Git repositories, setting up environment variables on Vercel/Netlify/Supabase, pushing code, and mapping live domains.
Graduation project
A fully functional React/TypeScript SaaS MVP built entirely using Vibe Coding methods, mapped to a custom domain, and deployed live to production.
Target audience
Office employees, HR, Marketing, Sales, and managers seeking to leverage standard AI tools to automate office workflows and document processing.
Detailed modules
Module 1: Advanced prompting & document analysis
Designing customized GPTs, analyzing long PDF financial reports, generating meeting summaries, and automating professional email templates.
Module 2: Multi-channel customer chatbots
Building no-code Zalo, Slack, or Telegram customer support bots connected directly to OpenAI/Claude APIs for automated customer queries.
Module 3: Office automation & app integrations
Connecting ChatGPT/Claude with Gmail, Google Docs, and Google Sheets using automated no-code workflows to parse and report daily tasks.
Graduation project
A customized multi-channel AI customer assistant bot linked with Google Sheets for tracking and classifying client inquiries.
Target audience
Analysts, PMs, BAs, and operations managers wanting to learn Python for big data analysis, automated reporting, and web scraping.
Detailed modules
Module 1: Python basics & Pandas DataFrames
Core syntax, variables, loops, writing custom functions, and manipulating tabular CSV/Excel datasets using Pandas & NumPy.
Module 2: Data visualization & interactive dashboards
Designing interactive web apps with Streamlit, rendering interactive plots with Plotly, and automating monthly Excel reports.
Module 3: Web scraping & automated tasks
Extracting data from public HTML pages, making HTTP API requests, scheduling regular execution scripts, and piping outputs.
Graduation project
An interactive Streamlit sales dashboard that automatically scrapes raw data, processes operational KPIs, and generates Excel reports.
Target audience
Business Analysts (IT BAs), Product Owners (POs), and Product Managers (PMs) looking to apply AI effectively to automate wireframing, document drafting (SRS/PRD), diagrams, and maximize productivity.
Detailed modules
Module 1: AI Era BA Mindset & Foundations
Reset BA thinking in the AI era (from Executor to Orchestrator). Distinguish tasks for AI vs humans. Master Large Language Models (GPT, Claude, Gemini, DeepSeek), token limits, context, and RAG.
Module 2: AI Requirements Elicitation & Automated Diagrams
Turn meeting notes and audio transcripts into solid requirement scopes. Auto-generate Use Cases, Flowcharts, Sequence, and ERD diagrams using Mermaid or PlantUML.
Module 3: AI Document Generation & Change Management (CR)
Build dedicated skills and assistants to draft URD, BRD, PRD, and SRS documents. Establish multi-agent peer review systems to automatically keep all documents synced during CR updates.
Module 4: Wireframes, UI & Automated Testcases
Convert text requirements into working UI prototypes (Lovable, Stitch, Figma MCP). Auto-generate checklists, test suites, and Playwright E2E automation scripts.
Graduation project
A personalized, end-to-end AI-powered BA System that automates brainstorming, design drafting, UI rendering, documentation, and task synchronization.
Target audience
Testers, Quality Control (QC) analysts, and Automation Test Engineers wanting to leverage AI to generate test cases, write automated scripts, and optimize software testing workflows.
Detailed modules
Module 1: AI & Modern Testing Mindset
Use AI to analyze PRD/SRS documents, generate test checklists, and identify boundary values or edge cases.
Module 2: Automated Test Case & Data Generation
Utilize LLMs to craft diverse mock test datasets and draft detailed test cases aligned with complex user stories.
Module 3: AI Copilots for Automation Scripting
Employ AI assistants to write automated scripts in Playwright, Cypress, Selenium, or Appium. Accelerate Page Object Model (POM) design.
Module 4: Log Analysis & Automated Reporting
Analyze error logs and debug stack traces using AI, classify bugs, propose fixes, and generate visual test reports.
Graduation project
An AI-optimized End-to-End (E2E) Test Suite that auto-generates test data, executes Playwright/Cypress scripts, and produces automated bug reports.
Target audience
DevOps engineers and backend developers who already know Docker/CI-CD basics and want to run production-grade Kubernetes clusters, infrastructure as code, and full observability stacks.
Detailed modules
Module 1: Kubernetes in production
Deploying to K8s (Deployments, Services, Ingress, ConfigMaps/Secrets), Helm charts, rolling updates, and horizontal pod autoscaling on a real cluster (k3s/EKS/GKE).
Module 2: Infrastructure as Code with Terraform
Provisioning cloud infrastructure declaratively, managing state, modules, and multi-environment (staging/prod) workspaces.
Module 3: GitOps & progressive delivery
ArgoCD/Flux GitOps pipelines, blue-green and canary rollout strategies, and automated rollback on failed health checks.
Module 4: Observability stack
Prometheus + Grafana metrics, centralized logging with Loki/ELK, alerting rules, and on-call incident runbooks.
Graduation project
A self-healing Kubernetes deployment with GitOps-driven rollouts, full Prometheus/Grafana observability, and infrastructure fully defined in Terraform.
Target audience
Data scientists and backend developers wanting to move machine learning models from a notebook into a reliable, versioned, and monitored production pipeline.
Detailed modules
Module 1: Experiment tracking & model versioning
Logging training runs, metrics, and artifacts with MLflow, and structuring a reproducible model registry.
Module 2: Packaging & serving models
Wrapping a trained model behind a FastAPI/BentoML inference service, containerizing it with Docker, and exposing a versioned REST/gRPC endpoint.
Module 3: CI/CD for ML pipelines
Automating retraining and evaluation gates in GitHub Actions, promoting models between staging and production registries.
Module 4: Monitoring model drift
Tracking prediction quality, data drift, and latency in production, and setting up alerts before a model silently degrades.
Graduation project
A containerized model-serving API with MLflow-tracked experiments, an automated retraining pipeline, and basic drift monitoring in production.
Tutoring path combos
Bundle courses together to optimize your learning investment and fast-track your career.
Combo 1: Comprehensive Software Engineer path
Go from developer to full autonomy, with the ability to design (System Architecture), code (Full Stack), and deploy (DevOps) a complete production system to VPS/Cloud.
Combo 2: Practical AI & automation engineer
A high-performance path for developers who want to master CLI AI agents, Advisor Strategy, Model Context Protocol (MCP) servers, and build advanced agentic systems.
Combo 3: Operations optimization path
Directly solve operational data analysis problems, build automated reports with Python Science, and apply AI tools (Zalo Chatbot, doc summaries) to streamline non-tech workflows.
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