Corporate Training for Engineering Teams
Custom corporate training in cloud, DevOps, AI/GenAI, data engineering, and full-stack development — scoped to your team's stack and shipped on your timeline.
About this program
beCloudReady designs and delivers custom corporate training programs for engineering, data, and platform teams at growth-stage and enterprise companies. With 200+ training programs delivered over 6+ years, we maintain a deep, battle-tested catalog across AWS, Azure, Google Cloud, Kubernetes, Terraform, Docker, CI/CD, Site Reliability Engineering, GenAI tooling (Claude, ChatGPT, GitHub Copilot, Microsoft Copilot, Cursor, LangChain, LangGraph, vLLM, MCP), data engineering (Snowflake, Databricks, Spark, Kafka, dbt, Airflow), full-stack development (Python, Java, JavaScript, TypeScript, React, GraphQL), security (DevSecOps, application security), test automation, and emerging technologies. Every engagement starts with a scoping call to map your team's current skills against the stack you're moving toward — then we assemble the modules, format, and delivery cadence that fits. Live online for distributed teams, on-site for focused intensives, or hybrid for the best of both.
- 200+ corporate training programs delivered across cloud, AI/GenAI, DevOps, data, and software engineering
- Hands-on labs run in real environments — AWS, Azure, Databricks, Kubernetes — not slideware demos
- Optional AI-tools acceleration: Claude Code, GitHub Copilot, Cursor, Microsoft Copilot, ChatGPT integrated into every track
- Custom curriculum scoped to your tech stack, team's current skill level, and target competencies
- Flexible formats: 1-day workshop, weekend intensive, week-long bootcamp, or 4–16 week cohort
- On-site, hybrid, or fully remote — delivered across North America, EMEA, and APAC time zones
- Lab artefacts, code, and curriculum retained by your team for ongoing self-service
- Certification-aligned tracks for AWS, Azure, Kubernetes (CKA/CKAD/CKS), Terraform, and Databricks
Skills covered
AI Tools You'll Master
What you'll achieve
- Measurable skill uplift across the engineering team — verified through hands-on labs and capstone projects
- Faster onboarding for new hires and reduced ramp-up time on new tech stacks
- Reduced dependency on external contractors for cloud, DevOps, data, and AI work
- Team-wide adoption of AI-assisted development practices (Claude Code, GitHub Copilot, Cursor)
- Production-ready capstone deliverables aligned to your real-world scenarios
- Curriculum, lab repos, and project artefacts retained as ongoing reference material
- Engineers ready to sit relevant certification exams (AWS, Azure, CKA, Terraform Associate, Databricks)
Curriculum
Cloud Platforms
- AWS — EC2, VPC, IAM, S3, RDS, EKS, Lambda, CloudFormation, AWS CDK
- Microsoft Azure — AKS, Azure DevOps, Azure Observability
- Google Cloud Platform fundamentals and GKE
- Private cloud — OpenStack, Nutanix
- Multi-cloud architecture, cost optimisation, and FinOps
- Certification prep: AWS SA Associate, AWS DevOps Pro, Azure AZ-400
DevOps, Platform Engineering & SRE
- Docker, Kubernetes (EKS / AKS / GKE), Helm, Argo CD, GitOps
- Terraform, Ansible, Pulumi — Infrastructure as Code
- Jenkins, GitHub Actions, GitLab CI — CI/CD pipelines
- Site Reliability Engineering — SLOs, error budgets, incident response
- Observability — Prometheus, Grafana, OpenTelemetry, Datadog, Dynatrace
- Linux administration, Bash scripting, systemd
- Microservices architecture and service mesh (Istio)
- Certification prep: CKA, CKAD, CKS, Terraform Associate
AI, GenAI & Agentic Engineering
- Claude Code, GitHub Copilot, Cursor — AI-assisted development for engineers
- Microsoft Copilot and Copilot Studio — for business, finance, and citizen developers
- Agentic coding with MCP (Model Context Protocol) and LLM guardrails
- LLMOps and AI Platform Engineering — production patterns for AI agents
- RAG, vector databases, LangChain, LangGraph, LlamaIndex
- vLLM inferencing on GPU infrastructure
- Snowflake Cortex AI and Databricks Mosaic AI
- Machine learning and computer vision with Python
Data Engineering & Analytics
- Snowflake — Lakehouse, Cortex AI, Data Engineering
- Databricks — Delta Lake, Unity Catalog, Lakeflow, AI/BI Genie
- Apache Spark, PySpark, dbt, Apache Airflow
- Apache Kafka, Apache NiFi — streaming and ETL
- PostgreSQL, Elasticsearch, MongoDB, Redis, Hadoop, Greenplum
- Tableau and Power BI — dashboard development and self-serve analytics
- SQL foundational, intermediate, and advanced
- Data warehousing patterns and dimensional modelling
Programming & Full-Stack Development
- Python, Java, JavaScript, TypeScript, Go, C++, C#/.NET, PHP
- React, Next.js, GraphQL, REST APIs, HTML5
- Android and iOS mobile development
- Microservices, Design Patterns, Clean Code practices
- API design and developer experience
- Fullstack programs combining backend, frontend, cloud, and DevOps
Security, DevSecOps & Application Security
- OWASP Top 10 and application security fundamentals
- DevSecOps pipeline integration and shift-left security
- Secure coding practices in Python and Java
- Container and Kubernetes security (CKS curriculum)
- IaC security scanning (Trivy, Checkov)
- Threat modelling and security architecture review
Test Automation & Quality Engineering
- Software Development Engineer in Test (SDET) curriculum
- Selenium with Java and Python
- Robot Framework — keyword-driven automation
- API testing and contract testing
- Performance testing fundamentals
Telecom, RPA & Emerging Technology
- 5G architecture and principles
- RAN, RF engineering, RF analytics with AI/ML
- Robotic Process Automation — Blue Prism, Automation Anywhere
- Blockchain fundamentals
- IoT architecture and platforms
- Solace PubSub+ event-driven messaging
Agile, Scrum & Engineering Practices
- Certified Scrum Developer (CSD) workshop
- Business Agility Foundation and Business Value Analysis
- Business Analysis in Agile Projects (ICP-BVA)
- Design Thinking bootcamp
- Engineering team practices — code review, pairing, on-call
Who should join
- Engineering managers, directors, VPs of Engineering, and CTOs scoping team upskilling
- Platform engineering, infrastructure, and SRE teams adopting Kubernetes, Terraform, or GitOps
- Data engineering, analytics, and AI/ML teams adopting Databricks, Snowflake, or LLMOps
- Software engineering teams adopting cloud-native or AI-assisted development workflows
- L&D and HR business partners rolling out company-wide technical upskilling programs
- Hiring managers running graduate or campus-hire onboarding cohorts
- Consulting firms building staff augmentation talent pipelines
Frequently asked questions
What does a typical corporate training engagement look like?
We start with a 30-minute scoping call to understand your team's current skills, the stack you're moving toward, and the timeline. Based on that, we propose a custom curriculum (1-day workshop, week-long bootcamp, or multi-week cohort), agree on dates, and deliver instructor-led training with hands-on labs. Every engagement includes a post-program review and lab artefacts retained by your team.
Can you deliver on-site, or only live online?
Both. We've delivered on-site programs across North America and EMEA, and we run fully remote cohorts globally. Hybrid (a few key days on-site, the rest live online) works well for distributed teams that want a kickoff in person.
Do you customise the curriculum to our tech stack?
Yes — that's the entire point of corporate engagements. Our catalog spans 200+ programs covering AWS, Azure, GCP, Kubernetes, Terraform, Docker, Snowflake, Databricks, Apache Spark, Python, Java, JavaScript, GenAI tooling, and more. We assemble the modules your team actually needs rather than shipping a fixed shrink-wrapped course.
How long does it take to roll out a program?
Typical lead time is 2–4 weeks from scoping call to Day 1, depending on customisation depth. Workshops on existing curriculum (e.g. a 1-day Claude Code workshop or AWS Core workshop) can be scheduled in under a week.
Do you integrate AI tools into the training?
Yes. Engineering tracks include hands-on use of Claude Code, GitHub Copilot, and Cursor. Business-track programs use Microsoft Copilot and Copilot Studio. We teach your team how to use these tools responsibly and productively in real workflows — not just demo them.
Do you provide certifications or completion credentials?
We issue beCloudReady completion certificates listing the specific tools and competencies covered. For certification-aligned tracks (AWS SA Associate, AWS DevOps Pro, CKA, CKAD, Terraform Associate, Databricks Spark Associate, Azure AZ-400) we map the curriculum to the official exam objectives so participants are exam-ready after the program.
What's the typical group size?
Sweet spot is 8–25 engineers per cohort for maximum hands-on time. We can scale up to 50+ with teaching assistants, or run smaller (3–8) executive workshops for engineering leadership teams.
How do you measure outcomes?
Through hands-on labs and capstone projects scored against pre-agreed competencies, plus a pre/post skills assessment if your L&D team wants quantitative metrics. Capstones and lab repos remain with the company as permanent reference material.
Do you offer training for non-engineering teams?
Yes. We run Microsoft Copilot and Copilot Studio programs for business analysts, finance teams, marketing teams, and citizen developers. We also offer Tableau, Power BI, SQL, and Excel/PowerPoint productivity tracks for analyst roles.
What languages do you deliver in?
We support English and Spanish delivery.
Apply or enquire
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