“The Microsoft Fabric implementation program gave our data engineering team a structured path from legacy pipelines to a modern lakehouse architecture.”
Enterprise Program Brief
Python, APIs and Git for AI Engineering
Build and test a small Python API client under version control. Proposed instructor-led duration; delivery subject to environment and lab validation.
VNode ITeSFoundation
Download Program Brief (PDF)Program Snapshot
Engagement scoped to cohort
Duration40 hours
FormatPrivate cohort
LevelFoundation
Course CodeF02
- MCT-led delivery
- Private cohort / virtual ILT
- Typical response: 1 business day
Scoping call typically scheduled within one business day
VNode ITeS delivers Python, APIs and Git for AI Engineering as an MCT-led VNode ITeS program for Technical professionals entering AI development. Typical duration is 40 hours (Private cohort). Delivery stays scoped to how your teams will actually use the platform after the room empties. Private cohorts can shift emphasis by role mix, workspace or repo constraints, and rollout timing.
Audience Profile
Built for these roles
Technical professionals entering AI development
- Tailored Team Delivery
Overview
Executive overview
Build and test a small Python API client under version control.
Environment and licensing
Supported Python version and isolated package environment Git and code editor Local mock API and synthetic data; optional approved model endpoint Delivery depends on environment and lab validation. This outline does not include step-by-step lab instructions.
Prerequisites
- Basic technical literacy
- First-time programmers require additional independent practice
Program Outcomes
Capabilities your teams will gain
- Implement a typed and validated Python API client
- Demonstrate pagination, timeout, invalid-input and retry tests
- Protect credentials and handle permission failures explicitly
- Provide a clean setup, Git history and understandable execution guide
Enterprise Delivery
Private cohort delivery
VNode-designed, vendor-aligned instructor-led program. Scope role mix, delivery format, and rollout goals for your cohort.
Curriculum
Curriculum roadmap
Proposed instructor-led duration; delivery subject to environment and lab validation.
- Python programming essentials
- Working with data and project environments
- HTTP and API integration
- Authentication, tests and Git
- Integration project and review
1Module 1 · 8 hours
Python programming essentials
+
Module 1 · 8 hours
Python programming essentials
Transform a request dataset and handle missing or invalid values.
Types and collections
- Choose strings, numbers and booleans for request fields
- Use lists and dictionaries for collections of records
Conditions and loops
- Apply branching to validation and routing
- Iterate through records without mutating source data unexpectedly
Functions
- Define functions with clear inputs and outputs
- Separate reusable transformations from program entry points
Exceptions and debugging
- Raise and handle specific exceptions
- Use a debugger to inspect invalid records
Concept and design 4h · applied exercise 3h · review 1h. Included within module duration; no extra hours. Refine during delivery planning without silently changing published course hours.
Applied exercise: Python programming essentials
Transform a request dataset and handle missing or invalid values.
Expected output. Validated Python transformation script
Acceptance. Transform valid records correctly and report malformed input without silent data loss.
2Module 2 · 8 hours
Working with data and project environments
+
Module 2 · 8 hours
Working with data and project environments
Create a reproducible project that reads and validates JSON inputs.
JSON and files
- Read and write UTF-8 JSON and CSV
- Handle missing files and malformed payloads
Packages and virtual environments
- Create isolated environments and install pinned packages
- Separate runtime and development dependencies
Configuration
- Read configuration from environment variables
- Keep secrets outside committed source
Type hints and logging
- Add type hints and input validation
- Use structured logging without sensitive payloads
Concept and design 4h · applied exercise 3h · review 1h. Included within module duration; no extra hours. Refine during delivery planning without silently changing published course hours.
Applied exercise: Working with data and project environments
Create a reproducible project that reads and validates JSON inputs.
Expected output. Reproducible project and validation examples
Acceptance. Run the project in a clean environment using its documented configuration.
3Module 3 · 8 hours
HTTP and API integration
+
Module 3 · 8 hours
HTTP and API integration
Build a client against an instructor-provided local mock service.
REST methods
- Map GET, POST, PATCH and DELETE to service operations
- Interpret response codes and request headers
Status codes
- Inspect JSON response structure and validation errors
- Handle empty and partial API results
Pagination
- Follow continuation tokens or page links
- Prevent duplicate processing across pages
Timeouts and bounded retries
- Set explicit timeouts and bounded retries
- Distinguish retryable errors from rejected requests
Concept and design 4h · applied exercise 3h · review 1h. Included within module duration; no extra hours. Refine during delivery planning without silently changing published course hours.
Applied exercise: HTTP and API integration
Build a client against an instructor-provided local mock service.
Expected output. API client and failure-handling evidence
Acceptance. Retrieve all mock-service pages and handle a simulated timeout within a retry limit.
4Module 4 · 8 hours
Authentication, tests and Git
+
Module 4 · 8 hours
Authentication, tests and Git
Test the API client without live credentials and review a change in Git.
Tokens and OAuth concepts
- Compare API keys, bearer tokens and OAuth flows
- Avoid committing credentials or printing tokens
Secrets outside source
- Write unit tests with controlled fixtures
- Mock responses for success, timeout and authorisation failure
Unit tests and mocks
- Stage and review changes in Git
- Use branches and meaningful commits
Branches and pull requests
- Review a pull request against acceptance criteria
- Resolve a simple conflict without discarding unrelated changes
Concept and design 4h · applied exercise 3h · review 1h. Included within module duration; no extra hours. Refine during delivery planning without silently changing published course hours.
Applied exercise: Authentication, tests and Git
Test the API client without live credentials and review a change in Git.
Expected output. Test suite and reviewable repository history
Acceptance. Pass isolated tests and demonstrate that repository history contains no credentials.
5Module 5 · 8 hours
Integration project and review
+
Module 5 · 8 hours
Integration project and review
Deliver a command-line client with tests, setup instructions and known limitations.
Project structure
- Organise client, configuration and validation modules
- Document a minimal execution command
Input contracts
- Enforce an input and output contract
- Return actionable errors with stable exit behaviour
Error reporting
- Include representative success and failure tests
- Document unsupported cases and rate-limit assumptions
Documentation and cleanup
- Review code and dependency choices
- Provide setup, operation and cleanup notes
Concept and design 2h · applied exercise 4h · review 2h. Included within module duration; no extra hours. Refine during delivery planning without silently changing published course hours.
Capstone: Integration project and review
Deliver a command-line client with tests, setup instructions and known limitations.
Expected output. Assessed Python API client repository
Acceptance. Run the client reproducibly and demonstrate normal, invalid-input and unavailable-service cases.
Capstone
Deliver a command-line client with tests, setup instructions and known limitations. Assessed Python API client repository Evidence of relevant access, quality and risk controls Demonstration and limitations record
Assessment
Scenario-based practical assessment Implement a typed and validated Python API client 30% Demonstrate pagination, timeout, invalid-input and retry tests 25% Protect credentials and handle permission failures explicitly 25% Provide a clean setup, Git history and understandable execution guide 20% Proposed VNode outline-level assessment; no vendor accreditation or completed lab validation implied.
Participant deliverables
- Assessed Python API client repository
- Evidence of relevant access, quality and risk controls
- Demonstration and limitations record
Scope boundaries
Step-by-step lab instructions; Runnable solution code; Packaged source datasets; Executed environment validation
Delivery options
Count teaching hours, not calendar days. Exclude breaks. Split into 4-hour or 8-hour teaching sessions; schedule complex project work in contiguous blocks.
Delivery Models
Delivery models
Virtual ILTOnsiteHybridExecutive WorkshopBootcampWeekend
Engagement Fit
Engagement fit
- Private cohort delivery
- Foundation practitioner depth
- Business outcome alignment
Enterprise Customization
Enterprise customization
Tailor this program to your organization's priorities: Build and test a small Python API client under version control.
- Private cohort scheduling
- Equivalent-experience entry review
Resources
Program resources
Yes. Most enterprise clients prefer private delivery scoped to role mix, timezone, and rollout timeline. We align lab environments and scenarios to your tenant context where applicable.
Enterprise Proof
Trusted delivery outcomes
“We needed a partner who understood both the technical depth of Azure OpenAI and the governance requirements of an enterprise.”
Banking & Finance
Representative Enterprise Banking Team
The focus was not just on tooling knowledge, but on helping teams work from a shared operating model as they adopted a more modern data platform.
- Clearer platform operating model across teams
- Improved confidence in modern data stack adoption
Healthcare
Representative Healthcare Product Team
The engagement helped product and engineering stakeholders move from interest in AI to clearer implementation choices, security expectations, and prototyping discipline.
- Stronger alignment between product and engineering teams
- Improved clarity on prototype-to-production requirements
Delivery Capability
Enterprise-grade instruction
MCT-led delivery
Programs led by Microsoft Certified Trainer practitioners
Enterprise program oversight
Founder-led specialist delivery with structured rollout planning
Global delivery
APAC · EMEA · Americas · Virtual & Onsite
Implementation-focused
Hands-on labs aligned to production scenarios
