Professional Programme · Build AI features a business can trust

AI Engineering

The route to building with generative AI professionally, not just using chatbots. Learn the Python and machine learning foundations, then build LLM features properly: prompts as specifications, validated outputs, retrieval with citations, evaluation against human labels, and the privacy, safety and cost controls that decide whether a feature can launch.

What you'll be able to do

Python and pandas for AI work
Machine learning evaluation: splits, recall and baselines
Prompt design, structured outputs and validation
Retrieval-augmented generation
Evaluating LLM outputs with people and judges
Privacy, prompt injection and cost control

CloudTech AI Engineer

Complete every required course and the capstone project to earn the free programme badge, then claim your official Professional Certificate.

Start with Python for Data Analytics

What you'll learn, module by module

Work through the modules in order. Open one to see exactly what it covers.

1Module 1FoundationThe Python and machine learning every AI engineer relies on.
Professional courseLevel 2 · Practical Skills
Python for Data Analytics
pandas for loading, cleaning and exploring the data AI features run on.
About 9 hours
You'll learn
- Python and Colab for Analysts
- Lists, Dictionaries, Loops and Functions
- DataFrames: Load and Explore
- Filtering and Sorting
- Calculated Columns and Dates
- Cleaning Messy Data
- groupby and Aggregation
- Merging Tables
- Pivot Tables and Trends
- Charts with pandas and matplotlib
- From Question to Insight
- Final Project
Professional courseLevel 2 · Practical Skills· Optional
Statistics for Data Analysis
Sampling and uncertainty, for reading evaluation results honestly.
About 8 hours
You'll learn
- Statistics for Analysts
- Averages: Mean, Median and Mode
- Spread: Range, IQR and Standard Deviation
- Distributions and Outliers
- Rates, Percentages and Weighted Averages
- Correlation
- Sampling and the Normal Distribution
- Confidence Intervals
- Comparing Groups
- Regression and Trends
- Final Project
Professional courseLevel 3 · Professional
Machine Learning Fundamentals
Train and test splits, baselines, recall and cost-based decisions.
About 9 hours
You'll learn
- What Machine Learning Is
- Preparing Data for a Model
- Train, Test and Baselines
- Linear Regression
- Trees, Forests and Overfitting
- Cross-validation and Tuning
- Classification and Logistic Regression
- Evaluating Classifiers and Choosing Thresholds
- Explaining Models and Responsible ML
- From Model to Decision
- Final Project
2Module 2CoreBuild LLM features properly.
Professional courseLevel 3 · Professional
Generative AI Engineering
Prompts, validation, retrieval, evaluation, safety and cost, on a mobile wallet's support assistant.
About 7 hours
You'll learn
- How Large Language Models Work
- Calling a Model from Code
- Prompts as Engineering
- Structured Outputs and Validation
- Evaluating an LLM Classifier
- Embeddings and Search
- Retrieval-Augmented Generation
- Evaluating Generated Answers
- Safety, Privacy and Cost
- Final Project
Professional courseLevel 3 · Professional· Optional
Feature Engineering and Model Evaluation
Calibration, drift and monitoring: the habits that keep models working after launch.
About 7 hours
You'll learn
- Features and Point-in-Time Thinking
- Features from Events
- Leakage Across Time
- Gradient Boosting and Model Comparison
- Calibration
- Lift and Targeting
- Drift and Retraining
- Final Project
3Module 3SpecialistGo further into AI systems.
Professional courseLevel 3 · Professional
AI Agents and Tool Use
Scoped tools, rules in code, guarded loops, approvals and injection defences, on a support agent's recorded runs.
About 7 hours
You'll learn
- From Chatbot to Agent
- Designing Tools
- The Agent Loop
- Rules in Code, Not Prompts
- Permissions and Approvals
- Evaluating Agents
- Injection Through Tools
- Cost, Latency and Limits
- Monitoring Agents in Production
- Final Project
Professional courseLevel 3 · Professional
LLM Evaluation and Safety in Production
Release gates, red-teaming, fair guardrails, alerts and incident response for a live assistant.
About 7 hours
You'll learn
- Production Is Different
- Building a Regression Suite
- Comparing Releases
- Release Gates
- Red-Teaming
- Guardrails and Thresholds
- Monitoring with Control Limits
- Feedback and Sampled Grading
- Incident Response
- Final Project
4Module 4CapstoneOne LLM feature from design to production, as a portfolio piece.
CapstoneLevel 4 · Career Projects
AI Engineer Capstone: From Prototype to Production
Build, evaluate, gate and monitor an insurer's WhatsApp claims assistant, in English and Pidgin.
About 12 hours
You'll learn
- The Brief and the Design
- Extraction and Validation
- Rules in Code
- Retrieval over the Policy
- Grounded Answers and Judging
- Red-Teaming and Fair Guardrails
- Cost, Latency and the Release Gate
- Launch, Monitoring and the Presentation
5Module 5CareerTurn your skills into applications that get interviews.
Short courseLevel 1 · Foundations
Career Essentials
An ATS-friendly CV and a LinkedIn profile recruiters can find.
1 hr 30 min
You'll learn
- Build a CV with AI
- A Professional LinkedIn Profile
- Quick Excel Analysis
Short courseLevel 1 · Foundations· Optional
Build Your Student Portfolio
One link that shows your notebooks and evaluation reports.
1 hr 25 min
You'll learn
- Plan Your Portfolio
- Show Your Work
- Build Your Portfolio Page
- Share Your Work on LinkedIn

Courses marked "In preparation" join the programme when they're ready. If you've already earned the programme badge by then, you keep it.

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AI Engineering

What you'll be able to do

Python and pandas for AI work
Machine learning evaluation: splits, recall and baselines
Prompt design, structured outputs and validation
Retrieval-augmented generation
Evaluating LLM outputs with people and judges
Privacy, prompt injection and cost control

CloudTech AI Engineer

Complete every required course and the capstone project to earn the free programme badge, then claim your official Professional Certificate.

Start with Python for Data Analytics

What you'll learn, module by module

Work through the modules in order. Open one to see exactly what it covers.

1Module 1FoundationThe Python and machine learning every AI engineer relies on.

Professional courseLevel 2 · Practical Skills

Python for Data Analytics

pandas for loading, cleaning and exploring the data AI features run on.

About 9 hours

You'll learn

Python and Colab for Analysts
Lists, Dictionaries, Loops and Functions
DataFrames: Load and Explore
Filtering and Sorting
Calculated Columns and Dates
Cleaning Messy Data
groupby and Aggregation
Merging Tables
Pivot Tables and Trends
Charts with pandas and matplotlib
From Question to Insight
Final Project

Professional courseLevel 2 · Practical Skills· Optional

Statistics for Data Analysis

Sampling and uncertainty, for reading evaluation results honestly.

About 8 hours

You'll learn

Statistics for Analysts
Averages: Mean, Median and Mode
Spread: Range, IQR and Standard Deviation
Distributions and Outliers
Rates, Percentages and Weighted Averages
Correlation
Sampling and the Normal Distribution
Confidence Intervals
Comparing Groups
Regression and Trends
Final Project

Professional courseLevel 3 · Professional

Machine Learning Fundamentals

Train and test splits, baselines, recall and cost-based decisions.

About 9 hours

You'll learn

What Machine Learning Is
Preparing Data for a Model
Train, Test and Baselines
Linear Regression
Trees, Forests and Overfitting
Cross-validation and Tuning
Classification and Logistic Regression
Evaluating Classifiers and Choosing Thresholds
Explaining Models and Responsible ML
From Model to Decision
Final Project

2Module 2CoreBuild LLM features properly.

Professional courseLevel 3 · Professional

Generative AI Engineering

Prompts, validation, retrieval, evaluation, safety and cost, on a mobile wallet's support assistant.

About 7 hours

You'll learn

How Large Language Models Work
Calling a Model from Code
Prompts as Engineering
Structured Outputs and Validation
Evaluating an LLM Classifier
Embeddings and Search
Retrieval-Augmented Generation
Evaluating Generated Answers
Safety, Privacy and Cost
Final Project

Professional courseLevel 3 · Professional· Optional

Feature Engineering and Model Evaluation

Calibration, drift and monitoring: the habits that keep models working after launch.

About 7 hours

You'll learn

Features and Point-in-Time Thinking
Features from Events
Leakage Across Time
Gradient Boosting and Model Comparison
Calibration
Lift and Targeting
Drift and Retraining
Final Project

3Module 3SpecialistGo further into AI systems.

Professional courseLevel 3 · Professional

AI Agents and Tool Use

Scoped tools, rules in code, guarded loops, approvals and injection defences, on a support agent's recorded runs.

About 7 hours

You'll learn

From Chatbot to Agent
Designing Tools
The Agent Loop
Rules in Code, Not Prompts
Permissions and Approvals
Evaluating Agents
Injection Through Tools
Cost, Latency and Limits
Monitoring Agents in Production
Final Project

Professional courseLevel 3 · Professional

LLM Evaluation and Safety in Production

Release gates, red-teaming, fair guardrails, alerts and incident response for a live assistant.

About 7 hours

You'll learn

Production Is Different
Building a Regression Suite
Comparing Releases
Release Gates
Red-Teaming
Guardrails and Thresholds
Monitoring with Control Limits
Feedback and Sampled Grading
Incident Response
Final Project

4Module 4CapstoneOne LLM feature from design to production, as a portfolio piece.

CapstoneLevel 4 · Career Projects

AI Engineer Capstone: From Prototype to Production

Build, evaluate, gate and monitor an insurer's WhatsApp claims assistant, in English and Pidgin.

About 12 hours

You'll learn

The Brief and the Design
Extraction and Validation
Rules in Code
Retrieval over the Policy
Grounded Answers and Judging
Red-Teaming and Fair Guardrails
Cost, Latency and the Release Gate
Launch, Monitoring and the Presentation

5Module 5CareerTurn your skills into applications that get interviews.

Short courseLevel 1 · Foundations

Career Essentials

An ATS-friendly CV and a LinkedIn profile recruiters can find.

1 hr 30 min

You'll learn

Build a CV with AI
A Professional LinkedIn Profile
Quick Excel Analysis

Short courseLevel 1 · Foundations· Optional

Build Your Student Portfolio

One link that shows your notebooks and evaluation reports.

1 hr 25 min

You'll learn

Plan Your Portfolio
Show Your Work
Build Your Portfolio Page
Share Your Work on LinkedIn

Courses marked "In preparation" join the programme when they're ready. If you've already earned the programme badge by then, you keep it.