The course lists are a draft for CARDTP's approval and may change slightly before the programme starts. Course availability is subject to confirmation within the programme's Coursera licence.
| Pathway | Hours over 12 months | Hours a week | What you earn |
|---|---|---|---|
| Full-Stack Software Engineering | 294–309 | 6.1–6.4 | Course certificates; optional IBM Full Stack certificate (Python track) |
| Cloud & DevOps Engineering | 313–314 | 6.5 | Course certificates; prepares for an AWS, Azure or Google Cloud exam |
| Data & AI Engineering | 306–311 | 6.4–6.5 | Course certificates; optional Machine Learning Specialization |
| Cybersecurity | 325 | 6.8 | Google Cybersecurity Professional Certificate |
| Product Management | 277 | 5.8 | IBM Product Manager Professional Certificate |
| Programme & Project Management (Agile) | 281 | 5.9 | Google Project Management Professional Certificate |
| Enterprise Architecture (Data & Security) | 284–298 | 5.9–6.2 | IBM Systems and Solutions Architect Professional Certificate |
What every learner takes
Whichever pathway you choose, you also take:
Hours are the course providers' estimates. Weekly figures spread the total over 48 weeks of the 12 months, which leaves time for orientation, holidays and catching up. We ask every learner for about 6.5 hours of study a week.
Full-Stack Software Engineering
Young people and career changers who want to build software, and learners continuing from the pilot Full Stack pathway.
You'll learn to build and test web applications end to end (front end, back end and database), work in Agile teams with Git, GitHub and GitLab, package and deploy applications in containers, and write secure code. The courses are built on courses from IBM's Full Stack Software Developer Professional Certificate, with Go from UC Irvine.
- Time
- About 294–309 hours over 12 months (about 6.1–6.4 hours a week), depending on your track.
- Entry
- Basic computer skills. The Python and JavaScript / TypeScript tracks need no programming experience; the Go track needs some.
- You'll earn
- A Coursera certificate for each course. On the Python track, if you are on or ahead of plan at Month 6, you can add 6 courses (about 88 hours) to complete the IBM Full Stack Software Developer Professional Certificate.
- Check-ins
- A 60-minute online check-in every two weeks with your Pathway Lead and a small group of learners.
- In the team project
- You build the application: front end and back end.
| Course | Provider | Hours |
|---|---|---|
| API Design and Fundamentals of Google Cloud's Apigee API Platform | Google Cloud | 7 |
| Postman Tutorial: Getting Started with API Testing | Packt | 6 |
| API Testing a real web application via Postman (guided project) | Coursera | 2 |
| Getting Started with Git and GitHub | IBM | 11 |
| Git with GitLab and BitBucket | LearnKartS | 2 |
| Introduction to Agile Development and Scrum | IBM | 13 |
| Agile with Atlassian Jira | Atlassian | 10 |
| Introduction to Software Engineering | IBM | 15 |
| Introduction to HTML, CSS, & JavaScript | IBM | 15 |
| Developing Front-End Apps with React | IBM | 16 |
| Introduction to Relational Databases (RDBMS) | IBM | 16 |
| Introduction to Test and Behavior Driven Development | IBM | 21 |
| Introduction to Cloud Computing | IBM | 12 |
| Introduction to Containers w/ Docker, Kubernetes & OpenShift | IBM | 17 |
| CI/CD with GitLab: Automating DevOps Pipelines | Coursera | 4 |
| OWASP Web Application Security | Edureka | 7 |
| 16 courses | 174 | |
Python track: 3 more courses, 52 hours (309 hours in all)
| Course | Provider | Hours |
|---|---|---|
| Python for Data Science, AI & Development | IBM | 24 |
| Developing AI Applications with Python and Flask | IBM | 13 |
| Django Application Development with SQL and Databases | IBM | 15 |
| 3 courses | 52 | |
JavaScript / TypeScript track: 3 more courses, 37 hours (294 hours in all)
| Course | Provider | Hours |
|---|---|---|
| JavaScript Programming Essentials | IBM | 18 |
| Learn TypeScript | Scrimba | 5 |
| Developing Back-End Apps with Node.js and Express | IBM | 14 |
| 3 courses | 37 | |
Go track: 4 more courses, 40 hours (297 hours in all)
| Course | Provider | Hours |
|---|---|---|
| Getting Started with Go | UC Irvine | 10 |
| Functions, Methods, and Interfaces in Go | UC Irvine | 11 |
| Concurrency in Go | UC Irvine | 10 |
| Building Microservices API in Go | Packt | 9 |
| 4 courses | 40 | |
Plus the courses every learner takes: Professional Skills, AI literacy (about 5 hours), AI for builders (about 21 hours), and the team project. What every learner takes
Cloud & DevOps Engineering
IT staff, system administrators, and learners from the pilot DevOps and SRE pathways.
You'll learn to administer Linux systems, understand networks, automate with Python and shell scripts, build CI/CD pipelines, manage infrastructure as code with Terraform, run containers, monitor services and apply DevSecOps practice on the cloud you choose. The courses are built on DevOps courses from IBM's DevOps and Software Engineering Professional Certificate, then one cloud provider's courses.
- Time
- About 313–314 hours over 12 months (about 6.5 hours a week), depending on your track.
- Entry
- Basic IT familiarity: operating systems, files and basic networking.
- You'll earn
- A Coursera certificate for each course.
- Optional exams
- AWS Certified Solutions Architect – Associate, Microsoft AZ-900 Azure Fundamentals or Google Cloud Associate Cloud Engineer, matching your cloud. Exam fees aren't included in the Coursera licence.
- Check-ins
- A 60-minute online check-in every two weeks with your Pathway Lead and a small group of learners.
- In the team project
- You own the CI/CD pipeline, infrastructure as code and monitoring.
AWS track: 2 more courses, 43 hours (313 hours in all)
| Course | Provider | Hours |
|---|---|---|
| AWS Cloud Technical Essentials | Amazon Web Services | 21 |
| Architecting Solutions on AWS | Amazon Web Services | 22 |
| 2 courses | 43 | |
Microsoft Azure track: 3 more courses, 43 hours (313 hours in all)
| Course | Provider | Hours |
|---|---|---|
| Essentials with Azure Fundamentals | Microsoft | 18 |
| Secure & Scalable Cloud Infrastructure with Microsoft Azure | Microsoft | 21 |
| Preparing for the AZ-900 Microsoft Azure Fundamentals Exam | Microsoft | 4 |
| 3 courses | 43 | |
Google Cloud track: 6 more courses, 44 hours (314 hours in all)
| Course | Provider | Hours |
|---|---|---|
| Build a Certification Study Guide: ACE Exam Prep | Google Cloud | 2 |
| Google Cloud Fundamentals: Core Infrastructure | Google Cloud | 8 |
| Essential Google Cloud Infrastructure: Foundation | Google Cloud | 8 |
| Essential Google Cloud Infrastructure: Core Services | Google Cloud | 11 |
| Elastic Google Cloud Infrastructure: Scaling and Automation | Google Cloud | 7 |
| Architecting with Google Kubernetes Engine: Foundations | Google Cloud | 8 |
| 6 courses | 44 | |
Plus the courses every learner takes: Professional Skills, AI literacy (about 5 hours), AI for builders (about 21 hours), and the team project. What every learner takes
Data & AI Engineering
Anyone interested in working with data. Data Engineering suits people new to data; Machine Learning & AI suits people comfortable with Python and secondary-school algebra.
You'll learn to build data pipelines, design data warehouses and work with NoSQL databases and Spark (Data Engineering); or build and evaluate machine-learning models, build generative-AI applications with retrieval (RAG) and run open models on your own computer (Machine Learning & AI). The courses are built on courses from IBM's Data Engineering Professional Certificate; on Machine Learning & AI, the Machine Learning Specialization (Stanford Online and DeepLearning.AI).
- Time
- About 306–311 hours over 12 months (about 6.4–6.5 hours a week), depending on your track.
- Entry
- Secondary-school mathematics. Machine Learning & AI also needs a short readiness check (8 Python and 8 algebra questions, about 20–25 minutes) on the application form.
- You'll earn
- A Coursera certificate for each course. On Machine Learning & AI, one extra course (about 28 hours) completes the Machine Learning Specialization.
- Check-ins
- A 60-minute online check-in every two weeks with your Pathway Lead and a small group of learners.
- In the team project
- You own the data pipeline (Data Engineering) or the machine-learning or AI feature (Machine Learning & AI).
| Course | Provider | Hours |
|---|---|---|
| API Design and Fundamentals of Google Cloud's Apigee API Platform | Google Cloud | 7 |
| API Testing a real web application via Postman (guided project) | Coursera | 2 |
| Getting Started with Git and GitHub | IBM | 11 |
| Introduction to Agile Development and Scrum | IBM | 13 |
| Python for Data Science, AI & Development | IBM | 24 |
| Databases and SQL for Data Science with Python | IBM | 18 |
| Data Analysis with Python | IBM | 16 |
| Statistics for Data Science with Python | IBM | 13 |
| 8 courses | 104 | |
Data Engineering track: 8 more courses, 119 hours (306 hours in all)
| Course | Provider | Hours |
|---|---|---|
| Postman Tutorial: Getting Started with API Testing | Packt | 6 |
| Introduction to Data Engineering | IBM | 14 |
| Python Project for Data Engineering | IBM | 10 |
| Hands-on Introduction to Linux Commands and Shell Scripting | IBM | 17 |
| ETL and Data Pipelines with Shell, Airflow and Kafka | IBM | 18 |
| Data Warehouse Fundamentals | IBM | 16 |
| Introduction to NoSQL Databases | IBM | 18 |
| Introduction to Big Data with Spark and Hadoop | IBM | 20 |
| 8 courses | 119 | |
Machine Learning & AI track: 7 more courses, 134 hours (311 hours in all)
| Course | Provider | Hours |
|---|---|---|
| Supervised Machine Learning: Regression and Classification | Stanford Online / DeepLearning.AI | 33 |
| Advanced Learning Algorithms | Stanford Online / DeepLearning.AI | 34 |
| Generative AI with Large Language Models | DeepLearning.AI / AWS | 16 |
| Fundamentals of AI Agents Using RAG and LangChain | IBM | 9 |
| Project: Generative AI Applications with RAG and LangChain | IBM | 9 |
| Foundations of Local Large Language Models | Duke University | 23 |
| Machine Learning in Production | DeepLearning.AI | 10 |
| 7 courses | 134 | |
Plus the courses every learner takes: Professional Skills, AI literacy (about 5 hours), AI for builders (about 11–21 hours), and the team project. What every learner takes
Cybersecurity
Public-sector IT and network staff, incident-response staff and career changers.
You'll learn to protect networks and systems, detect and respond to incidents, use Linux, SQL and Python for security work, apply governance and compliance frameworks, test for vulnerabilities, and secure cloud and AI systems. The courses are built on the full Google Cybersecurity Professional Certificate, plus courses on governance, cloud and AI security.
- Time
- About 325 hours over 12 months (about 6.8 hours a week).
- Entry
- Basic computer confidence. No prior experience needed.
- You'll earn
- The Google Cybersecurity Professional Certificate, and a Coursera certificate for each course.
- Optional exams
- CompTIA Security+ (discounted for Google certificate graduates), or ISC2 Certified in Cybersecurity (CC). Exam fees aren't included in the Coursera licence.
- Check-ins
- A 60-minute online check-in every two weeks with your Pathway Lead and a small group of learners.
- In the team project
- You are the team's security owner: threat model, security testing, access control and the incident runbook.
Plus the courses every learner takes: Professional Skills, AI literacy (about 5 hours), and the team project. What every learner takes
Product Management
Business analysts, public-sector service owners, entrepreneurs and anyone who shapes digital services.
You'll learn to turn a problem into a product strategy, gather and write requirements, plan and prioritise an Agile backlog, test ideas before building them, design with users in mind and measure results. The courses are built on the full IBM Product Manager Professional Certificate, plus University of Alberta and UVA Darden courses.
- Time
- About 277 hours over 12 months (about 5.8 hours a week).
- Entry
- None.
- You'll earn
- The IBM Product Manager Professional Certificate, and a Coursera certificate for each course.
- Optional exams
- AIPMM Certified Product Manager (CPM), or Scrum.org Professional Scrum Product Owner (PSPO I). Exam fees aren't included in the Coursera licence.
- Check-ins
- A 60-minute online check-in every two weeks with your Pathway Lead and a small group of learners.
- In the team project
- You are the team's product manager: product brief, personas, prioritised backlog and success measures.
Plus the courses every learner takes: Professional Skills, AI literacy (about 5 hours), and the team project. What every learner takes
Programme & Project Management (Agile)
Public-sector project officers, team leads and PMO staff.
You'll learn to start, plan, run and close projects with traditional and Agile methods, manage risks, budgets and stakeholders, and coordinate related projects as a programme. The courses are built on the full Google Project Management Professional Certificate, plus programme management courses.
- Time
- About 281 hours over 12 months (about 5.9 hours a week).
- Entry
- None.
- You'll earn
- The Google Project Management Professional Certificate, which counts as 100+ hours of project management education towards PMI credentials, and a Coursera certificate for each course.
- Optional exams
- PMI Certified Associate in Project Management (CAPM), discounted for certificate graduates. Exam fees aren't included in the Coursera licence.
- Check-ins
- A 60-minute online check-in every two weeks with your Pathway Lead and a small group of learners.
- In the team project
- You are the team's delivery lead and Scrum Master: sprints, risks and dependencies, and progress reports.
| Course | Provider | Hours |
|---|---|---|
| API Design and Fundamentals of Google Cloud's Apigee API Platform | Google Cloud | 7 |
| API Testing a real web application via Postman (guided project) | Coursera | 2 |
| Foundations of Project Management | 13 | |
| Project Initiation: Starting a Successful Project | 15 | |
| Project Planning: Putting It All Together | 23 | |
| Project Execution: Running the Project | 25 | |
| Agile Project Management | 20 | |
| Capstone: Applying Project Management in the Real World | 40 | |
| Accelerate Your Job Search with AI | 6 | |
| Agile with Atlassian Jira | Atlassian | 10 |
| Introduction to Software Engineering | IBM | 15 |
| Introduction to Program Management | IBM | 7 |
| Program Management: Framework, Strategy, and Planning | SkillUp | 13 |
| Program Management: Execution, Stakeholders & Governance | SkillUp | 12 |
| Stakeholder Management | Starweaver | 5 |
| Practice Exam for CAPM Certification | SkillUp | 6 |
| 16 courses | 219 | |
Plus the courses every learner takes: Professional Skills, AI literacy (about 5 hours), and the team project. What every learner takes
Enterprise Architecture (Data & Security)
Experienced IT staff (systems, network, database and security staff, developers and ICT managers) who design, run or oversee government systems.
You'll learn to describe and assess a system's architecture, design how data is integrated, stored, migrated and governed, apply security architecture including zero trust, decide where systems should run (cloud, on-premises or hybrid), and take systems into service and manage their suppliers. The courses are built on the full IBM Systems and Solutions Architect Professional Certificate, plus enterprise architecture, privacy, zero trust, service and supplier management courses.
- Time
- About 284–298 hours over 12 months (about 5.9–6.2 hours a week), depending on your track.
- Entry
- At least 3 years in an IT role, or an IT or computing degree and 2 years, and a short readiness check (20 questions, about 25 minutes) on the application form.
- You'll earn
- The IBM Systems and Solutions Architect Professional Certificate, and a Coursera certificate for each course.
- Optional exams
- TOGAF 10 Foundation and ITIL 4 Foundation; on the AWS track, AWS Certified Solutions Architect – Associate. Exam fees aren't included in the Coursera licence.
- Check-ins
- A 60-minute online check-in once a month with your Pathway Lead and a small group of learners.
- In the team project
- You are the team's architecture lead: the architecture overview, data, security and hosting decisions, and the transition-to-service pack.
AWS track: 1 more courses, 22 hours (298 hours in all)
| Course | Provider | Hours |
|---|---|---|
| Architecting Solutions on AWS | Amazon Web Services | 22 |
| 1 courses | 22 | |
Microsoft Azure track: 1 more courses, 11 hours (287 hours in all)
| Course | Provider | Hours |
|---|---|---|
| Advanced Azure Architecture and Migration Strategies | Packt | 11 |
| 1 courses | 11 | |
Google Cloud track: 1 more courses, 8 hours (284 hours in all)
| Course | Provider | Hours |
|---|---|---|
| Reliable Google Cloud Infrastructure: Design and Process | Google Cloud | 8 |
| 1 courses | 8 | |
Plus the courses every learner takes: Professional Skills, AI literacy (about 5 hours), and the team project. What every learner takes
Certificates and professional exams
Every course you complete gives you a Coursera certificate, and completing every course in a Coursera Professional Certificate gives you that certificate too. Both are included in your licence. Professional certifications such as CompTIA Security+, PMI CAPM or the AWS, Microsoft and Google Cloud exams are separate exams with their own fees, which the licence doesn't cover. The programme will set out which exams it supports, and how, by Month 4.