AI Practitioner Professional Certificate (AWS)
IBM, AWS, Anthropic, Packt, Politecnico di Milano, Lund, UVA Darden, Rutgers & Kennesaw State via Coursera
Best for: Career changers with some coding interest. Best if you can invest 3–5 months consistently.
Roles to research: AI / ML Engineer · Software Developer · Applications Engineer
Preparation: Intermediate track. Best if you enjoy problem-solving, structured learning, and tech.
★ Pilot program — reviewed by a real team, with a decision by email.
A 16-course pathway for non-technical and business professionals who need to apply Artificial Intelligence in real-world work. Curriculum sourced from leading universities and industry providers covers AI foundations, generative AI and prompt engineering, ethics and responsible AI, AI for business and digital transformation, AI applied across communication, sales, marketing, and CRM (Salesforce), and certification-track content from AWS, Anthropic (Claude), and Packt. Graduates leave practitioner-ready — prepared to deploy AI tools, design effective prompts, evaluate vendor solutions, and lead AI initiatives.
Official program syllabus
Training details
Delivery format
Hybrid, Self-Paced
Total hours
160 Hours Total=145 Clock Hours + 15 Lab Hours
Training providers
IBM, AWS, Anthropic, Packt, Politecnico di Milano, Lund, UVA Darden, Rutgers & Kennesaw State via Coursera
Published tuition and fees
$7,500
Qualifying WorkforceAP members are not billed for covered training.
Program snapshot
What you should know before you apply
Best fit
Career changers with some coding interest. Best if you can invest 3–5 months consistently.
Typical roles
AI / ML Engineer · Software Developer · Applications Engineer
Course preview
- Introduction to Artificial Intelligence (AI)
- Artificial Intelligence: An Overview
- Introduction to Digital Transformation Part 1
- AI For All
Plus 13 more courses in the full path.
Languages
Skills you’ll learn
Course list
1. Introduction to Artificial Intelligence (AI) ~11 hrs
AI fundamentals from IBM — prompt engineering, automation, machine learning vs. deep learning, and the AI roles.
2. Artificial Intelligence: An Overview ~8 hrs
Politecnico di Milano’s broad overview of AI — historical context, core techniques, neural networks, and how AI systems are designed, evaluated, and deployed.
3. Introduction to Digital Transformation Part 1 ~9 hrs
UVA Darden’s framework— strategy, customer experience, data, and the organizational capabilities to lead AI-driven change.
4. AI For All ~6 hrs
AI CERTs introduction designed for non-technical audiences — what AI is, what it can and cannot do, and how to identify high-value AI opportunities at work.
5. AI Concepts and Strategy ~8 hrs
Rutgers University course on translating AI capabilities into business strategy — build vs. buy decisions, ROI framing, and managing AI initiatives.
6. AI for Professional Communication ~9 hrs
Course on using AI tools to improve writing, presentations, meetings, and stakeholder communication.
7. Understand and Apply Artificial Intelligence Fundamentals ~8 hrs
Course covering applied AI fundamentals — supervised vs. unsupervised learning, model evaluation, and practical deployment considerations.
8. AI for Business: Generation & Prediction ~10 hrs
Coursera course on the two foundational AI capabilities — generation (text, images, code) and prediction (forecasts, classifications) — and how to apply each in business workflows.
9. Artificial Intelligence: Ethics & Societal Challenges ~11 hrs
Lund University course on AI ethics — bias, fairness, transparency, accountability, privacy, and the societal impact of automated decision-making.
10. ChatGPT — Foundations ~6 hrs
Packt course on ChatGPT fundamentals — capabilities, limitations, prompting patterns, and practical use cacross knowledge work.
11. ChatGPT for Beginners: Using AI for Market Research ~2 hrs
Hands-on guided project — use ChatGPT to design research questions, synthesize competitive intelligence, and produce market analysis deliverables.
12. AI Fundamentals with Claude ~7 hrs
Anthropic course on using Claude — prompt engineering, working with long context, and constitutional AI principles.
13. Sales with AI ~6 hrs
AI CERTs course on AI across the sales lifecycle — lead scoring, call analysis, forecasting, and pipeline management.
14. AI for Marketing ~6 hrs
AI CERTs course on AI-augmented marketing — audience segmentation, content generation, and campaign optimization.
15. Salesforce Certified AI Associate Certification ~30 hrs
Packt certification-track preparation — AI fundamentals applied within the Salesforce platform, Einstein AI, predictive vs. generative AI in CRM, and exam objectives for the Salesforce AI Associate credential.
16. AWS Artificial Intelligence Practitioner ~8 hrs
AWS-authored learning plan aligned with the AWS Certified AI Practitioner (AIF-C01) exam — ML/AI concepts, generative AI, AWS AI/ML services (SageMaker, Bedrock), responsible AI, security and governance, and prompt engineering essentials.
17. Lab, Project, and Test Preparation ~15 hrs
Hands-on labs, project work, and test preparation supporting all program competencies
Before you apply
What to expect from this program
Preparation
The published syllabus does not list a recommended prerequisite. Ask an advisor to confirm preparation and program fit.
Time commitment
160 hours • Hybrid, Self-Paced. 17 courses in the full path.
What you should know first
Intermediate track. Best if you enjoy problem-solving, structured learning, and tech.
Funding
Available at no cost through WIOA funding for qualifying members.
Program costs are covered by grants, scholarships, partnerships, and donations — never billed to qualifying members.
Career research
Explore roles connected to these skills
AI / ML Engineer
Software Developer
Applications Engineer
Job requirements and pay vary by employer, location, and experience. A certificate alone does not guarantee a role or salary. Research occupations, wages, and entry requirements, then discuss your next step with an advisor.
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