Executive Summary
Model: Industry Practicum + University AI Module (Purdue University (West Lafayette, Indiana)
StrategEast proposes the launch of a 12-month National AI & Engineering Acceleration Program designed to strengthen Azerbaijan’s high-value digital workforce through an integrated industry–academic model.
The program combines:
- Industry-led engineering training and real-world project execution (Sigma Software Group)
- International academic AI micro-credentials (Purdue University, West Lafayette, Indiana)
- Structured selection, monitoring, and reporting aligned with national workforce development priorities
Each cohort, the program will train up to 125 university students and young technical professionals, with 70 advancing into the advanced project-based engineering phase.
This initiative is designed to:
- Increase national AI and engineering capacity
- Improve graduate employability and job readiness
- Build a structured pipeline of high-performing specialists
- Support local job creation and talent retention
- Strengthen Azerbaijan’s position in applied AI and modern engineering practices
What the country (IT ecosystem) gains:
- Capacity building and development of IT workforce of the country
- Specialists who have been selected through an admissions process and completed hands-on practice and project work aligned with engineering standards, not just a lecture-based course.
- Practical AI literacy backed by an official Purdue University module (professional certificate + digital badge).
- A pipeline of top graduates who, based on program results, can be considered for industry employment, including opportunities at Sigma Software Group and other partners. In other words, the program directly supports job creation and helps retain strong talent in the country.
The initiative has two complementary layers and runs as two consecutive cohorts.
Each cohort includes:
- Industry Layer “Engineering Mastery Program” (Core Program – Sigma Software Group)
- University Layer (Academic AI Module – Purdue University, West Lafayette, Indiana)
These layers run in parallel and reinforce each other.
| Parameter | Cohort 1 | Cohort 2 | Annual Total |
| Duration | 6 months | 6 months | 12 months |
| Phase 1 participants (theory) | 125 | 125 | 250 |
| Phase 2 participants (practice) | 70 | 70 | 140 |
| Purdue AI module participants | 50 | 50 | 100 |
| Phase 1 — Excellence Fundamentals | Phase 2 — Project-Based Practice | |
| Duration | 2 months | 4 months |
| Participants | Up to 125 (5 tracks × 25) | 70 (5 cohorts × 14) |
| Format | Twice a week + live mentor workshops per track | Full-scale project work in mini-teams with sprints, code & architecture review |
| Selection | Technical assessment at the end of Phase 1 — top 14 per track advance | Cohorts formed by specialization track, skill level, and tech stack |
| Month 1–2 | Month 3–4 | Month 5–6 | Month 7–8 | Month 9–10 | Month 11–12 |
| Cohort 1
Phase 1: Selection |
Cohort 1
Phase 1: Fundamentals |
Cohort 1
Phase 2: Project-Based Practice |
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| Cohort 2
Phase 1: Selection |
Cohort 2
Phase 1: Fundamentals |
Cohort 2
Phase 2: Project-Based Practice |
|||
| Purdue University AI Micro-Credentials — asynchronous, running in parallel with both cohorts | |||||
Target Audience:
- Bachelor’s students
- Master’s students
- Specializations:
- Software Engineering
- Data Engineering
- AI / ML Engineers
- Cloud & DevOps
- Blockchain / Web3 Developers (optional specialized track)
Selection process
Marketing and promotion of the selection process will be conducted by the partner through their communication channels, with informational support from StrategEast. Our team will provide the necessary content and can assist with preparing visual design materials. StrategEast will also develop and manage the program landing page and application forms to facilitate the selection process, while the stakeholder will be responsible for publishing and disseminating promotional materials through their platforms.
Industry Layer — Engineering Mastery Program (Sigma Software Group)
Delivered by Sigma Software Group and built around practice: selection, small-group work, mentoring, and a project phase grounded in engineering standards. Participants don’t just study materials. They complete regular assignments, receive reviews and feedback, learn to work in a team delivery model, and produce outcomes at a quality level that can be applied in real-world systems.
Sigma’s key value is its results and market focus: participants graduate with a portfolio of completed work and a clear competency profile, while the IT ecosystem gains a structured pool of high-performing specialists. Top graduates can be considered for further growth and potential industry placement, including at Sigma Software Group and other partners — which directly supports job creation.
Phase 1 — Excellence Fundamentals (2 months)
- Duration: 2 months, with sessions held twice per week
- Total participants: up to 125 participants across three specialization tracks
- Format: structured theoretical sessions combined with parallel live workshops led by industry mentors
- Assessment: technical evaluation conducted at the end of the phase to identify top-performing participants
Phase 2 — Project-Based Engineering Cohorts (4 months)
- Participants: approximately 70 participants selected from Phase 1
- Cohort size: around 14 participants per cohort, formed based on specialization track, skill level, and technology stack
- Format: hands-on project work in mini-teams with clearly defined roles, sprint cycles, code and architecture reviews, and regular mentorship
- Expected outcome: 50 participants successfully graduate and deliver end-to-end project solutions
| Cohort Type | Target Audience | Focus |
| AI / ML / Data Engineering | Data and ML specialists | Applied POC/PED projects, modern technology stacks, production-like approach |
| Engineering Practice | Junior / Strong Junior engineers | Modern development methodologies, Agile project management, real team-based work |
| Blockchain / Web3 Engineering | Blockchain developers | Smart contract development, dApp architecture, security and scalability, production-like environments and tooling |
- Phase 1: 125 participants
- Phase 2: 70 participants
- Fully scalable model for repeated cohorts
- Scalable talent development framework
- Combination of mass education and deep specialization
- Strong focus on modern engineering and delivery excellence
- Coverage of emerging Web3 and decentralized technologies
- Creation of a sustainable talent pipeline
As part of the program, an academic AI component is proposed in collaboration with Purdue University (West Lafayette, Indiana), based on its AI micro-credential courses.
These courses are short university programs designed to provide practical understanding of modern artificial intelligence technologies and their real-world applications.
The Purdue component can include one or several courses from the university’s AI micro-credential portfolio.
Each course represents a standalone learning module with approximately 15 hours of total learner workload.
Depending on the goals of the program and the available budget, the program can include:
- 1 university course (~15 hours of learning)
- 2 courses (~30 hours of learning)
The selection of courses can be adjusted based on the participant profile and program objectives.
Examples of topics that may be included in the program:
- Interdisciplinary AI Fundamentals — foundational understanding of artificial intelligence technologies and their applications
- AI Policy and Governance — regulation, ethics, and governance frameworks for AI implementation
- Machine Learning in Action: Tools, Techniques, and Industrial Cases — practical applications of machine learning methods and tools
- AI Data Storytelling — interpreting and communicating insights derived from AI models and data
Each course is delivered as a structured online learning module with defined learning outcomes, assignments, and a final assessment. Upon completion, participants receive formal recognition of their university-level training in AI from Purdue University. The credentials can be added to professional profiles and shared with employers, institutions, and partner organizations.
Each program cohort includes 50 participants.
Each AI course includes:
- self-paced learning in an asynchronous format
- short video lectures and reading materials
- practical assignments based on real-world cases
- quizzes and intermediate knowledge checks
- a final assessment confirming successful course completion
The full learning path and participant progress are tracked through the learning platform, enabling transparent monitoring and reporting of program outcomes.
Upon successful completion of the course, participants receive:
- an official Purdue University Professional Certificate
- a verifiable digital badge (Credly) that can be added to LinkedIn and professional profiles
- official course completion documentation
If participants complete two courses, a certificate is issued for each completed course.
Purdue has also indicated that certain AI micro-credentials may in the future articulate into academic credit (up to 3 credits) toward selected master’s programs such as MS in Artificial Intelligence or MS in Data Science, subject to final academic approval.
While this does not guarantee admission, it creates a clear academic pathway for participants interested in continuing their education at Purdue.
