Volunteer Online Machine Learning Training Support

Host entity: UNDP Istanbul International Center for Private Sector in Development

Application deadline: 08/10/2026

Mission and objectives

Istanbul International Center for Private Sector in Development (IICPSD) supports the private sector and foundations to become transformative partners in development through research, advocacy for inclusive business, facilitation of public-private dialogue and brokering partnerships. IICPSD, established in 2011 in partnership with the Government of Turkey, is one of UNDP's six Global Policy Centres. It leads UNDP’s global work on private sector and foundations and supports UNDP’s offices all over the world. The Center focuses on four thematic areas:

1. Inclusive Business;

2. Private Sector Engagement in Skills Development;

3. Impact investing;

4. Resilience and Crisis Response.

The Center also hosts four global initiatives: Business Call to Action, SDG Philanthropy Platform, Global Islamic Finance and Impact Investing Platform and Connecting Business Initiative.

Assignment context

The online volunteers are expected to deliver minimum 8 live lectures(online) on Machine Learning. The materials for Machine Learning are present.

Task description

We are recruiting 1 Online Volunteer to deliver live training on Machine Learning and Generative AI course for the Innovation Campus programme under the guidance of the team focal point:

The Online Volunteer will:

- Review and improve 8 existing SDG AI Lab slide decks which are for training materials for Data Analysis, Modelling, Generative AI, Git & GitHub, Docker, and Deployment.
- Prepare one pre-recorded demonstration for each topic of the three topics: Data Analysis, Modelling, Generative AIGit & GitHub, Docker, and Deployment, delivered before the corresponding live sessions
- Deliver 8 live online lectures (one each on Data Analysis, Modelling, Git & GitHub, Docker, and Deployment), Generative AIincluding practical live coding demonstrations.
- Answer participants' questions during the live sessions.
- Provide brief documentation summarizing the updates made to the training materials.

Time Allocation (11–15 hours/week)
• Preparation & material improvement (reviewing/improving slides, building demos): ~6–8 hrs
• Live teaching & coding sessions: ~2–3 hrs
• Student support (Q&A, chat, follow-up): ~2–3 hrs
• Coordination meetings with SDG AI Lab: ~1 hr
Schedule: Evening sessions on weekdays and morning sessions on weekends.

Target Audience

Participants are Innovation Campus students with a beginner technical background (basic programming familiarity, limited prior DevOps exposure). Expected class size is approximately 50 participants. Sessions are conducted in English/Turkish.

Skills and experience

-Minimum a senior year student, ideally a Bachelor’s Degree in Computer Science/Engineering or in a relevant field, with strong programming background.

-Teaching experience.

-A high level of proficiency in Data Science

-Knowledge about Python, Machine Learning and Data Science.

-Strong coding skills.

Full eligibility requirements, conditions of service and application instructions are available on the official UNV platform.