- Gustavo Fonseca Ribeiro
- YING WANG
Intermediate
Event organizer(s)
Description
The course offers a comprehensive exploration of Artificial Intelligence, examining its evolving landscape and its capacity to drive inclusive and sustainable development. It delves into the foundational principles and key technologies that underpin AI, such as generative AI, Natural Language Processing (NLP), and computer vision. Participants will learn how to identify and prioritize high-impact AI applications across critical sectors like energy, health, and education. The course also highlights models for multi-stakeholder collaboration and the creation of equitable AI ecosystems, with particular attention to the transformational adoption of AI in emerging economies. Finally, it addresses the development of ethical frameworks and global standards that promote responsible and accessible AI growth.
This training is targeted at technical managers, engineers and employees from regulators, government organizations, companies and academia, who are interested in the latest developments in AI technology and their applications.
Qualifications or experience needed to participate in this training course:
- The participants are expected to have a telecommunication /ICTs engineering educational background and basic knowledge of ICT
Selection criteria:
- diversity of students, including the gender balance;
- the strength of participants’ application, such as work related to the course topic in the application.
Number of available places for the cohort:
- Max 70 active participants
Upon completion of this course, participants will be able to:
- Explain core AI concepts and key technologies such as generative AI, NLP, and computer vision.
- Identify high-impact, inclusive AI applications across sectors like health, education, and climate.
- Evaluate collaborative models and strategies for accessible and affordable AI solutions.
- Assess the ethical and societal implications of AI adoption in diverse global contexts.
- Advocate for responsible AI standards and equitable policy frameworks.
- Self-learning: The participants are required to read and watch the course materials uploaded on the platform; some courses will be delivered lively via zoom platform.
- Tutor-led live and chat zoom sessions: Tutor will deliver live sessions and respond questions raised from participants;
- Forum: participants and tutors will interact through the ITU Academy forum platform to discuss course topics and express their opinions and submit questions;
- Quizzes and Assignment: participants are required to take quizzes which will be organized at the end of each week to check their knowledge achievement. The assignment also needs to be submitted at the end of the training course to assess satisfactory understanding of the given topic.
The course will contain the following assessment and methods:
- Course Materials: The relevant course material will be made available on the website, which will include presentations and recorded videos with explanation of the key topics. Some of the courses will be delivered via ZOOM meeting.
- Online Discussion Forums: Participants are expected to participate actively in discussion forums on selected topics throughout the week. Tutors will respond to the posts and interact with participants
- Chat Sessions: Online chat sessions with the tutor will take place 2 times during the two weeks’ time, if there is significant demand, we will arrange additional chat sessions. All participants are expected to join the chat sessions to interact with tutors. The specific time will be sent to participants in advance by tutors.
- Quizzes: 2 mandatory online quizzes will be launched at the end of each week, and participants are required to submit them before the announced deadline.
- Assignment: There will be a mandatory assignment at the end of the course, which is required to submit before the announced deadline.
It will be graded based on the following:
- Quizzes (2 quizzes): 30%
- Capstone Project (Individual Assignment): 40%
- Discussion Forums: 20%
- Live and chat sessions: 10%
- Total: 100%
A total score of 70% or higher is required to obtain the ITU certificate
Session: Opening Session: Setting the Stage & AI Foundations (Part 1)
Date: May 25
Learning Objectives:
- Outline the goals and the global context of inclusive AI development under the theme “Bridging the AI Divide.”
- Explain core AI and Machine Learning principles, including neural networks and data pipelines.
- Identify key AI technologies such as Generative AI, Natural Language Processing (NLP), and Computer Vision.
Session: AI Foundations: Demystifying the Technology (Part 2)
Date: May 26
Learning Objectives:
- Evaluate AI infrastructure needs, including compute resources and the trade-offs between cloud and edge computing.
- Assess the role of open-source tools in making AI more accessible.
Session: Understanding AI Demand & Strategic Scenarios
Date: May 27
Learning Objectives:
- Identify and prioritize high-impact, inclusive AI applications in sectors such as health, education, and climate.
- Align potential AI use cases with ethical AI principles and global policy frameworks.
Session: AI Industry Integration & Collaborative Ecosystems
Date: May 28
Learning Objectives:
- Evaluate models for multi-stakeholder collaboration (e.g., industry–academia–startups).
- Analyze trends in affordable and localized AI solutions for the Global South.
Session: AI Adoption: Cross-Industry Transformation
Date: May 29
Learning Objectives:
- Examine case studies of AI transformation in emerging economies (e.g., agriculture, healthcare).
- Develop metrics for measuring equitable impact, such as accessibility and job creation.
Session: AI for Science: Accelerating Global Solutions
Date: June 1
Learning Objectives:
- Apply low-cost AI tools to address planetary challenges such as climate change and disease tracking.
- Propose strategies for democratizing access to scientific AI tools.
Session: AI Standardization: Enabling Responsible & Inclusive Growth
Date: June 2
Learning Objectives:
- Evaluate ethical frameworks for bias mitigation, transparency, and accountability in AI.
- Assess the role of global standards in ensuring interoperability and preventing a widening divide.
Session: AI Enterprise: Inclusive Business Leadership
Date: June 3
Learning Objectives:
- Plan strategies for ethical AI deployment, including cost-effective models and workforce reskilling.
- Analyze future outlooks for policy and equitable AI markets.
Session: Capstone Project (Final Assignment) Workshop
Date: June 4
Learning Objectives:
- Synthesize course concepts to develop a concrete project proposal for an inclusive AI solution.
Session: Closing Ceremony
Date: June 5
Learning Objectives:
- Summarize the training outcomes.
- Conduct a final Q&A session.
Capstone Project (Final Assignment) Delivery
Dates: June 6–20, 2026
Registration information
Unless specified otherwise, all ITU Academy training courses are open to all interested professionals, irrespective of their race, ethnicity, age, gender, religion, economic status and other diverse backgrounds. We strongly encourage registrations from female participants, and participants from developing countries. This includes least developed countries, small island developing states and landlocked developing countries.
