AI Learning Companions

AI Learning Companions from around the world, each with their own face, voice and expertise. Chat with one, read their guides, take their courses, or design your own.

  • Amahlé Ndlovù (South Africa): Fair, trustworthy AI, told through the stories of the people it affects.
  • Kwamé Asantè (Ghana): Machine learning you can see working, from Kumasi's cocoa farms to your phone.
  • Fatimà Diallò (Senegal): Teaching machines to listen to every language, starting with Wolof.
  • Chukwuemekà Obiechè (Nigeria): From notebook to production: shipping models that survive real traffic.
  • Aïssatà Coulibàly (Côte d'Ivoire): Computer vision, step by step: from a photo of a leaf to a diagnosis.
  • Tariqù Benaì (Morocco): Robots that sense, decide and act, explained from the ground up.
  • Nkirukà Ezenwà (Nigeria): Prompt engineering for people who want AI to do what they actually mean.
  • Sekouù Camàra (Guinea): The maths behind AI, one good question at a time.
  • Amiraà Hassàn (Egypt): How large language models work, and why Arabic is such a good test of them.
  • Thandiwè Dlaminì (Eswatini): Using data to keep medicine on clinic shelves, and teaching you how.
  • Mouhamadouù Bâ (Mali): Small models, big impact: AI that runs where the internet doesn't.
  • Zawadì Mutembò (Tanzania): Camera traps, lions and the computer vision that counts them.
  • Youssoufaù Traoré (Burkina Faso): Generative AI for filmmakers, storytellers and anyone with an idea.
  • Nalèdi Mokoèna (Lesotho): AI rules and rights, explained clearly for citizens and small countries.
  • Abderrahmàn Bensoussàn (Algeria): AI agents that plan, check and act, built for the real world.
  • Akosùa Mensàh (Ghana): AI for small businesses: practical tools for traders, makers and founders.
  • Idrissà Ouédraogò (Burkina Faso): Weather, harvests and data: data science for a changing climate.
  • Zinhlée Khumàlo (Zimbabwe): Chatbots in the classroom: how they work and how to use them well.
  • Mamadouù Dioufée (Senegal): Drones, boats and robots that work along the coast.
  • Lindiwe Sibandà (Zambia): Building AI agents, and the start-ups around them.
  • Hiroshì Yamadà (Japan): Industrial robots and the AI that makes them safer, explained carefully.
  • Mei-Líng Zhāng (China): Inside large language models: what they learn, and what they only seem to know.
  • Rajèsh Krishnàn (India): Linear algebra, probability and calculus: the maths of AI, made friendly.
  • Soo-Yéon Kimm (South Korea): Generative AI for artists, webtoon creators and music makers.
  • Fatimàh Rahimì (Afghanistan): Language technology for Dari and Pashto, and every language left out.
  • Arjùn Sharmà (India): AI agents for customer service, from first prototype to millions of chats.
  • Yuki Tanakà (Japan): Kind, careful AI: designing assistants people can trust.
  • Wei-Chéng Liú (Taiwan): The chips, numbers and engineering that make AI run fast.
  • Priyà Nairé (India): Medical imaging AI, and the ethics of getting it right.
  • Barakà Al-Rashíd (Saudi Arabia): AI policy, smart cities and how governments decide what AI may do.
  • Ngo Thi Huừngé (Vietnam): Data science for online shops: turning clicks into decisions.
  • Khalidà Sultàn (Pakistan): Machine learning from scratch, for self-taught builders everywhere.
  • Chaiyapòn Srisomboòn (Thailand): AI agents for deliveries, logistics and getting things there on time.
  • Layla Al-Mansourì (UAE): Arabic large language models and AI in government services.
  • Bintà Yusupovà (Uzbekistan): Maths olympiad coaching for the maths behind AI.
  • Davaadorjì Gantulàg (Mongolia): Reading the land from space: computer vision and satellite images.
  • Siti Nurhalizah Rahimàn (Malaysia): Generative AI for content creators, marketers and small brands.
  • Ravi Chandrasekharàn (Sri Lanka): How computers understand Tamil, Sinhala and English, explained simply.
  • Aynurè Abdullayevà (Azerbaijan): Getting great answers from AI: prompting and language models for everyone.
  • Jae-Wòn Parkk (South Korea): AI agents that play, plan and learn, from games to real tasks.
  • Divyà Mehtà (India): AI for business owners: from family firms to fast-growing start-ups.
  • Hamzà Al-Khalìl (Jordan): Drones, robots and the computer vision that guides them.
  • Nataliyà Kovalenkò (Kazakhstan): Machine learning fundamentals, explained with rockets, steppe and stars.
  • Thida Kyawzìn (Myanmar): Language AI for Burmese, and for humanitarian work that needs it.
  • Ismaìlè Rahimovì (Tajikistan): Keeping AI running in power plants: deployment, monitoring and maintenance.
  • Élèna Petrovà (Russia): The foundations of machine learning, rigorous and clear.
  • Luís Ferreiràs (Portugal): Build your first AI agent this week, and learn by building.
  • Annikà Lindqvìst (Sweden): AI ethics, sustainability and doing the right thing at scale.
  • Konstantinì Papadopouloùs (Greece): Geometry, logic and the old ideas inside modern AI.
  • Maïa Duplessiè (France): Generative AI for artists and designers, with taste and care.
  • Björn Sigurdssòn (Iceland): Language AI for small languages, from Icelandic to yours.
  • Agnieszka Kowalskà (Poland): Machine learning foundations and smart prompting, for curious beginners.
  • Mattèo Ferrarì (Italy): Robots, race cars and data: AI in motion.
  • Ingridè Hansèn (Norway): Computer vision under the sea: fish farms, oceans and data.
  • Ferencz Nagŷ (Hungary): Probability and statistics for AI, with maths-camp puzzles.
  • Cataliná Ionescù (Romania): AI security: how AI systems are attacked, and how to defend them.
  • Nikolàs Petrovicì (Serbia): AI agents and generative AI for game makers.
  • Siobhàn O'Briénn (Ireland): Europe's AI rules, data protection and your rights, explained plainly.
  • Dariusz Wojciechowskì (Poland): MLOps and large language models in production, without the drama.
  • Yildizè Demirèl (Turkey): Language AI for Turkish and beyond, and prompts that respect it.
  • Alekseï Volkovì (Russia): Large language models and the maths inside them, from a physicist.
  • Marisolò Garcíà (Spain): Data science through football: stats, models and match-day decisions.
  • Lasse Mäkìnen (Finland): AI basics for everyone, the Finnish way: clear, free and practical.
  • Zoë Papadakìs (Greece): AI meets ancient art: computer vision for history and heritage.
  • Michèl Lambertè (Belgium): Inside Europe's AI rules: how laws get made and what they mean for you.
  • Katarína Novákovà (Slovakia): Factory robots, and the AI that keeps production lines running.
  • Emrè Yilmazì (Turkey): AI for online businesses: agents, automation and growth.
  • Sigríður Björnsdóttìr (Iceland): Volcanoes, earthquakes and the maths of predicting them.
  • Vladimìr Novàk (Czech Republic): Prompt engineering for developers: reliable outputs, tests and tools.
  • Aoifè Murphŷ (Ireland): Generative AI for writers and storytellers, from an Irish storyteller.
  • Marisèl Rodriguèz (Mexico): Prompting and AI tools for small businesses and busy people.
  • Deshawné Thompsòn (USA): Fair AI in hiring, lending and everyday life: who it helps, who it harms.
  • Chloé Tremblàŷ (Canada): How large language models really learn, from Montréal's deep learning scene.
  • Xiomàra Hernándèz (Guatemala): AI that speaks Mayan languages, and why that matters.
  • Jamàl Washingtoneè (USA): Self-driving cars, robots and the computer vision that guides them.
  • Ingridè Bjornssòn (Canada): AI for farms and food businesses on the Canadian prairies.
  • Alejandroó Riveràs (Mexico): Generative AI for creators: images, music and video in your own style.
  • Keishà Brownè (Jamaica): AI for music, media and small businesses, with Kingston energy.
  • Tatiànna Morrisòn (USA): Health data science: from nurses' notes to models that help patients.
  • Carlòs Ramirèz (Costa Rica): Deploying AI that lasts: MLOps and agents in the real world.
  • Amèlia Whitè (USA): AI safety, and how researchers look inside language models.
  • Dontè Jacksoneè (USA): Machine learning basics through basketball stats and real games.
  • Valentinà Lopèz (Colombia): AI for smarter cities and businesses, from Medellín.
  • Rodrigoò Silvà (Brazil): Payments, agents and MLOps: the AI behind Brazil's instant money.
  • Isabelà Martinèz (Argentina): How AI understands language, and what it misses about people.
  • Luciànò Ferreiràs (Brazil): Computer vision from Recife's tech hub: cameras that understand the world.
  • Camilà Torresè (Chile): Machine learning under the darkest skies on Earth.
  • Ximènà Castillò (Peru): Data science for farms, food and the Andes.
  • Sebastiàn Vargàs (Venezuela): Building chatbots that work: prompts, language models and testing.
  • Mariànnà Sanchèz (Ecuador): Underwater robots and AI for the Galápagos.
  • Diègo Ramirèz (Bolivia): AI policy, natural resources and fair technology for Latin America.
  • Fernandà Oliveirà (Brazil): Prompting for creatives and marketers: words that make AI shine.
  • Arohà Ngàta (New Zealand): AI that respects people and their data, from a Māori point of view.
  • Lachlaneè Mitchèll (Australia): Robots in the outback: automation, mining and MLOps.
  • Tiàre Teriifaàtia (French Polynesia): Reef data and ocean science: data science in the Pacific.
  • Kaimànà Kahananùi (Hawaii / USA Pacific): Navigating by the stars: the maths of search, planning and AI.
  • Merelaisà Tuivagà (Fiji): AI for climate resilience, policy and Pacific island communities.
  • Braideùn O'Sullivàn (Australia): Prompting large language models, from first try to dependable results.
  • Aleksandrà Sorokinà (Russia / Antarctic Station): Ice cores, climate and the data science of Earth's coldest place.
  • Erikà Lindströmè (Sweden / Antarctic Station): Robots that explore ice and ocean: autonomous agents at the end of the world.
  • Mojeed Abisiga (Nigeria): AI in the news, in business and in your life, explained with an editor's eye.
  • Gbenga Akingbulere (Nigeria): AI and cybersecurity: how attacks work, and how to keep AI systems safe.
  • Ogweda Haruna (Nigeria): Statistics, the quiet engine of AI, explained by a statistician's AI companion.
  • Sonia (English(United States of America) SoCal Valley girl. ): Super friendly and cute while being intelligent and precise.