DIYA Programs
Research opportunities for students, professional development for educators, and networking for professionals in data science and AI.
AI Research
Conduct data-driven AI research: build predictive models and produce a research-style paper and presentation to showcase your work.
AI Ventures
Build the skills to turn an idea into a real AI-powered produc. Learn prompting, agents, and modern prototyping including teamwork, problem-solving, and responsible AI habits.
AI & Cybersecurity
Explore how artificial intelligence is used to detect cyber threats, prevent online scams, and protect digital systems through real-world examples and hands-on activities.
AI & Data Science
Dive into AI, data science and ML core concepts with hands-on learning and capstone projects. Requires prior Python experience.
AI & Robotics
Learn how artificial intelligence powers robots and autonomous systems through simulations, real-world examples, and hands-on problem-solving activities.
AI & Creativity
Explore AI in art, music, storytelling, and design through guided, no-code creation projects and responsible AI discussions.
AI & Healthcare
Explore AI in healthcare through real case studies and hands-on, no-code labs in Tableau, building data skills and responsible AI awareness.
Python for AI
Build strong Python foundations for AI through hands-on projects—APIs, web scraping, and interactive apps—ending with a capstone showcase.
Research Integration Workshop for Educators
Professional development program helping educators integrate research skills and methodologies into their curriculum. Includes lesson plans, assessment tools, and ongoing support.
Bringing Data & AI into Your Classroom
Professional development program helping educators integrate data science and AI concepts into existing lesson plans across subjects with hands-on tools and real-world examples.
Industry-Academic Network
Connect with researchers, industry professionals, and academics. Share expertise, mentor students, and collaborate on research initiatives that bridge theory and practice.
Deep Dive into AI with Python Libraries
Learn to teach AI and data science using Python libraries like Pandas, NumPy, Scikit-learn, and TensorFlow through guided projects, coding challenges, and classroom-ready curricula.
Deep Dive with CODAP & Tableau
Master data visualization and statistical analysis using CODAP and Tableau to create engaging, interactive lessons that develop students' data literacy and critical thinking skills.