Blore.AI delivers structured, hands-on university training programs focused on Artificial Intelligence, Generative AI, and modern data workflows.
Our programs are designed around the Microsoft ecosystem and OpenAI technologies, enabling students to learn through practical, tool-driven experiences aligned with current industry practices.
Why AI Training Matters
- Introduce students to real-world AI tools and platforms
- Bridge the gap between academic concepts and practical usage
- Build strong foundations in data, automation, and AI workflows
- Prepare students for evolving technology landscapes
Our Approach
Structured Curriculum
Programs aligned with university learning paths
Tool-Based Learning
Hands-on exposure to Microsoft and OpenAI platforms
Practical Exercises
Guided labs and mini-projects for applied understanding
Flexible Delivery
Workshops, semester programs, and bootcamps
Who Should Attend
Undergraduate Students
Students across engineering, science, and commerce streams
Final Year Students
Students preparing for industry roles and projects
Faculty Members
Educators looking to integrate AI into curriculum delivery
Training & Placement Cells
Teams responsible for academic-industry alignment
Program Formats
Workshops (1–2 Days)
Introductory sessions on AI tools and concepts
Bootcamps (2–4 Weeks)
Hands-on learning with guided projects
Semester Programs
Structured modules integrated into academic schedules
Faculty Development Programs
Enable educators to deliver AI-focused curriculum
Training Areas
- Generative AI using OpenAI APIs
- Microsoft Copilot and AI productivity tools
- Azure AI and cloud fundamentals
- Data analytics with Microsoft ecosystem
- Low-code automation using Power Platform
Sample Use Cases
- Build AI-powered chatbots and assistants
- Create data dashboards and analytics reports
- Automate routine academic or project workflows
- Develop mini AI applications using APIs
Pilot Program (2–4 Weeks)
Start with a structured pilot program to introduce AI capabilities within your institution before scaling across departments.
- Identify target student groups or departments
- Conduct hands-on training sessions
- Build mini projects or capstone outputs
- Evaluate outcomes and expand program scope
Learning Outcome:
Develop practical understanding of AI tools, data workflows, and automation using modern industry platforms.