Student performance prediction with AI
Why it matters: Student Performance Prediction with AI enhances personalized learning, identifies at-risk students, and boosts retention.
Sanksshep Mahendra
Sanksshep Mahendra is a technology executive with success in driving, vision, strategy, design, and execution of software engineering for the web, mobile, apps, social, voice, IoT, applications along with Machine learning and AI. His expertise lies in partnering with business leaders, powering through roadblocks, and leading global teams to deliver disruptive products that advance the organization’s mission and capture game-changing results in the market. Sanksshep Mahendra has a lot of experience in M&A and compliance, he holds a Master's degree from Pratt Institute and executive education from Massachusetts Institute of Technology, in AI, Robotics, and Automation.
Ethical issues of AI in education
Why it matters: Explore ethical issues of AI in education like privacy, fairness, transparency, accountability, and teacher-student impact.
Collaborative learning with AI tools
Why it matters: Explore Collaborative Learning with AI Tools: Foster teamwork, critical thinking, and personalized education efficiently.
AI to bridge learning gaps
Why it matters: AI to Bridge Learning Gaps: Discover how AI personalizes learning, offers real-time feedback, and addresses disparities.
Future of AI in educational policy
Why it matters: Exploring AI’s powerful role in shaping educational policy, curriculum, governance, equity, and teacher support.
AI and Machine Learning in Education: Personalizing Learning Paths
Why it matters: Explore how AI and Machine Learning personalize learning paths, enhancing student engagement enhancing outcomes
Defining an AI strategy for businesses
Why it matters: Defining an AI strategy for businesses helps align AI innovation with goals, boosting efficiency and driving success.
Identifying AI opportunities within an organization
Why it matters: Identifying AI opportunities within an organization by evaluating AI readiness, workflows, automation, and challenges.
Building a data infrastructure for AI
Why it matters: Building a Data Infrastructure for AI: Learn about key components, scalable pipelines, storage, and data governance.
Selecting the right AI tools and platforms
Why it matters: Selecting the Right AI Tools and Platforms: Explore factors, open-source vs commercial tools, cloud solutions, and more!