π― Session Outcomes:
β
Enhanced Understanding β Participants gained theoretical and practical insights into Data Science, AI, and ML.
β Hands-on Experience β Students implemented machine learning models, deep learning techniques, and data visualization.
β Industry-Relevant Skills β Exposure to Python, AI frameworks, and Oracle APEX for application development.
β Real-World Applications β Case studies helped students understand AI-driven decision-making.
β Problem-Solving Abilities β Participants learned to apply AI techniques to real-time challenges.
β Data Analytics Expertise β Improved knowledge of data handling, visualization, and business intelligence tools.
β AI Ethics Awareness β Addressed concerns like bias, security, and ethical implications of AI.
β Career Readiness β Equipped students with the necessary skills for AI, ML, and Data Science careers.
β Collaboration & Innovation β Encouraged teamwork and innovative thinking in AI-driven projects.
β Future Learning Pathways β Inspired students to explore further AI research and practical applications.

