AI & Machine Learning Masterclass at IISC BangaloreBuild a strong foundation in artificial intelligence and machine learningThis masterclass is designed for students, professionals, tech enthusiasts, and aspiring data scientists who want to dive into the world of artificial intelligence and machine learning. You’ll learn core concepts, real-life applications, and get hands-on with ML workflows – even if you’re just starting out. Whether you’re from a coding, non-coding, or business background, this workshop will help you make sense of AI and ML in a practical, beginner-friendly way.This workshop is for:- Students and graduates exploring careers in AI/ML- Non-tech professionals curious about how AI works- Aspiring data scientists wanting hands-on experience- Educators and trainers looking to adopt AI tools- Working professionals aiming to apply ML in their field- Anyone eager to understand AI’s real-world impactWhat You’ll LearnAudience IntroductionTiming: 10:30 a.m. – 11:00 a.m.Welcome and expectationsAI/ML landscape overviewReal-world impact of machine learningUnderstanding AI and ML FundamentalsModule 1Timing (11:00 a.m. to 1:00 p.m.)Start with core concepts and how machines learn from data.Topics Covered- What is AI and ML?Definitions, differences, and real-life applications- Supervised vs Unsupervised LearningUse cases, examples, and simplified explanation- Workflow of a Machine Learning ModelData -> Training -> Evaluation -> Prediction- Common ML Algorithms (explained simply)Linear regression, classification, clusteringSkills Acquired- AI and ML conceptual clarity- Data-driven thinking- Model building mindset- Application awarenessTools and Techniques in Machine LearningModule 2Timing (2:00 p.m. to 3:30 p.m.)Get familiar with tools used to build and experiment with AI and ML.Topics Covered- Hands-on with Google Teachable MachineCreate a basic ML model in minutes- Intro to Python and Scikit-learnBeginner-friendly ML Libraries- Role of Data in Machine LearningCollecting, cleaning, and splitting datasets- Responsible AIBias, fairness, and ethical use of dataSkills Acquired- Tool-based learning- Awareness of Python ML libraries- Responsible AI principles- Understanding ML pipelinesMini Project and AI Career InsightsModule 3Timing (3:30 p.m. to 05:30 p.m.)Apply what you’ve learned and plan your next steps in the AI/ML journey.Topics Covered- ML Mini Project (live activity)Build a model using Google Teachable Machine or Scikit-learn- How to Learn AI/ML FurtherCertification paths, courses, online platforms- AI Career Roles and Salary TrendsData analyst, ML engineer, AI consultant- What’s Next in AI?GenAI, LLMs, AI in your fieldSkills Acquired- Hands-on ML model creation- Career mapping in AI/ML- Project presentation and teamwork- Clarity on next steps
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