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Advanced Machine Learning & AI: Concepts and Real-World Applications

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Delivery Mode
Virtual / Online
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Level
Moderate
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Duration
3 Days
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Certificate
Mentor Based
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Language
English
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Rating
4 Stars
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About Workshop

IntelliLearn is a cutting-edge international workshop crafted to introduce and deepen understanding of Machine Learning (ML) and Intelligence systems. This program is curated for learners, researchers, and professionals aiming to harness the power of data and algorithms to solve real-world challenges. Through expert-led sessions, hands-on projects, and collaborative discussions, participants will explore supervised and unsupervised learning, neural networks, deep learning architectures, natural language processing, and ethical AI deployment.
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Aim

To empower participants with foundational and advanced concepts in Machine Learning and Artificial Intelligence, fostering real-world application skills and preparing them for dynamic roles in intelligent systems and data-driven industries.
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What Participants Will Learn

  • Introduce core ML and AI principles
  • Enable learners to build predictive and classification models
  • Understand the ethical considerations in intelligent system design
  • Familiarize participants with current trends and industry practices
  • Motivate interdisciplinary research and innovation
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Structure

Day 1 – Foundations of Modern Machine Learning ā— Evolution of Machine Learning: Classical to Intelligent Systems ā— Supervised, Unsupervised & Self-Supervised Learning Techniques ā— Structuring ML Pipelines: Data Preprocessing to Model Deployment ā— Hands-On: Training your first ML model using scikit-learn on real-world data Day 2 – Deep Learning & Transfer Learning in Action ā— Understanding CNNs, RNNs, Transformers – Architectures that Matter ā— Leveraging Transfer Learning with Pretrained Models (ResNet, BERT) ā— Best Practices for Fine-Tuning and Customization ā— Hands-On: Fine-tuning a transformer model for text classification using Hugging Face Day 3 – ML Ethics, Interpretability & Applications ā— Responsible AI: Fairness, Bias Mitigation, and Compliance ā— Interpreting ML Decisions: SHAP, LIME, and XAI Tools ā— Industry Use Cases: Healthcare, Finance, Smart Cities ā— Hands-On: Interpreting model predictions using SHAP on a sensitive dataset

Important Dates

Registration Ends

3:00 PM

Workshop Dates

2025-06-10
5 : 30 PM
5 : 30 PM
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What You Will Gain

Sample Certificate
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Outcomes

  • Develop a robust understanding of ML workflows
  • Hands-on exposure to tools like Python, scikit-learn, TensorFlow
  • Create and evaluate basic ML models
  • Learn to apply AI in real-world domains
  • Receive internationally recognized certification
  • Build a network with peers and mentors across the globe
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Who Should Attend

  • Students (UG/PG/PhD) from Science, Engineering, Data Science, IT, and related disciplines
  • Academicians and researchers
  • Industry professionals exploring ML and AI
  • Startups and entrepreneurs in tech domains

Gurpreet Kaur

Assistant Professor

Speciality: Machine Learning, Artificial Intelligence, Supervised Learning, Unsupervised Learning, Deep Learning, Neural Networks, Python, Data Science, Predictive Modeling, AI Ethics, Intelligent Systems, Applied AI, ML Careers, Global Workshop, e-Certificate

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