Course Program

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#1Introduction to AI
  • What is Artificial Intelligence?---
  • History and Evolution of AI---
  • AI Applications and Examples---
#2Fundamentals of Machine Learning
  • Understanding Machine Learning---
  • Supervised vs Unsupervised Learning---
  • Popular Machine Learning Algorithms---
  • Data Preprocessing Techniques---
#3Natural Language Processing (NLP)
  • Basics of NLP---
  • Text Preprocessing Steps---
  • Understanding Tokenization---
  • Sentiment Analysis Techniques---
  • NLP With Python---
#4Deep Learning
  • Introduction to Neural Networks---
  • Deep Learning Frameworks---
  • Convolutional Neural Networks (CNNs)---
  • Recurrent Neural Networks (RNNs)---
  • Training Deep Learning Models---
#5AI and Big Data
  • Big Data Concepts---
  • Integrating AI with Big Data---
  • Data Storage and Retrieval---
  • Real-time Big Data Analysis---
#6Computer Vision
  • Basics of Computer Vision---
  • Object Detection Methods---
  • Image Classification---
  • Face Recognition Technology---
  • Image Segmentation Techniques---
#7AI Ethics and Governance
  • Ethical Concerns in AI---
  • AI Fairness and Bias---
  • Policies and Regulations---
  • Governance Structures for AI---
#8AI in Industry Applications
  • AI in Healthcare---
  • AI in Finance---
  • AI in Marketing---
  • AI for Customer Service---
#9Robust AI System Design
  • AI System Architectures---
  • Deployment Strategies---
  • Monitoring and Maintenance---
  • Scalability Considerations---
#10Emerging Trends in AI
  • AI Cold Fusion---
  • Enhanced Generalized Models---
  • Sustainable AI Practices---
#11Project-Based Learning in AI
  • Defining AI Project Requirements---
  • Hands-on Capstone Projects---
  • Collaborative Project Work---
  • Showcasing AI Project Outcomes---