Course curriculum

    1. DS 1.1 Machine Learning Applications in Finance - A Comprehensive Guide

    2. DS 1.1 Retail and Marketing Analytics - Comprehensive Guide

    3. DS 1.1.Data Science Applications in Healthcare - Transforming Modern Medicine

    4. DS 1.2 Advanced NLP Applications - Chatbots, Sentiment Analysis, Text Summarization

    5. DS 1.3 Industry Applications of Computer Vision - Object Detection & Image Recognition

    6. DS 1.4 Recommendation Systems - Personalization and User Profiling

    7. DS 1.5 IoT & Real-Time Analytics - Sensor Data & Device-Level Intelligence

    8. DS 2.1 Data Science & ML Programming Toolkit

    9. DS 2.2 Exploratory Data Analysis (EDA) – A Comprehensive Guide to Visualization

    10. DS 2.3 AI and Machine Learning Foundations - A Comprehensive

    11. DS 2.4 Feature Engineering - Basic Pipelines & Transformations

    12. DS 2.5 Data Storytelling - The Art of Communicating Insights Effectively

    13. DS 3.1 Modern Data Architectures - Navigating Data Lakes, Lakehouses, and Cloud Storage

    14. DS 3.2 Real-Time Data Processing - Kafka, Spark Streaming, Flink

    15. DS 3.3 Distributed Computing - Apache Spark and Dask

    16. DS 3.4 Vector Databases - Storing Embeddings for NLP and Computer Vision Tasks

    17. DS 3.5 Data Governance & Quality Framework

    18. DS 4.1.1 Agentic AI - Advanced Autonomous Intelligence Systems

    19. DS 4.1.2 Generative AI - Understanding LLMs, Diffusion Models, and Prompt Engineering

    20. DS 4.1.3 Deep Learning Architectures - CNNs, RNNs, Transformers

    21. DS 4.1.4 Explainable AI - Understanding LIME, SHAP, and Integrated Gradients

    22. DS 4.2.1 Advanced Optimization in Deep Learning - SGD Variants and Distributed Training

    23. DS 4.2.2 Edge & Federated Learning – Where Privacy-Preserving Approaches Apply

    24. DS 5.1 Conceptual MLOps Lifecycle A Comprehensive Guide

    25. DS 5.2-MLOps Essentials - CICD, Model Registries, Monitoring, and Retraining

    26. DS 5.3 Production Deployment for Machine Learning - Containerization and Kubernetes

    27. DS 5.4 AutoML & Feature Stores - Streamlining Machine Learning Experimentation

    28. DS 5.5 Ethical AI Frameworks for Fairness, Bias Detection, and Privacy

    1. DS 1.1 Healthcare Sector

    2. DS 1.2 Data Science Applications financial services through fraud detection

    3. DS 1.3 Retail & Marketing Analytics Powering the Future of Retail

About this course

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  • 31 lessons
  • 0 hours of video content

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