Advanced Data Science & Machine Learning

Skill-up with Advanced ML and Data Engineering tools to solve complex and dynamic business problems


5 Days


Advanced Level

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This will be a more advanced exploration of the libraries that developers will have been exposed to, deep learning, additional models, operationalization concerns of these systems, and the often-forgotten security aspects of data-driven systems. The goal will be to have as many hands-on activities as is feasible intermixed with a sufficient amount of theory to motivate the exercises.

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  • Data Engineers
  • Software Developers
  • Machine Learning Engineers
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  • SQL
  • Advanced Numpy
  • Advanced Pandas
  • Advanced Visualization
  • Keras and PyTorch
  •  CNNs
  •  Generative Models
  •  PyTorch Lightning
  • Model Exchange with ONNX
  •  Time Series Data
      • Classical Time Series Models
      • RNNs, LSTMs
      • PyTorch Forecasting
      • Anomaly Detection
    •  Ranking Models
      • Metrics
      • Models
    •  Multi-Modal Models
      • Representation
      • Alignment
      • Composaibility of Models
      • Modality Transference
      • Quantification
      • Multimodal Framework (MMF)
    •  NLP Models
      • Embeddings
      • Transformers
      • LMM and ChatGPT
  • Data Engineering Pipelines
    • Apache Airflow
  • Deployment Architectures
    • Continuous Learning
    • Handling Streaming Data
  • Security
  • Threat Taxonomies
  • Monitoring, Logging, and Alerting
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This course assumes students have taken the Data Science with Python or have equivalent skills/experience.


we'd love to have your feedback on your experience so far