Advanced Data Science & Machine Learning (ADSML)


Course Overview

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.

Who should attend

  • Data Engineers
  • Software Developers
  • Machine Learning Engineers

Outline: Advanced Data Science & Machine Learning (ADSML)

Deeper Data-Engineering Dives

  • SQL
  • Advanced Numpy
  • Advanced Pandas
  • Advanced Visualization

Deeper Deep Learning Dives

  • Keras and PyTorch
  • CNNs
  • Generative Models
  • PyTorch Lightning
  • Model Exchange with ONNX

Additional Models

  • 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

MLOps and Security

  • Data Engineering Pipelines
    • Apache Airflow
  • Deployment Architectures
    • Continuous Learning
    • Handling Streaming Data
  • Security
  • Threat Taxonomies
  • Monitoring, Logging, and Alerting

Prices & Delivery methods

Online Training

5 days

  • on request
Classroom Training

5 days

  • on request


Currently there are no training dates scheduled for this course.