Advanced Data Science & Machine Learning

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

Duration

5 Days

Level

Advanced Level

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As per your team needs

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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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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

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This course assumes students have taken the Data Science with Python or have equivalent skills/experience.

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Advanced Data Science & Machine Learning

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