Data Science Hands-on Workshop

About Course

This Data Science Hans on Workshop aims to provide a deeper hands-on experience on data analysis, machine learning, and deep learning, and to help learners prepare data, detect statistical data biases, perform feature engineering at scale to train models, & train, evaluate, & tune models with AutoML.

Ingest, register, and explore datasets
Detect statistical bias in a dataset
Automatically train and select models with AutoML
Create machine learning features from raw data
Save and manage features in a feature store
Train and evaluate models using built-in algorithms and custom BERT models
Debug, profile, and compare models to improve performance
Build and run a complete ML pipeline end-to-end2 Implement Digital Circuits on Xilinx FPGAs and Altera FPGAs using Verilog HDL
Optimize model performance using hyperparameter tuning

Course Content

Analyze Datasets and Train ML Models using AutoML

Explore the use case and analyze the data set
Data Bias and Feature Importance
Use Automated Machine Learning to train a Text Classifier
Built in Algorithm

Data Science Hands-on Workshop

About Course

What Will You Learn?

Course Content

Analyze Datasets and Train ML Models using AutoML

Explore the use case and analyze the data set

Data Bias and Feature Importance

Use Automated Machine Learning to train a Text Classifier

Built in Algorithm

Build, Train, and Deploy ML Pipelines using BERT

Feature Engineering and Feature Store

Deploy End-To-End Machine Learning pipelines

Optimize ML Models and Deploy Human-in-the-Loop Pipelines

Advanced model training, tuning and evaluation

Advanced model deployment and monitoring

Data labelling and human-in-the-loop pipelines