Machine Learning Scientist

In this course, you'll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

5 hr

Build a regression model for a DVD rental firm to predict rental duration. Evaluate models to recommend the best one.

2 hr

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

4 hr

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

4 hr

Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.

4 hr

Learn how to clean and prepare your data for machine learning!

4 hr

This course focuses on feature engineering and machine learning for time series data.

4 hr

Create new features to improve the performance of your Machine Learning models.

4 hr

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

4 hr

Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.

4 hr

Master text analysis with essential NLP techniques from preprocessing to advanced transformer models.

4 hr

Master the core operations of spaCy and train models for natural language processing. Extract information from unstructured data and match patterns.

4 hr

Learn techniques to extract useful information from text and process them into a format suitable for machine learning.

4 hr

Learn how to build your first neural network, adjust hyperparameters, and tackle classification and regression problems in PyTorch.

4 hr

Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.

4 hr

Learn to process, transform, and manipulate images at your will.

4 hr

Master PySpark to handle big data with ease—learn to process, query, and optimize massive datasets for powerful analytics!

4 hr

Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.

4 hr

Learn how to approach and win competitions on Kaggle.

4 hr