Attend this Applied Data Science with Python and Jupyter training course and learn about some of the most commonly used libraries that are part of the Anaconda distribution and then explore machine learning models with real datasets. You will also learn about creating reproducible data processing pipelines, visualizations, and prediction models, all with the goal of giving you the skills and exposure you’ll need for the real world.
Data Science is one of the fastest growing professions across all industries. Open source tools like Python have become increasingly popular, and when paired with Jupyter Notebooks, can provide a variety of data-science applications. Attend this one-day hands-on course and learn to leverage all that these powerful tools have to offer.
Knowledge of programming fundamentals and some experience with Python, including Python libraries, Pandas, Matplotlib, and scikit-learn.
Applied Data Science with Python and Jupyter Delivery Methods
After-course instructor coaching benefit
Applied Data Science with Python and Jupyter Course Benefits
Jupyter FundamentalsData Cleaning and Advanced ModelingWeb Scraping and Interactive VisualizationsMachine learning classification strategyExploratory data analysis and investigation
Applied Data Science with Python and Jupyter Training Outline
Lesson 1: Jupyter Fundamentals
Basic Functionality and Features
Our First Analysis – The Boston Housing Dataset
Lesson 2: Data Cleaning and Advanced Machine Learning
Lesson 3: Web Scraping and Interactive Visualizations