Applied Data Science with Python and Jupyter
Course Outline
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 Benefits
- Jupyter Fundamentals
- Data Cleaning and Advanced Modeling
- Web Scraping and Interactive Visualizations
- Machine learning classification strategy
- Exploratory 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
- Scraping Web Page Data
- choosing a selection results in a full page refresh