Applied Data Science with Python and Jupyter

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, visualisations, 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 Fundamentals
• Data Cleaning and Advanced Modelling
• Web Scraping and Interactive Visualisations
• 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

Preparing to Train a Predictive Model

Training Classification Models

Lesson 3: Web Scraping and Interactive Visualisations

• Scraping Web Page Data