Data Analytics with Python
Apply Python and its extensive ecosystem to perform end-to-end data analytics on real-world datasets.
Get Course Info
Audience: Data Analysts / Data Scientists / Developers
Duration: 3 days
Format: Lectures and hands-on labs (50% lecture, 50% lab)
Overview
Python has become a powerful language and environment for performing data science. It combines a robust object-oriented language with a powerful library of data science packages such as NumPy, SciPy, Matplotlib, Scikit-learn, and Pandas. These tools together make Python one of the best combinations of robust programming language and great library support.
Objective
Apply Python and its extensive ecosystem to perform end-to-end data analytics on real-world datasets.
What You Will Learn
- Quick Python primer
- Data science algorithms overview
- NumPy
- SciPy
- Pandas
- Scikit-learn
Course Details
Audience: Data Analysts / Data Scientists / Developers
Duration: 3 days
Format: Lectures and hands-on labs (50% lecture, 50% lab)
- Software development experience
- Some analytics or ML background helpful
- Python experience recommended (a brief intro is included)
Setup: Zero-install cloud lab provided · SSH client · Chrome browser
Detailed Outline
- Basics of Python language
- Editing, running, and testing Python code
- Anaconda distribution of Python
- IDEs
- Jupyter notebooks
- Series and DataFrames
- Loading data using Pandas
- Labs
- Arrays
- Matrices
- Linear Algebra
- Labs
- Visualizing data with Matplotlib
- Introducing Scikit-Learn
- Clustering Data
- Building a Classifier
- Introduction to Spark and PySpark
- Using the Spark framework for Big Data
- Using MLlib for Data Science in PySpark
Ready to Get Started?
Contact us to learn more about this course and schedule your training.