Using Data Science Tools in Python (PY-3)

Location: Virtual or On-site

Length: 2 Days

Price: $1,600 per student

Overview:

More and more organizations are turning to data science to help guide business decisions. Regardless of industry, the ability to extract knowledge from data is crucial for a modern business to stay competitive. One of the tools at the forefront of data science is the Python® programming language. Python's robust libraries have given data scientists the ability to load, analyze, shape, clean, and visualize data in easy to use, yet powerful, ways. This course will teach you the skills you need to successfully use these key libraries to extract useful insights from data, and as a result, provide great value to the business.

Learn why Fulcrum Forge is the best choice to be your training partner.

Course Objectives:

In this course, you will use various Python tools to load, analyze, manipulate, and visualize business data. You will:

• Set up a Python data science environment.

• Manage and analyze data with NumPy arrays.

• Manipulate and modify data with NumPy arrays.

• Manage and analyze data with pandas DataFrames.

• Manipulate, modify, and visualize data with pandas DataFrames.

• Visualize data with Matplotlib and Seaborn.

Who Should Attend:

This course is designed for programmers or data analysts who wish to expand their ability to extract knowledge from business data and solve business problems using powerful programming libraries that go beyond the limitations of prepackaged GUI tools or database queries; libraries that give the data scientist more fine-tuned control over the analysis, manipulation, and presentation of data.

The target student for this course understands the principles and benefits of data science and has used basic data-driven tools like Microsoft® Excel® and Structured Query Language (SQL) queries, but wants to take the next steps into more advanced applications of data science.

A typical student in this course should have several years of experience with computing technology, along with a proficiency in programming.

Certification:

Not applicable.

Prerequisites:

• Introduction to Programming with Python®

• Advanced Programming Techniques with Python®

Detailed Course Outline

Lesson 1: Setting Up a Python Data Science Environment

Topic A: Select Python Data Science Tools

Topic B: Install Python Using Anaconda

Topic C: Set Up an Environment Using Jupyter Notebook

Lesson 2: Managing and Analyzing Data with NumPy

Topic A: Create NumPy Arrays

Topic B: Load and Save NumPy Data

Topic C: Analyze Data in NumPy Arrays

Lesson 3: Transforming Data with NumPy

Topic A: Manipulate Data in NumPy Arrays

Topic B: Modify Data in NumPy Arrays

Lesson 4: Managing and Analyzing Data with pandas

Topic A: Create Series and DataFrames

Topic B: Load and Save pandas Data

Topic C: Analyze Data in DataFrames

Topic D: Slice and Filter Data in DataFrames

Lesson 5: Transforming and Visualizing Data with pandas

Topic A: Manipulate Data in DataFrames

Topic B: Modify Data in DataFrames

Topic C: Plot DataFrame Data

Lesson 6: Visualizing Data with Matplotlib and Seaborn

Topic A: Create and Save Simple Line Plots

Topic B: Create Subplots

Topic C: Create Common Types of Plots

Topic D: Format Plots

Topic E: Streamline Plotting with Seaborn

Appendix A: Scraping Web Data Using Beautiful Soup

To discuss training options, call us at (888) 430-2456.