Python For Data Science

Training for Your Group

Training for Individuals

$1695

Course Overview

This Python for Data Science course takes a structured, in-depth approach, helping you not only learn how to apply data science but also why it matters. Through a carefully balanced mix of real-world case studies and the mathematical theory behind key data science algorithms, you’ll develop both the practical skills and foundational understanding needed to excel in the field.

Course Length: 3 Days

Audience: This course is ideal for both new programmers and experienced developers seeking to add Python to their skillset.

Prerequisites: Some experience in working with data from Excel, databases, or text files.

What You're Going To Learn

The Python for Data Science course teaches the fundamentals of Python for data analysis and visualization. Participants will work with key libraries like Pandas, NumPy, Matplotlib, and Seaborn to clean, transform, and analyze data. They will create interactive visualizations to communicate insights effectively and apply their skills through hands-on projects using Jupyter Notebook and real-world datasets.

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Course Outline

1. Introduction to Python for Data Science

  • Overview of Python and its role in data science

  • Setting up Python environments (Anaconda, Jupyter Notebooks)

  • Writing and running Python scripts

2. Working with Jupyter Notebooks

  • Introduction to Jupyter Notebooks

  • Markdown and code cells

  • Running, saving, and sharing notebooks

3. Numerical Computing with NumPy

  • Understanding arrays and their advantages

  • Creating and manipulating NumPy arrays

  • Mathematical operations and broadcasting

4. Data Manipulation with Pandas

  • Understanding Series and DataFrames

  • Importing and exploring datasets

  • Filtering, sorting, and transforming data

5. Data Input and Output (I/O)

  • Reading and writing Excel files

  • Working with CSV files

  • Connecting and querying SQL databases

6. Converting Datasets to Pandas DataFrames

  • Transforming structured and unstructured data

  • Importing datasets from APIs and web sources

7. Advanced Data Handling

  • Altering specific data using custom functions

  • Handling missing data – filling, dropping, and imputing values

  • Aggregating data using group operations

8. Data Visualization with Matplotlib

  • Creating fully customizable plots

  • Implementing custom figures and axis

  • Adding labels, legends, and annotations

9. Statistical Data Visualization with Seaborn

  • Creating scatter plots

  • Generating distribution plots

  • Visualizing summary statistics with box plots

10. Hands-on Projects and Real-World Applications

  • Data analysis case studies

  • End-to-end data science project

  • Best practices for working with large datasets

What to Expect at LeapFox

Knowledgeable Instructors

Our instructors are certified professionals. They are trained on the latest features and how to get the most out of software programs.

Hands-on Labs

No boring lectures! Our courses are designed to give students lots of time to practice what they are learning with hands-on exercises and projects.

Certificate of Completion

Receive a certificate of completion at the end of every course.

Up-to-date Curriculum

Each course comes with a helpful and up-to-date ebook which will contain instruction and practice exercises.

Time Saving Tips N Tricks

In each course, your instructor will show you tips and tricks that will save you time and make you more efficient.

Friendly and Helpful Staff

Our staff is dedicated to your success. Each team member is trained to provide the absolute best customer service possible.

Satisfaction Guarantee

If you aren't 100% satisfied with your experience at LeapFox, simply let us know, and we will make it right.

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