Curriculum

12 Chapters · 12 Lessons

  1. 1

    Book Preview

    1. Ultimate Python Libraries for Data Analysis and Visualization Free preview
  2. 2

    Introduction

    1. (Included in full purchase)

      Introduction

  3. 3

    Chapter 1 : Introduction to Data Analysis and Data Visualization using Python

    1. (Included in full purchase)

      Introduction to Data Analysis and Data Visualization using Python

  4. 4

    Chapter 2 : Data Acquisition

    1. (Included in full purchase)

      Data Acquisition

  5. 5

    Chapter 3 : Data Cleaning and Preparation

    1. (Included in full purchase)

      Data Cleaning and Preparation

  6. 6

    Chapter 4 : Exploratory Data Analysis

    1. (Included in full purchase)

      Exploratory Data Analysis

  7. 7

    Chapter 5 : Statistical Analysis

    1. (Included in full purchase)

      Statistical Analysis

  8. 8

    Chapter 6 : Time Series Analysis and Forecasting

    1. (Included in full purchase)

      Time Series Analysis and Forecasting

  9. 9

    Chapter 7 : Signal Processing

    1. (Included in full purchase)

      Signal Processing

  10. 10

    Chapter 8 : Analyzing Real-World Data Sets using Python

    1. (Included in full purchase)

      Analyzing Real-World Data Sets using Python

  11. 11

    APPENDIX A

    1. (Included in full purchase)

      Additional Questions

  12. 12

    Index

    1. (Included in full purchase)

      Index

About the course

Ultimate Data Analysis and Visualization with Python is your comprehensive guide to mastering the intricacies of data analysis and visualization using Python. This book serves as your roadmap to unlocking the full potential of Python for extracting insights from data using Pandas, NumPy, Matplotlib, Seaborn, and Julius AI. Starting with the fundamentals of data acquisition, you'll learn essential techniques for gathering and preparing data for analysis. From there, you’ll dive into exploratory data analysis, uncovering patterns and relationships hidden within your datasets. Through step-by-step tutorials, you'll gain proficiency in statistical analysis, time series forecasting, and signal processing, equipping you with the tools to extract actionable insights from any dataset. What sets this book apart is its emphasis on real-world applications. With a series of hands-on projects, you’ll apply your newfound skills to analyze diverse datasets spanning industries such as finance, healthcare, e-commerce, and more. By the end of the book, you'll have the confidence and expertise to tackle any data analysis challenge with Python. To aid your journey, the book includes a handy Python cheat sheet in the appendix, serving as a quick reference guide for common functions and syntax.

About the Author

Travis DeForge is the Manager of Cybersecurity Engineering at Gotham Security, a US-based boutique cybersecurity firm that provides high-quality penetration testing, malicious adversary simulation, threat intelligence, and cybersecurity strategy services. In this role, Travis routinely conducts network and web application penetration tests, social engineering engagements, and cloud security assessments for multibillion-dollar global organizations. Travis holds a Bachelor of Arts from the University of Vermont in Mandarin Chinese and a Master of Science from Western Governors University in Information Technology Management as well as numerous certifications in networking, project management, cyber security, cloud computing, and information technology including CompTIA SecuritY+, Network+, Pentest+ and Lean Six Sigma Blackbelt.