Introduction to PyKX
Introduction to PyKX, available at Free, with 22 lectures, and has 246 subscribers.
You will learn about Gain foundational understanding of PyKX and its applications Generate PyKX objects How to build and query PyKX tables Perform Time-Series analytics with PyKX This course is ideal for individuals who are Developers who want to learn the basics of the PyKX, create and query PyKX objects, learn to perform basic time-series analysis with PyKX.. or Developers who want to prepare for more advanced PyKX, KDB+, and q use-cases. It is particularly useful for Developers who want to learn the basics of the PyKX, create and query PyKX objects, learn to perform basic time-series analysis with PyKX.. or Developers who want to prepare for more advanced PyKX, KDB+, and q use-cases.
Enroll now: Introduction to PyKX
Summary
Title: Introduction to PyKX
Price: Free
Number of Lectures: 22
Number of Published Lectures: 22
Number of Curriculum Items: 22
Number of Published Curriculum Objects: 22
Original Price: Free
Quality Status: approved
Status: Live
What You Will Learn
- Gain foundational understanding of PyKX and its applications
- Generate PyKX objects
- How to build and query PyKX tables
- Perform Time-Series analytics with PyKX
Who Should Attend
- Developers who want to learn the basics of the PyKX, create and query PyKX objects, learn to perform basic time-series analysis with PyKX..
- Developers who want to prepare for more advanced PyKX, KDB+, and q use-cases.
Target Audiences
- Developers who want to learn the basics of the PyKX, create and query PyKX objects, learn to perform basic time-series analysis with PyKX..
- Developers who want to prepare for more advanced PyKX, KDB+, and q use-cases.
In this course, you will learn a foundational understanding of PyKX and its applications. You will learn about the basic data types and structures in PyKX, how to generate PyKX objects from Python objects, the skills to query large PyKX datasets, and perform time series analysis with PyKX. The course covers the essentials of working with PyKX, including setting up your environment, understanding the basic data structures, and leveraging the power of PyKX for efficient data processing.
This course is aimed at users who have a working knowledge of Python. No prior experience with kdb+/q is required. It is designed for users who want to grasp the basics of PyKX, enabling them to query data effectively and run basic time-series operations. Additionally, the course will delve into advanced querying techniques and optimization strategies for handling large datasets – including a comparison between Pandas and PyKX.
The Python notebook for each topic is available in that section’s introduction which includes real-world examples to reinforce your learning and ensure you can apply these skills in your own projects. Whether you are looking to enhance your data analysis capabilities or streamline your time-series data handling, this course will provide you with the necessary tools and insights. Join us to unlock the potential of PyKX and elevate your data processing skills.
Course Curriculum
Chapter 1: Course Introduction
Lecture 1: Introduction
Lecture 2: Sandbox Setup
Lecture 3: PyKX License Setup
Chapter 2: PyKX Basics
Lecture 1: Section Introduction: PyKX Basics
Lecture 2: PyKX Basics
Lecture 3: Generating PyKX Objects
Lecture 4: Indexing & Slicing
Lecture 5: Reading & Writing CSV Files
Chapter 3: Analytics on PyKX Objects
Lecture 1: Section Introduction: PyKX Analytics
Lecture 2: Analytics with the Pandas-like API
Lecture 3: PyKX Native Functions
Chapter 4: PyKX Tables
Lecture 1: Section Introduction: PyKX Tables
Lecture 2: PyKX Table Construction, Exploration, Interrogation
Lecture 3: Index, Filter, Sort, Group By
Lecture 4: PyKX Table Analytics
Lecture 5: Joins & Merges
Chapter 5: Querying Tables
Lecture 1: Section Introduction: Querying Tables
Lecture 2: Querying with qSQL
Lecture 3: Querying with Standard SQL and Through IPC
Chapter 6: Time Series Analytics
Lecture 1: Section Introduction: PyKX Time Series Analytics
Lecture 2: Date & Time Objects
Lecture 3: Time Series Operations
Instructors
-
Ryan Siegler
Data Science @ KX
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Frequently Asked Questions
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You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!
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